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1. The effect of physical activity level and exercise training on the association between plasma branched-chain amino acids and intrahepatic lipid content in participants with obesity

Author: Froukje Vanweert, Dennis O. Mook-Kanamori, Esther Phielix, Renée de Mutsert, Patrick Schrauwen, Frits R. Rosendaal, Hildo J. Lamb, Sebastiaan C. Boone, Bram Brouwers, Matthijs K. C. Hesselink, Vera B. Schrauwen-Hinderling, Nutrition and Movement Sciences, RS: NUTRIM - R1 - Obesity, diabetes and cardiovascular health, Promovendi NTM, MUMC+: DA BV Research (9), and MUMC+: DA BV Klinisch Fysicus (9)
Subjects: 0301 basic medicine, Male, medicine.medical_specialty, Epidemiology, Endocrinology, Diabetes and Metabolism, Medicine (miscellaneous), 030209 endocrinology & metabolism, Type 2 diabetes, Article, 03 medical and health sciences, 0302 clinical medicine, Valine, Non-alcoholic Fatty Liver Disease, Internal medicine, Medicine, Humans, Obesity, Exercise, Aged, chemistry.chemical_classification, Nutrition and Dietetics, business.industry, Fatty liver, Middle Aged, medicine.disease, Lipid Metabolism, Lipids, Physical activity level, Amino acid, 030104 developmental biology, Endocrinology, Cross-Sectional Studies, chemistry, Diabetes Mellitus, Type 2, Liver, Lipid content, Isoleucine, business, Amino Acids, Branched-Chain
Abstract: Aims To evaluate whether the association between plasma branched-chain amino acids (BCAA) and intrahepatic lipid (IHL) was affected by physical activity level. Furthermore, to investigate if a conventional exercise training program, a subcategory of physical activity, could lower plasma BCAA along with alterations in IHL content in patients with type 2 diabetes (T2DM) and people with nonalcoholic fatty liver (NAFL). Methods To investigate the effect of physical activity on the association between plasma BCAA and IHL content, linear regression analyses were performed in 1983 individuals from the Netherlands Epidemiology of Obesity (NEO) stratified by physical activity frequency. Furthermore, the effect of a 12-week supervised combined aerobic resistance-exercise program on plasma BCAA, insulin sensitivity (hyperinsulinemic–euglycemic clamp), and IHL (proton-magnetic resonance spectroscopy (1H-MRS)) was investigated in seven patients with T2DM, seven individuals with NAFL and seven BMI-matched control participants (CON). Results We observed positive associations between plasma valine, isoleucine and leucine level, and IHL content (1.29 (95% CI: 1.21, 1.38), 1.52 (95% CI: 1.43, 1.61), and 1.54 (95% CI: 1.44, 1.64) times IHL, respectively, per standard deviation of plasma amino acid level). Similar associations were observed in less active versus more active individuals. Exercise training did not change plasma BCAA levels among groups, but reduced IHL content in NAFL (from 11.6 ± 3.0% pre-exercise to 8.1 ± 2.0% post exercise, p p p Conclusions The association between plasma BCAA levels and IHL is not affected by physical activity level. Exercise training reduced IHL without affecting plasma BCAA levels in individuals with NAFL and CON. We conclude that exercise training-induced reduction in IHL content is not related to changes in plasma BCAA levels. Trial registration Trial registry number: NCT01317576.
Published: 2021

2. Association of measures of body fat with serum alpha-tocopherol and its metabolites in middle-aged individuals

Author: Leon G. Martens, Nadia Ashrafi, Kevin Mills, Frits R. Rosendaal, Jiao Luo, Diana van Heemst, Fleur L. Meulmeester, Hildo J. Lamb, Renée de Mutsert, Dennis O. Mook-Kanamori, Ko Willems van Dijk, and Raymond Noordam
Subjects: Male, medicine.medical_specialty, Subcutaneous adipose tissue, Epidemiology, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Urinary system, alpha-Tocopherol, Medicine (miscellaneous), Adipose tissue, 030209 endocrinology & metabolism, Urine, Intra-Abdominal Fat, 030204 cardiovascular system & hematology, Body Mass Index, Vitamin E metabolites, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Internal medicine, medicine, Humans, Obesity, Adiposity, Netherlands, Nutrition and Dietetics, Mass spectrometry, business.industry, Vitamin E, Confounding, Age Factors, Alpha tocopherol, Middle Aged, medicine.disease, Cross-Sectional Studies, Endocrinology, chemistry, Visceral adipose tissue, Obesity, Abdominal, Female, Lipid Peroxidation, Cardiology and Cardiovascular Medicine, business, Body mass index, Biomarkers
Abstract: Background and aims: The accumulation of fat increases the formation of lipid perox-ides, which are partly scavenged by alpha-tocopherol (a-TOH). Here, we aimed to investigate the associations between different measures of (abdominal) fat and levels of urinary a-TOH metab-olites in middle-aged individuals. Methods and results: In this cross-sectional analysis in the Netherlands Epidemiology of Obesity study (N Z 511, 53% women; mean [SD] age of 55 [6.1] years), serum a-TOH and a-TOH metab-olites from 24-h urine were measured as alpha-tocopheronolactone hydroquinone (a-TLHQ, oxidized) and alpha-carboxymethyl-hydroxychroman (a-CEHC, enzymatically converted) using liquid-chromatography-tandem mass spectrometry. Body mass index and total body fat were measured, and abdominal subcutaneous and visceral adipose tissue (aSAT and VAT) were as-sessed using magnetic resonance imaging. Using multivariable-adjusted linear regression ana -lyses, we analysed the associations of BMI, TBF, aSAT and VAT with levels of urinary a-TOH metabolites, adjusted for confounders. We observed no evidence for associations between body fat measures and serum a-TOH. Higher BMI and TBF were associated with lower urinary levels of TLHQ (0.95 [95%CI: 0.90, 1.00] and 0.94 [0.88, 1.01] times per SD, respectively) and with lower TLHQ relative to CEHC (0.93 [0.90, 0.98] and 0.93 [0.87, 0.98] times per SD, respectively). We observed similar associations for VAT (TLHQ: 0.94 [0.89, 0.99] times per SD), but not for aSAT. Conclusions: Opposite to our research hypothesis, higher abdominal adiposity was moderately associated with lower levels of oxidized a-TOH metabolites, which might reflect lower vitamin E antioxidative activity in individuals with higher abdominal fat instead. (c) 2021 The Author(s). Published by Elsevier B.V. on behalf of The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Published: 2021

3. The Relation Between Adult Weight Gain, Adipocyte Volume, and the Metabolic Profile at Middle Age

Author: Costantinos Christodoulides, Inge Verkouter, Dennis O. Mook-Kanamori, Frits R. Rosendaal, Fredrik Karpe, Nellie Y. Loh, Peter L. Zock, Renée de Mutsert, Saskia le Cessie, Raymond Noordam, and Ko Willems van Dijk
Subjects: 0301 basic medicine, Male, Aging, Endocrinology, Diabetes and Metabolism, Biopsy, Clinical Biochemistry, 030204 cardiovascular system & hematology, Biochemistry, Cohort Studies, chemistry.chemical_compound, 0302 clinical medicine, Endocrinology, Adipocyte, Adipocytes, Medicine, Netherlands, chemistry.chemical_classification, weight gain, Middle Aged, metabolomics, metabolic profile, Nutritional Biology, Metabolome, Female, medicine.symptom, AcademicSubjects/MED00250, Polyunsaturated fatty acid, medicine.medical_specialty, Lipoproteins, Abdominal Fat, Context (language use), body mass index, 03 medical and health sciences, Internal medicine, cohort study, Humans, Obesity, Online Only Articles, Clinical Research Articles, adipocyte volume, business.industry, Biochemistry (medical), Middle age, 030104 developmental biology, chemistry, Adipocyte hypertrophy, business, Weight gain, Body mass index, Lipoprotein
Abstract: Context Weight gain during adulthood increases cardiometabolic disease risk, possibly through adipocyte hypertrophy. Objective We aimed to study the specific metabolomic profile of adult weight gain, and to examine its association with adipocyte volume. Methods Nuclear magnetic resonance–based metabolomics were measured in the Netherlands Epidemiology of Obesity (NEO) study (n = 6347, discovery) and Oxford Biobank (n = 6317, replication). Adult weight gain was calculated as the absolute difference between body mass index (BMI) at middle age and recalled BMI at age 20 years. We performed linear regression analyses with both exposures BMI at age 20 years and weight gain, and separately with BMI at middle age in relation to 149 serum metabolomic measures, adjusted for age, sex, and multiple testing. Additionally, subcutaneous abdominal adipocyte biopsies were collected in a subset of the Oxford Biobank (n = 114) to estimate adipocyte volume. Results Mean (SD) weight gain was 4.5 (3.7) kg/m2 in the NEO study and 3.6 (3.7) kg/m2 in the Oxford Biobank. Weight gain, and not BMI at age 20 nor middle age, was associated with concentrations of 7 metabolomic measures after successful replication, which included polyunsaturated fatty acids, small to medium low-density lipoproteins, and total intermediate-density lipoprotein. One SD weight gain was associated with 386 μm3 (95% CI, 143-629) higher median adipocyte volume. Adipocyte volume was associated with lipoprotein particles specific for adult weight gain. Conclusion Adult weight gain is associated with specific metabolomic alterations of which the higher lipoprotein concentrations were likely contributed by larger adipocyte volumes, presumably linking weight gain to cardiometabolic disease.
Published: 2021

4. Sampling Strategies for Internal Validation Samples for Exposure Measurement–Error Correction: A Study of Visceral Adipose Tissue Measures Replaced by Waist Circumference Measures

Author: Maarten van Smeden, Renée de Mutsert, Rolf H.H. Groenwold, Frits R. Rosendaal, and Linda Nab
Subjects: Male, Epidemiology, Calibration (statistics), Practice of Epidemiology, Sample (statistics), Intra-Abdominal Fat, Sampling Studies, 03 medical and health sciences, 0302 clinical medicine, Bias, Statistics, substitute exposure measurement, Humans, AcademicSubjects/MED00860, 030212 general & internal medicine, Mathematics, Aged, Observational error, Models, Statistical, measurement-error correction, Sampling (statistics), Reproducibility of Results, regression calibration, Middle Aged, Circumference, internal validation sample, Cross-Sectional Studies, Sample size determination, Research Design, 030220 oncology & carcinogenesis, Sample Size, Calibration, Errors-in-variables models, Female, Insulin Resistance, Waist Circumference, Error detection and correction
Abstract: Statistical correction for measurement error in epidemiologic studies is possible, provided that information about the measurement error model and its parameters are available. Such information is commonly obtained from a randomly sampled internal validation sample. It is however unknown whether randomly sampling the internal validation sample is the optimal sampling strategy. We conducted a simulation study to investigate various internal validation sampling strategies in conjunction with regression calibration. Our simulation study showed that for an internal validation study sample of 40% of the main study’s sample size, stratified random and extremes sampling had a small efficiency gain over random sampling (10% and 12% decrease on average over all scenarios, respectively). The efficiency gain was more pronounced in smaller validation samples of 10% of the main study’s sample size (i.e., a 31% and 36% decrease on average over all scenarios, for stratified random and extremes sampling, respectively). To mitigate the bias due to measurement error in epidemiologic studies, small efficiency gains can be achieved for internal validation sampling strategies other than random, but only when measurement error is nondifferential. For regression calibration, the gain in efficiency is, however, at the cost of a higher percentage bias and lower coverage.
Published: 2021

5. The Separate Contributions of Visceral Fat and Liver Fat to Chronic Kidney Disease-Related Renal Outcomes

Author: Frits R. Rosendaal, Ton J. Rabelink, Hildo J. Lamb, Renée de Mutsert, Aiko P. J. de Vries, Ilona A. Dekkers, and Roelof A.J. Smit
Subjects: Male, 0301 basic medicine, medicine.medical_specialty, 030232 urology & nephrology, Medicine (miscellaneous), Adipose tissue, Renal function, Intra-Abdominal Fat, Kidney, urologic and male genital diseases, Gastroenterology, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Mendelian randomization, medicine, Albuminuria, Humans, Renal Insufficiency, Chronic, Triglycerides, Aged, Netherlands, 030109 nutrition & dietetics, Nutrition and Dietetics, business.industry, Fatty liver, nutritional and metabolic diseases, Odds ratio, Middle Aged, medicine.disease, Confidence interval, Fatty Liver, Cross-Sectional Studies, Nephrology, Female, Microalbuminuria, business, Kidney disease
Abstract: Objectives: This study aims to investigate the separate contributions of liver fat and visceral fat on microalbuminuria and impaired renal function, and second, to examine whether non-alcoholic fatty liver disease is causally related to microalbuminuria and/or impaired renal function.Methods: Associations between visceral adipose tissue (VAT), hepatic triglyceride content (HTGC), and risk of microalbuminuria and renal function were studied cross-sectionally in the Netherlands Epidemiology of Obesity study. Mendelian randomization using GWAS meta-analysis data was performed to estimate the causal effect of non-alcoholic fatty liver disease (PNPLA3, LYPLAL1, NCAN, GCKR) on eGFR (N-max 118,460), microalbuminuria (N-max 54,116), and impaired renal function (N-max 118,147).Results: In total, 2,023 participants (mean age 55.5 +/- 6.0 years, 53% women) were included of which 29% had fatty liver and 2.0% chronic kidney disease stage >= 3. In joint models, VAT was associated with a 2-fold increased risk of microalbuminuria which was mainly driven by the association in women (total population: per standard deviation [SD] = 55.4 cm(2), odds ratio [OR] 2.02, 95% confidence interval [CI] 1.18-3.47; women: OR 2.83, 95% CI 1.44, 5.56), but HTGC was not (total population: per SD = 7.9%, OR 1.20, 95% CI 0.85, 1.70). No associations were found for VAT and HTGC with eGFR (VAT: per SD = 55.4 cm(2), OR 1.25, 95% CI 0.83, 1.87; HTGC: per SD = 7.9%, OR 0.65, 95% CI 0.42, 0.99). No causal effect of NAFLD on microalbuminuria or impaired renal function was found.Conclusions: In observational analyses, visceral fat was associated with microalbuminuria in women. Liver fat was not associated with microalbuminuria or renal function, which was supported by Mendelian randomization. Visceral fat might be more important than liver fat in the etiology of microalbuminuria. (C) 2019 by the National Kidney Foundation, Inc. All rights reserved.
Published: 2020

6. Hepatic saturated fatty acid fraction is associated with de novo lipogenesis and hepatic insulin resistance

Author: Marcus Ståhlman, Patrick Schrauwen, Carlijn M. E. Remie, Pandichelvam Veeraiah, Martijn C. G. J. Brouwers, Bas Havekes, Yvonne M. H. Bruls, Vera B. Schrauwen-Hinderling, Esther Phielix, Renée de Mutsert, Marja-Riitta Taskinen, Kay H. M. Roumans, Lucas Lindeboom, Jan Borén, Bart Staels, Marjan Alssema, Harry P. F. Peters, Maastricht University [Maastricht], Maastricht University Medical Centre (MUMC), University of Gothenburg (GU), Sahlgrenska University Hospital [Gothenburg], Unilever Food Innovation Center [Wageningue, Pays-Bas], Leiden University Medical Center (LUMC), Universiteit Leiden, Récepteurs nucléaires, maladies cardiovasculaires et diabète - U 1011 (RNMCD), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, This research was in part financed by the Ministry of Economic Affairs and Climate Policy by means of the PPP Allowance made available by the Top Sector Life Sciences & Health to stimulate public–private partnerships and by Unilever R&D Wageningen. We acknowledge the support from the Netherlands Cardiovascular Research Initiative: an initiative with support of the Dutch Heart Foundation (CVON2014-02 ENERGISE). L.L. is a recipient of a veni grant from ZonMW (016.veni.188.036) and a junior fellowship (2017.81.004) from the Diabetes Fonds (Dutch Diabetes Research Foundation). B.S. is a recipient of an Advanced ERC Grant (694717). V.B.S.-H. is a recipient of an ERC starting grant (grant no. 759161 ‘MRS in diabetes’)., European Project: 694717,H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) ,ImmunoBile(2016), Nutrition and Movement Sciences, RS: NUTRIM - R1 - Obesity, diabetes and cardiovascular health, Beeldvorming, Interne Geneeskunde, MUMC+: MA Endocrinologie (9), RS: Carim - V01 Vascular complications of diabetes and metabolic syndrome, MUMC+: DA BV Research (9), MUMC+: DA BV Klinisch Fysicus (9), University of Helsinki, HUS Heart and Lung Center, Clinicum, CAMM - Research Program for Clinical and Molecular Metabolism, Research Programs Unit, Bodescot, Myriam, and Bile acid, immune-metabolism, lipid and glucose homeostasis - ImmunoBile - - H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) 2016-09-01 - 2021-08-31 - 694717 - VALID
Subjects: 0301 basic medicine, Male, Type 2/metabolism, General Physics and Astronomy, Type 2 diabetes, Lipogenesis/physiology, 0302 clinical medicine, Non-alcoholic Fatty Liver Disease, Triglycerides/metabolism, BRAIN, lcsh:Science, RISK, chemistry.chemical_classification, SPECTROSCOPY, Multidisciplinary, Fatty liver, Fatty Acids, food and beverages, Liver/diagnostic imaging, Middle Aged, Lipids, 3. Good health, Fatty Acids/metabolism, Adipose Tissue, Liver, CARDIOVASCULAR-DISEASE, Lipogenesis, Saturated fatty acid, Female, Polyunsaturated fatty acid, Adult, medicine.medical_specialty, Science, 030209 endocrinology & metabolism, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Insulin resistance, Non-alcoholic Fatty Liver Disease/metabolism, LIVER-DISEASE, Diabetes mellitus, Internal medicine, Diabetes Mellitus, medicine, STEATOSIS, Humans, Triglycerides, Aged, [SDV.MHEP.HEG]Life Sciences [q-bio]/Human health and pathology/Hépatology and Gastroenterology, General Chemistry, medicine.disease, Diabetes Mellitus, Type 2/metabolism, [SDV.MHEP.HEG] Life Sciences [q-bio]/Human health and pathology/Hépatology and Gastroenterology, MICE, 030104 developmental biology, Endocrinology, Cross-Sectional Studies, chemistry, Diabetes Mellitus, Type 2, 3121 General medicine, internal medicine and other clinical medicine, lcsh:Q, Steatosis, Insulin Resistance, Insulin Resistance/physiology
Abstract: Hepatic steatosis is associated with poor cardiometabolic health, with de novo lipogenesis (DNL) contributing to hepatic steatosis and subsequent insulin resistance. Hepatic saturated fatty acids (SFA) may be a marker of DNL and are suggested to be most detrimental in contributing to insulin resistance. Here, we show in a cross-sectional study design (ClinicalTrials.gov ID: NCT03211299) that we are able to distinguish the fractions of hepatic SFA, mono- and polyunsaturated fatty acids in healthy and metabolically compromised volunteers using proton magnetic resonance spectroscopy (1H-MRS). DNL is positively associated with SFA fraction and is elevated in patients with non-alcoholic fatty liver and type 2 diabetes. Intriguingly, SFA fraction shows a strong, negative correlation with hepatic insulin sensitivity. Our results show that the hepatic lipid composition, as determined by our 1H-MRS methodology, is a measure of DNL and suggest that specifically the SFA fraction may hamper hepatic insulin sensitivity., Hepatic steatosis is associated with poor cardiometabolic health, with de novo lipogenesis (DNL) contributing to hepatic steatosis and subsequent insulin resistance. Here, the authors use 1H-MRS methodology to show hepatic SFA fraction is a measure of DNL and specifically may hamper hepatic insulin sensitivity.
Published: 2020

7. Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses

Author: Robert A. Schoevers, Mohsen Ghanbari, Annemarie I. Luik, Bastiaan T. Heijmans, Nienke R. Biermasz, Brenda W.J.H. Penninx, Carisha S. Thesing, Aeilko H. Zwinderman, Ruifang Li-Gao, Kaitlin H Wade, Frits R. Rosendaal, Dorret I. Boomsma, M. Arfan Ikram, Marian Beekman, Dennis O. Mook-Kanamori, Lisanne S. Vijfhuizen, P. Eline Slagboom, Debbie A Lawlor, Matthew Lee, Naveed Sattar, Matt J. Neville, Stella Trompet, J. Wouter Jukema, L.H. Lumey, Diana van Heemst, Ian Ford, Renée de Mutsert, Rima Mustafa, Patrick C.N. Rensen, Xiang Zhang, M.M. Bos, Abbas Dehghan, Carolien A. Wijsman, Gonneke Willemsen, Gisela M. Terwindt, Irene de Boer, Raymond Noordam, Ko Willems van Dijk, René Pool, Fredrik Karpe, Arn M. J. M. van den Maagdenberg, Neil Goulding, Rebecca C Richmond, Simon P. Mooijaart, Amy Hofman, Constantinos Christodoulides, Chihua Li, Mariska Bot, Neurosurgery, ANS - Neurodegeneration, ANS - Systems & Network Neuroscience, Epidemiology and Data Science, APH - Methodology, Clinical Cognitive Neuropsychiatry Research Program (CCNP), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Psychiatry, APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Digital Health, Epidemiology, Biological Psychology, APH - Health Behaviors & Chronic Diseases, and APH - Personalized Medicine
Subjects: medicine.medical_specialty, Epidemiology, lcsh:Medicine, Physiology, Coronary Artery Disease, Polymorphism, Single Nucleotide, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Metabolic Diseases, SDG 3 - Good Health and Well-being, Risk Factors, Mendelian randomization, medicine, Insomnia, Humans, Metabolomics, Isoleucine, sleep, Aged, 030304 developmental biology, 2. Zero hunger, 0303 health sciences, Creatinine, business.industry, lcsh:R, Chronotype, General Medicine, Mendelian Randomization Analysis, R1, Confidence interval, 3. Good health, Cross-Sectional Studies, Phenotype, chemistry, Human and Animal Physiology, Cohort, Fysiologie van Mens en Dier, medicine.symptom, business, Sleep, Body mass index, 030217 neurology & neurosurgery, Research Article, Genome-Wide Association Study
Abstract: Background Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease. Methods We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions. Results We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (− 0.08 standard deviation (SD)[95% confidence interval (CI) − 0.12, − 0.03] in AMV and − 0.03SD [− 0.07, − 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (− 0.04SD [− 0.08, 0.00] in AMV and − 0.05SD [− 0.09, − 0.02] in MR), and lower phospholipids in very large HDL particles (− 0.04SD [− 0.08, 0.002] in AMV and − 0.05SD [− 0.08, − 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures. Conclusions Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.
Published: 2021

8. Estimated pulse wave velocity (ePWV) as a potential gatekeeper for MRI-assessed PWV

Author: Max J P van Hout, Martin J. Schalij, Arthur J.H.A. Scholte, Hildo J. Lamb, Renée de Mutsert, Jos J.M. Westenberg, Frits R. Rosendaal, J. Wouter Jukema, Sebastiaan C. Boone, Ralph L. Widya, Ling Lin, and Ilona A. Dekkers
Subjects: Adult, Male, 030204 cardiovascular system & hematology, Pulse Wave Analysis, 03 medical and health sciences, 0302 clinical medicine, Vascular Stiffness, Magnetic resonance imaging, Discriminative model, Predictive Value of Tests, Statistics, Range (statistics), Medicine, Humans, Radiology, Nuclear Medicine and imaging, 030212 general & internal medicine, Obesity, Pulse wave velocity, Aged, Netherlands, Artificial neural network, business.industry, Regression analysis, Anthropometry, Middle Aged, Regression, Epidemiology of obesity, Prediction modelling, Female, Neural Networks, Computer, Cardiology and Cardiovascular Medicine, business
Abstract: Pulse wave velocity (PWV) assessed by magnetic resonance imaging (MRI) is a prognostic marker for cardiovascular events. Prediction modelling could enable indirect PWV assessment based on clinical and anthropometric data. The aim was to calculate estimated-PWV (ePWV) based on clinical and anthropometric measures using linear ridge regression as well as a Deep Neural Network (DNN) and to determine the cut-off which provides optimal discriminative performance between lower and higher PWV values. In total 2254 participants from the Netherlands Epidemiology of Obesity study were included (age 45–65 years, 51% male). Both a basic and expanded prediction model were developed. PWV was estimated using linear ridge regression and DNN. External validation was performed in 114 participants (age 30–70 years, 54% female). Performance was compared between models and estimation accuracy was evaluated by ROC-curves. A cut-off for optimal discriminative performance was determined using Youden’s index. The basic ridge regression model provided an adjusted R2 of 0.33 and bias of 2: 0.29). All models showed good discriminative performance for PWV
Published: 2021

9. Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations

Author: Nicholas J. Wareham, Carol A. Wang, Daniel I. Chasman, Yasmin Mossavar-Rahmani, Jordi Merino, Ruifang Li-Gao, Jessica C. Kiefte-de Jong, Rozenn N. Lemaitre, Paul M. Ridker, Kent D. Taylor, Gina M. Peloso, Achilleas N. Pitsillides, Craig E. Pennell, Wendy H. Oddy, Linda Snetselaar, Kim V.E. Braun, Nathan L. Tintle, Alice H. Lichtenstein, Nita G. Forouhi, James B. Meigs, Alexis C. Wood, M. Arfan Ikram, Fumiaki Imamura, Melanie Guirette, Jason Westra, Jorma Viikari, Frits R. Rosendall, Kristin L. Young, Dennis O. Mook-Kanamori, Renée de Mutsert, Jian'an Luan, Mika Helminen, Dariush Mozaffarian, Jerome I. Rotter, Niina Pitkänen, Danielle E. Haslam, Olli T. Raitakari, Steven Rich, JoAnn E. Manson, Trudy Voortman, Nicola M. McKeown, Mariaelisa Graff, Mohsen Ghanbari, Josée Dupuis, Mark A. Herman, Kari E. North, Terho Lehtimäki, Caren E. Smith, Bruce M. Psaty, Hassan S. Dashti, Samia Mora, Traci M. Bartz, André G. Uitterlinden, Kara A Livingston, Mika Kähönen, Lisa W. Martin, Imamura, Fumiaki [0000-0002-6841-8396], Luan, Jian'an [0000-0003-3137-6337], Forouhi, Nita [0000-0002-5041-248X], Wareham, Nicholas [0000-0003-1422-2993], Apollo - University of Cambridge Repository, Epidemiology, Radiology & Nuclear Medicine, Internal Medicine, Tampere University, Department of Clinical Physiology and Nuclear Medicine, Clinical Medicine, Tays Research Services, Health Sciences, and Department of Clinical Chemistry
Subjects: 0301 basic medicine, Male, carbohydrates, Cardiovascular, chemistry.chemical_compound, 0302 clinical medicine, High-density lipoprotein, genetics, 030212 general & internal medicine, Sugar-Sweetened Beverages, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, General Medicine, Single Nucleotide, Middle Aged, Cholesterol, nutrition, Biochemistry, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, Female, epidemiology, Adult, HDL, Locus (genetics), Polymorphism, Single Nucleotide, 03 medical and health sciences, Meta-Analysis as Topic, Genetics, Humans, triglyceride, Polymorphism, Sugar, Carbohydrate-responsive element-binding protein, Transcription factor, Triglycerides, Triglyceride, Human Genome, Cholesterol, HDL, dyslipidemia, Original Articles, Carbohydrate, 3141 Health care science, stomatognathic diseases, 030104 developmental biology, chemistry, sugars, 3111 Biomedicine
Abstract: Supplemental Digital Content is available in the text., Background: ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the CHREBP locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the CHREBP locus and dyslipidemia. Methods: Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near CHREBP were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake. Results: In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16–3.07] mg/dL per allele; P
Published: 2021

10. Differential effect of statin use on coagulation markers

Author: J. Wouter Jukema, Renée de Mutsert, Willem M. Lijfering, Melike Cevval, Frits R. Rosendaal, and Mohammadreza Bordbar
Subjects: medicine.medical_specialty, Statin, medicine.drug_class, Fibrate, 030204 cardiovascular system & hematology, Fibrinogen, Niacin, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Diabetes mellitus, Statistical significance, medicine, Diseases of the blood and blood-forming organs, 030212 general & internal medicine, business.industry, Research, Statins, Coagulation factors, nutritional and metabolic diseases, Hematology, medicine.disease, Confidence interval, RC633-647.5, business, Body mass index, Fibrates, medicine.drug, Venous thromboembolism
Abstract: Background Statins are a potential treatment for venous thromboembolism (VTE) prophylaxis complementary to conventional anticoagulants without associated bleeding complications. This study aimed to compare pro-thrombotic activities of different classes of lipid-lowering drugs in an active comparator design and determine whether there is a relation between statin versus fibrate/niacin use and pro-coagulant factor outcomes. Methods This is a cross-sectional analysis of participants from the Netherlands Epidemiology of Obesity study using any class of lipid-lowering drugs, including any types of statins, niacin, and fibrates. We performed linear regression analyses to determine fibrinogen, factor (F) VIII, FIX, and FXI activity in statins versus fibrate/niacin users and adjusted for age, sex, tobacco smoking, body mass index (BMI), hypertension, diabetes, and prevalent cardiovascular disease. Results Among 1043 participants, the mean age was 58.4 ± 5.2 years, 61% were men, and the mean BMI was 31.3 ± 4.5 kg/m2. Clinical characteristics were balanced between statin and fibrate/niacin users. Statin users had lower mean FXI (18.3 IU/dL, 95% confidence interval (CI) 9.4 to 27.3) levels compared to fibrate/niacin users. The level of FVIII (15.8 IU/dL, 95% CI − 0.003 to 31.6), and FIX (11.3 IU/dL, 95% CI − 0.4 to 23.2) were lower in statin users than fibrate/niacin users with marginal statistical significance. Conclusion Current statin use was associated with lower plasma levels of FXI than fibrate/niacin use. The effects on coagulation factors may, in part, explain the benefit of statin therapy rendered in primary and secondary prevention of VTE.
Published: 2021

11. Urinary oxidized, but not enzymatic vitamin E metabolites are inversely associated with measures of glucose homeostasis in middle-aged healthy individuals

Author: Diana van Heemst, Fleur L. Meulmeester, Nadia Ashrafi, Dennis O. Mook-Kanamori, Frits R. Rosendaal, Kevin Mills, Raymond Noordam, Jiao Luo, Renée de Mutsert, Ko Willems van Dijk, Saskia le Cessie, and Leon G. Martens
Subjects: Blood Glucose, Male, 0301 basic medicine, Metabolite, medicine.medical_treatment, Urine, Critical Care and Intensive Care Medicine, Glucose homeostasis, Body Mass Index, Lipid peroxidation, chemistry.chemical_compound, 0302 clinical medicine, Homeostasis, Vitamin E, Prospective Studies, Netherlands, education.field_of_study, Nutrition and Dietetics, Middle Aged, Healthy Volunteers, Postprandial, Female, Oxidation-Reduction, Vitamin E, Alpha-tocopherol, Glucose homeostasis, Insulin resistance, medicine.medical_specialty, Population, 030209 endocrinology & metabolism, 03 medical and health sciences, Insulin resistance, Internal medicine, medicine, Humans, Chromans, education, Aged, 030109 nutrition & dietetics, business.industry, medicine.disease, Cross-Sectional Studies, Endocrinology, chemistry, Linear Models, Alpha-tocopherol, Lipid Peroxidation, Propionates, alpha-Tocopherol, business
Abstract: Background & aims: Damage induced by lipid peroxidation has been associated with impaired glucose homeostasis. Vitamin E (alpha-tocopherol, alpha-TOH) competitively reacts with lipid peroxyl radicals to mitigate oxidative damage, and forms oxidized vitamin E metabolites. Accordingly, we aimed to investigate the associations between alpha-TOH metabolites (oxidized and enzymatic) in both circulation and urine and measures of glucose homeostasis in the general middle-aged population. Methods: This cross-sectional study was embedded in the population-based Netherlands Epidemiology of Obesity (NEO) Study. alpha-TOH metabolites in blood (alpha-TOH and alpha-CEHC-SO3) and urine [sulfate (SO3) and glucuronide (GLU) of both alpha-TLHQ (oxidized) and alpha-CEHC (enzymatic)] were quantified by liquid chromatography coupled with tandem mass spectrometry (LC/MSeMS). Measures of glucose homeostasis (HOMA-B, HOMA-IR, Insulinogenic index and Matsuda index) were obtained from fasting and postprandial blood samples. Multivariable linear regression analyses were performed to assess the associations of alpha-TOH metabolites and measures of glucose homeostasis. Results: We included 498 participants (45% men) with mean (SD) age of 55.8 (6.1) years who did not use glucose-lowering medication. While blood alpha-TOH was not associated with measures of glucose homeostasis, urinary oxidized metabolites (alpha-TLHQ-SO3/GLU) were associated with HOMA-IR and Matsuda index. For example, a one-SD higher alpha-TLHQ-SO3 was associated with 0.92 (95% CI: 0.87, 0.97) fold lower HOMA-IR and 1.06 (1.01, 1.11) fold higher Matsuda index, respectively. Similar results were obtained for the urinary alpha-TLHQ to alpha-CEHC ratio as a measure of oxidized-over-enzymatic conversion of alpha-TOH. Conclusion: Higher urinary levels of oxidized alpha-TOH metabolites as well as higher oxidized-to-enzymatic alpha-TOH metabolite ratio, but not circulating alpha-TOH or enzymatic metabolites, were associated with lower insulin resistance. Rather than circulating alpha-TOH, estimates of the conversion of alpha-TOH might be informative in relation to health and disease. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/
Published: 2021

12. Electrocardiographic Detection of Left Ventricular Hypertrophy; Adding Body Mass Index and Spatial QRS-T Angle: A Cross-Sectional Study

Author: Peter W. Macfarlane, J. Wouter Jukema, Hildo J. Lamb, Frits R. Rosendaal, Arie C. Maan, Renée de Mutsert, Theodora W. Elffers, and Stella Trompet
Subjects: lcsh:Diseases of the circulatory (Cardiovascular) system, medicine.medical_specialty, Cross-sectional study, 030204 cardiovascular system & hematology, Left ventricular hypertrophy, Electrocardiography, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine, Obesity, cardiovascular diseases, 030212 general & internal medicine, Risk factor, Original Research, medicine.diagnostic_test, business.industry, Spatial QRS-T angle, medicine.disease, lcsh:RC666-701, Cardiology, Cardiology and Cardiovascular Medicine, business, Body mass index, Cardiovascular outcomes
Abstract: Introduction We investigated improvement of electrocardiographic LVH detection by adding measures of adiposity and/or novel electrocardiographic measures. Left ventricular hypertrophy (LVH) is an important risk factor for adverse cardiovascular outcomes. Improvement of electrocardiographic criteria for LVH is desirable, since electrocardiography is widely used. Methods We included 1091 participants of the Netherlands Epidemiology of Obesity Study (NEO) who underwent cardiac magnetic resonance imaging (MRI). Performance of Sokolow–Lyon and Cornell voltage and product criteria was assessed. Stepwise regression analysis was performed with each conventional electrocardiographic criterion and age, sex, body mass index (BMI), waist circumference, and waist:hip ratio (p-entry 0.10). T-wave abnormalities or the spatial QRS-T angle (SA) were added to the improved models. Results The study population had a mean (SD) age of 56 (6) years, BMI of 26.1 (4.0) kg/m2 and 46% were men. MRI-LVH was present in 10% of participants. The c-statistic for Sokolow–Lyon voltage was 0.58, R2 was 0.02 and sensitivity at 90% specificity was 16%, for Sokolow–Lyon product this was 0.62, 0.02, and 21%, for Cornell voltage 0.65, 0.04, and 28% and for Cornell product 0.67, 0.04, and 25%. Best performing models were obtained by addition of both BMI and SA (Sokolow-Lyon voltage: c-statistic 0.74, R2 0.11, sensitivity of 41% at 90% specificity; Sokolow-Lyon product: 0.75, 0.12, 42%; Cornell voltage: c-statistic 0.70, R2 0.08, sensitivity of 38% at 90% specificity; Cornell product: c-statistic 0.72, R2 0.08, sensitivity of 44% at 90% specificity). Conclusions Electrocardiographic detection of LVH improved by adding BMI and SA to a model with conventional electrocardiographic criteria. This approach would require little extra effort and application in clinical practice is feasible. However, results should first be replicated in high-risk populations. Electronic supplementary material The online version of this article (10.1007/s40119-019-00151-9) contains supplementary material, which is available to authorized users.
Published: 2019

13. Genome-Wide Association Study on the Early-Phase Insulin Response to a Liquid Mixed Meal: Results From the NEO Study

Author: Frits R. Rosendaal, Ruifang Li-Gao, Ko Willems van Dijk, Astrid van Hylckama Vlieg, Eelco J.P. de Koning, Dennis O. Mook-Kanamori, Françoise Carlotti, Renée de Mutsert, J. Wouter Jukema, and Hubrecht Institute for Developmental Biology and Stem Cell Research
Subjects: Blood Glucose, Male, 0301 basic medicine, medicine.medical_specialty, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, 030209 endocrinology & metabolism, Genome-wide association study, Type 2 diabetes, Biology, ABO Blood-Group System, 03 medical and health sciences, Endocrinology, 0302 clinical medicine, ABO blood group system, Internal medicine, Insulin Secretion, Internal Medicine, medicine, Humans, Insulin, Glucose homeostasis, Allele, Meals, Aged, Fasting, Middle Aged, Postprandial Period, medicine.disease, Diabetes and Metabolism, Minor allele frequency, 030104 developmental biology, Postprandial, Diabetes Mellitus, Type 2, Female, Genome-Wide Association Study
Abstract: Early-phase insulin secretion is a determinant of postprandial glucose homeostasis. In this study, we aimed to identify novel genetic variants associated with the early-phase insulin response to a liquid mixed meal by a genome-wide association study using a discovery and replication design embedded in the Netherlands Epidemiology of Obesity (NEO) study. The early-phase insulin response was defined as the difference between the natural logarithm–transformed insulin concentrations of the postprandial state at 30 min after a meal challenge and the fasting state (Δinsulin). After Bonferroni correction, rs505922 (β: −6.5% [minor allele frequency (MAF) 0.32, P = 3.3 × 10−8]) located in the ABO gene reached genome-wide significant level (P < 5 × 10−8) and was also replicated successfully (β: −7.8% [MAF 0.32, P = 7.2 × 10−5]). The function of the ABO gene was assessed using in vitro shRNA-mediated knockdown of gene expression in the murine pancreatic β-cell line MIN6. Knocking down the ABO gene led to decreased insulin secretion in the murine pancreatic β-cell line. These data indicate that the previously identified elevated risk of type 2 diabetes for carriers of the ABO rs505922:C allele may be caused by decreased early-phase insulin secretion.
Published: 2019

14. Hepatic triglyceride content does not affect circulating CETP: lessons from a liraglutide intervention trial and a population-based cohort

Author: Lisanne L. Blauw, Yanan Wang, Huub J. van Eyk, Renée de Mutsert, Johannes W. A. Smit, Patrick C.N. Rensen, Ingrid M. Jazet, Ko Willems van Dijk, Hildo J. Lamb, and Maurice B. Bizino
Subjects: Male, 0301 basic medicine, lcsh:Medicine, Type 2 diabetes, 0302 clinical medicine, Prospective Studies, Prospective cohort study, lcsh:Science, education.field_of_study, Multidisciplinary, biology, Double Bind Interaction, Endocrine system and metabolic diseases, Middle Aged, 3. Good health, Treatment Outcome, Liver, Female, lipids (amino acids, peptides, and proteins), medicine.drug, Adult, medicine.medical_specialty, Population, Placebo, Article, Healthcare improvement science Radboud Institute for Health Sciences [Radboudumc 18], Young Adult, 03 medical and health sciences, All institutes and research themes of the Radboud University Medical Center, Diabetes mellitus, Internal medicine, Cholesterylester transfer protein, medicine, Humans, Hypoglycemic Agents, education, Triglycerides, Aged, business.industry, Liraglutide, lcsh:R, medicine.disease, Cholesterol Ester Transfer Proteins, carbohydrates (lipids), 030104 developmental biology, Endocrinology, Diabetes Mellitus, Type 2, biology.protein, lcsh:Q, business, Pioglitazone, 030217 neurology & neurosurgery
Abstract: Cholesteryl ester transfer protein (CETP) is mainly expressed by Kupffer cells in the liver. A reduction of hepatic triglyceride content (HTGC) by pioglitazone or caloric restriction is accompanied by a decrease in circulating CETP. Since GLP-1 analogues also reduce HTGC, we assessed whether liraglutide decreases CETP. Furthermore, we investigated the association between HTGC and CETP in a population-based cohort. In a placebo-controlled trial, 50 patients with type 2 diabetes were randomly assigned to treatment with liraglutide or placebo added to standard care. In this trial and in 1,611 participants of the Netherlands Epidemiology of Obesity (NEO) study, we measured HTGC and circulating CETP by proton magnetic resonance spectroscopy and ELISA, respectively. The HTGC was decreased in the liraglutide group (−6.3%; 95%CI of difference [−9.5, −3.0]) but also in the placebo group (−4.0%; 95%CI[−6.0, −2.0]), without between-group differences. CETP was not decreased by liraglutide (−0.05 µg/mL; 95%CI[−0.13, 0.04]) or placebo (−0.04 µg/mL; 95%CI[−0.12, 0.04]). No association was present between HTGC and CETP at baseline (β: 0.002 µg/mL per %TG, 95%CI[−0.005, 0.009]) and between the changes after treatment with liraglutide (β: 0.003 µg/mL per %TG, 95%CI[−0.010, 0.017]) or placebo (β: 0.006 µg/mL per %TG, 95%CI[−0.012,0.024]). Also, in the cohort n o association between HTGC and CETP was present (β: −0.001 µg/mL per SD TG, 95%CI[−0.005, 0.003]). A reduction of HTGC after treatment with liraglutide or placebo does not decrease circulating CETP. Also, no association between HTGC and CETP was present in a large cohort. These findings indicate that circulating CETP is not determined by HTGC.Clinical Trial Registration: Clinicaltrials.gov (NCT01761318).
Published: 2019

15. Consumption of Alcoholic and Sugar-Sweetened Beverages is Associated with Increased Liver Fat Content in Middle-Aged Men and Women

Author: Albert de Roos, Joline W.J. Beulens, Frits R. Rosendaal, Anouk Geelen, Renée de Mutsert, Esther van Eekelen, Vera B. Schrauwen-Hinderling, Hildo J. Lamb, Nutrition and Movement Sciences, MUMC+: DA BV Research (9), RS: NUTRIM - R1 - Obesity, diabetes and cardiovascular health, ACS - Diabetes & metabolism, APH - Health Behaviors & Chronic Diseases, Epidemiology and Data Science, and ACS - Heart failure & arrhythmias
Subjects: Male, medicine.medical_specialty, nonalcoholic beverages, Alcohol Drinking, Nutrition and Disease, alcoholic beverages, alcohol consumption, Population, Medicine (miscellaneous), Alcohol, Wine, Gastroenterology, Cohort Studies, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Internal medicine, Voeding en Ziekte, Liver fat, substitution, medicine, Humans, 030212 general & internal medicine, education, Sugar, VLAG, 2. Zero hunger, Sugar-Sweetened Beverages, education.field_of_study, Nutrition and Dietetics, business.industry, Fatty liver, Beer, Middle Aged, liver fat, medicine.disease, 3. Good health, Fatty Liver, Triglyceride content, Cross-Sectional Studies, chemistry, Cohort, 030211 gastroenterology & hepatology, Female, business, Alcohol consumption
Abstract: Background Fatty liver is the leading cause of chronic liver diseases and increases the risk of cardiovascular disease. Besides alcohol consumption, energy-containing nonalcoholic beverages may contribute to liver fat accumulation. Objective We aimed to study the consumption of alcoholic and nonalcoholic beverages and their mutual replacement in relation to hepatic triglyceride content (HTGC) in middle-aged men and women. Methods In this cross-sectional analysis, HTGC was assessed by proton magnetic resonance spectroscopy. Habitual consumption of alcoholic and nonalcoholic beverages was assessed using a validated food-frequency questionnaire. All beverages were converted to standard servings and to percentage of total energy intake (En%). We performed linear regression to examine the association of alcoholic and nonalcoholic beverages with HTGC, adjusted for age, sex, smoking, education, ethnicity, physical activity, total energy intake, and total body fat. We studied replacement of alcoholic beverages with nonalcoholic beverages per 1 serving/d and per 5 En%/d. Results After exclusion of individuals with missing values, 1966 participants (47% men) were analyzed, with a mean ± SD age of 55 ± 6 y, BMI of 26 ± 4 kg/m2, and HTGC of 5.7% ± 7.9%. Each extra alcoholic serving per day was associated with more liver fat (1.09 times; 95% CI: 1.05, 1.12). Replacing 5 En% of alcoholic beverages with milk was associated with less liver fat (0.89 times; 95% CI: 0.81, 0.98), whereas replacement with 5 En% of sugar-sweetened beverages was associated with liver fat to an extent similar to alcoholic beverages (1.00 times; 95% CI: 0.91, 1.09). Conclusion In a population-based cohort, consumption of each extra daily alcoholic beverage was associated with more liver fat. In isocaloric replacement of alcoholic beverages, milk was associated with less liver fat, whereas sugar-sweetened beverages were equally associated with liver fat. This suggests that intake of alcohol and sugars may contribute to liver fat accumulation. This trial was registered at clinicaltrials.gov as NCT03410316.
Published: 2019

16. Genome-wide meta-analysis of macronutrient intake of 91,114 European ancestry participants from the cohorts for heart and aging research in genomic epidemiology consortium

Author: Panos Deloukas, Christina-Alexandra Schulz, Caren E. Smith, Lu Qi, Mary F. Feitosa, Melissa E. Garcia, Natalia Pervjakova, Denise K. Houston, Michael A. Province, Stavroula Kanoni, Torben Hansen, Jean Shin, Lynda M. Rose, Oscar H. Franco, Yongmei Liu, Trudy Voortman, Marie-Claude Vohl, Luigi Ferrucci, Chloé Sarnowski, Paul S. de Vries, Jose C. Florez, John C. Lieske, Louis Pérusse, Misa Graff, Jian'an Luan, Nicola M. McKeown, Felix R. Day, L. Adrienne Cupples, Qibin Qi, Frank J. A. van Rooij, Robert A. Scott, Josée Dupuis, Stephen S. Rich, Jorma Viikari, Tarunveer S. Ahluwalia, Leo-Pekka Lyytikäinen, Paul M. Ridker, Tomáš Paus, Stephen Turner, Harri Rissanen, Audrey Y. Chu, Albert Hofman, Olli T. Raitakari, Paul Knekt, Daniel I. Chasman, Nita G. Forouhi, Vera Mikkilä, Toshiko Tanaka, Mika Kähönen, George Dedoussis, Minjung Kho, Yun J. Sung, Anne E. Justice, Julius S. Ngwa, Ani Manichaikul, M. Carola Zillikens, Jordi Merino, Dena G. Hernandez, Rozenn N. Lemaitre, Tao Huang, Sharon L.R. Kardia, Jing Hua Zhao, Stefania Bandinelli, Veikko Salomaa, Arne Astrup, Wei Zhao, David S. Siscovick, John Blangero, Zdenka Pausova, Dabeeru C. Rao, Oluf Pedersen, Craig E. Pennell, Wendy H. Oddy, Jose M. Ordovas, Jessica C. Kiefte-de Jong, Marju Orho-Melander, Hassan S. Dashti, Satu Männistö, Tuomo Rankinen, Constantina Papoutsakis, Sherly X. Li, Antti Jula, Kari E. North, Thorkild I. A. Sørensen, André G. Uitterlinden, Alexis C. Frazier-Wood, Nicholas J. Wareham, Ulrika Ericson, Markus Perola, Ioanna P. Kalafati, Renée de Mutsert, Jinyan Huang, Ruifang Li-Gao, Claudia Langenberg, Mike A. Nalls, Olivia Li, Joanne E. Curran, Dennis O. Mook-Kanamori, Niina Eklund, Jerome I. Rotter, Angelo Tremblay, Claude Bouchard, Jennifer A. Smith, Terho Lehtimäki, Mary K. Wojczynski, Carol A. Wang, Epidemiology, Internal Medicine, Zhao, Jing Hua [0000-0003-4930-3582], Luan, Jian'an [0000-0003-3137-6337], Day, Felix [0000-0003-3789-7651], Langenberg, Claudia [0000-0002-5017-7344], Wareham, Nicholas [0000-0003-1422-2993], Forouhi, Nita [0000-0002-5041-248X], and Apollo - University of Cambridge Repository
Subjects: 0301 basic medicine, Male, medicine.medical_specialty, Aging, Calorie, Genotype, Heart Diseases, Receptors, Retinoic Acid, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Locus (genetics), Genome-wide association study, Biology, Polymorphism, Single Nucleotide, Article, White People, Cohort Studies, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Genetic variation, medicine, Humans, Genetic Predisposition to Disease, Obesity, Molecular Biology, Aged, 2. Zero hunger, Genetics, Family aggregation, Membrane Proteins, Genomics, Nutrients, Middle Aged, medicine.disease, 3. Good health, Fibroblast Growth Factors, Psychiatry and Mental health, 030104 developmental biology, Genetic Loci, Meta-analysis, Medical genetics, Female, Energy Intake, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P < 1 × 10(−6)) associated with intake of any macronutrient in 91,114 European ancestry participants. Four loci replicated and reached genome-wide significance in a combined meta-analysis including 123,659 European descent participants, unraveling two novel loci; a common variant in RARB locus for carbohydrate intake and a rare variant in DRAM1 locus for protein intake, and corroborating earlier FGF21 and FTO findings. In additional analysis of 144,770 participants from the UK Biobank, all identified associations from the two-stage analysis were confirmed except for DRAM1. Identified loci might have implications in brain and adipose tissue biology and have clinical impact in obesity-related phenotypes. Our findings provide new insight into biological functions related to macronutrient intake.
Published: 2019

17. Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions

Author: Alexandre C. Pereira, Jie Yao, Makoto Hirata, Ozren Polasek, Dragana Vuckovic, Mariaelisa Graff, Jing Hua Zhao, Michael R. Brown, Xuan Deng, Barbara V. Howard, Vilmundur Gudnason, Tuomo Rankinen, Yuan Shi, Timo A. Lakka, Ulrich Broeckel, Anuradhani Kasturiratne, Eric Boerwinkle, Charles Kooperberg, Hugues Aschard, Stephen S. Rich, Pamela J. Schreiner, Dan E. Arking, Hans J. Grabe, Ilaria Gandin, Mario Sims, Carl D. Langefeld, Yii-Der Ida Chen, Meian He, W. James Gauderman, Bruce M. Psaty, Kent D. Taylor, Tõnu Esko, Olli T. Raitakari, Saima Afaq, Maik Pietzner, Federica Laguzzi, Dennis O. Mook-Kanamori, Gregory P. Wilson, Xiuqing Guo, Jaspal S. Kooner, David R. Jacobs, Yajuan Wang, Raha Pazoki, Wei Zhao, Andres Metspalu, Mary F. Feitosa, Jost B. Jonas, Tin Aung, Tamara B. Harris, Karin Leander, Nancy L. Pedersen, Charles B. Eaton, Sharon L.R. Kardia, Bernardo L. Horta, Candace M. Kammerer, Terrence Forrester, Alexander P. Reiner, Paul W. Franks, Tanika N. Kelly, Igor Rudan, Ruben N. Eppinga, Melissa A. Richard, Colin A. McKenzie, Christine Williams, Christian Gieger, Joseph H. Lee, Brigitte Kühnel, Christopher P. Nelson, Wen Bin Wei, Antonietta Robino, Anne U. Jackson, E. Shyong Tai, Alisa K. Manning, Lisa R. Yanek, Paul Elliott, Lynne E. Wagenknecht, Ananda R. Wickremasinghe, José Eduardo Krieger, Peter S. Sever, Nora Franceschini, André G. Uitterlinden, Paul M. Ridker, Yun J. Sung, Karen L. Mohlke, Thomas H. Mosley, Nilesh J. Samani, Patricia B. Munroe, Jennifer A. Smith, John M. C. Connell, H. Janaka de Silva, Nicholas Y. Q. Tan, Jian'an Luan, Jennifer E. Huffman, Anna F. Dominiczak, Carsten Oliver Schmidt, Christie M. Ballantyne, Peter J. van der Most, Anuj Goel, Jerome I. Rotter, Amy R. Bentley, Lihua Wang, Rajkumar Dorajoo, Lenore J. Launer, Yechiel Friedlander, Mickaël Canouil, Traci M. Bartz, Thomas Meitinger, Robert A. Scott, Mike A. Nalls, Xueling Sim, Sarah E. Harris, Michael A. Province, Chew-Kiat Heng, Zhe Wang, Norihiro Kato, Evangelos Evangelou, Philippe Froguel, Virginia Fisher, Leslie J. Raffel, Renée de Mutsert, Michele K. Evans, Brenda W.J.H. Penninx, Yih Chung Tham, Tin Louie, Nana Matoba, Lawrence F. Bielak, Andrea R. V. R. Horimoto, Jingmin Liu, Lynda M. Rose, Nona Sotoodehnia, Daniel I. Chasman, Jasmin Divers, John M. Starr, Patricia A. Peyser, Ervin R. Fox, Barry I. Freedman, Megan L. Grove, Jeffrey R. O'Connell, Rob M. van Dam, Michiaki Kubo, Jessica D. Faul, Fang-Chi Hsu, Yize Li, Ilja M. Nolte, Caroline Hayward, Paolo Gasparini, Chiea Chuen Khor, Changwei Li, Xu Chen, James E. Hixson, Patrik K. E. Magnusson, John C. Chambers, Yoichiro Kamatani, Sami Heikkinen, M. Abdullah Said, Martin Farrall, Alena Stančáková, Konstantin Strauch, Albert V. Smith, Yik Ying Teo, Bamidele O. Tayo, Tamar Sofer, Caizheng Yu, Maris Alver, Oscar H. Franco, Yongmei Liu, Ioanna Ntalla, Myriam Fornage, W. Craig Johnson, Dina Vojinovic, William R. Scott, David R. Weir, Yanick Hagemeijer, Raymond Noordam, Mathilde Boissel, Cornelia M. van Duijn, Karen Schwander, Jingzhong Ding, James Scott, Diana van Heemst, Ching-Yu Cheng, Woon-Puay Koh, Jianjun Liu, Kenneth J. Mukamal, Blair H. Smith, Claude Bouchard, Claudia Langenberg, Jingjing Liang, Wei Zheng, Najaf Amin, Ulf de Faire, Bing Yu, Archie Campbell, Kari E. North, Salman M. Tajuddin, Fernando Pires Hartwig, Steve B. Kritchevsky, Tibor V. Varga, Pirjo Komulainen, Hugh Watkins, Johanna Kuusisto, Kurt Lohman, Rozenn N. Lemaitre, Ani Manichaikul, Dabeeru C. Rao, Kenneth Rice, Weihua Zhang, Franco Giulianini, Reedik Mägi, Solomon K. Musani, Wanqing Wen, Nicholas J. Wareham, Charles N. Rotimi, Marzyeh Amini, Rainer Rauramaa, Nicholette D. Palmer, Annette Peters, Neil R Poulter, Benjamin Lehne, Matthias Nauck, Harold Snieder, Donald W. Bowden, M. Arfan Ikram, Lisa de las Fuentes, C. Charles Gu, Xiaofeng Zhu, Markku Laakso, Tuomas O. Kilpeläinen, Ching-Ti Liu, Michael Boehnke, Jin-Fang Chai, Lili Milani, L. Adrienne Cupples, Yuri Milaneschi, Kiang Liu, Stephen Sidney, Alan B. Zonderman, Thomas W. Winkler, Ian J. Deary, Fumihiko Takeuchi, Mary K. Wojczynski, Pim van der Harst, Leo-Pekka Lyytikäinen, Jennifer G. Robinson, Chuan Gao, Xiao-Ou Shu, Diane M. Becker, Mohsen Ghanbari, Alanna C. Morrison, Jian-Min Yuan, Tomohiro Katsuya, Ivana Kolcic, Melanie Waldenberger, Terho Lehtimäki, Heikki A. Koistinen, Erin B. Ware, Ya Xing Wang, Marie Loh, Treva Rice, Qing Duan, Aldi T. Kraja, Sabanayagam Charumathi, Tien Yin Wong, Paul S. de Vries, Yujie Wang, Muhammad Riaz, Home Office, Action on Hearing Loss, Imperial College Healthcare NHS Trust- BRC Funding, British Heart Foundation, Medical Research Council (MRC), Wellcome Trust, National Institute for Health Research, Luan, Jian'an [0000-0003-3137-6337], Pietzner, Maik [0000-0003-3437-9963], Zhao, Jing Hua [0000-0003-4930-3582], Langenberg, Claudia [0000-0002-5017-7344], Wareham, Nicholas [0000-0003-1422-2993], Apollo - University of Cambridge Repository, APH - Mental Health, Psychiatry, APH - Digital Health, The University of Texas Health Science Center at Houston (UTHealth), National Institutes of Health [Bethesda] (NIH), Washington University in Saint Louis (WUSTL), University of Regensburg, Queen Mary University of London (QMUL), Washington University School of Medicine in St. Louis, Harbor UCLA Medical Center [Torrance, Ca.], University of North Carolina at Chapel Hill (UNC), Singapore National Eye Centre and Duke-NUS [Singapore], Singapore Eye Research Institute [Singapore] (SERI), National University of Singapore (NUS), Erasmus University Medical Center [Rotterdam] (Erasmus MC), Département de Biologie Computationnelle - Department of Computational Biology, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), University Management, Department of Medicine, University of Helsinki, Endokrinologian yksikkö, HUS Abdominal Center, Lifelines Cohort, Groningen, The Netherlands (Lifelines Cohort Study), Epidemiology, Neurology, Radiology & Nuclear Medicine, Internal Medicine, Life Course Epidemiology (LCE), Cardiovascular Centre (CVC), de Vries, Paul S, Brown, Michael R, Bentley, Amy R, Sung, Yun J, Winkler, Thomas W, Ntalla, Ioanna, Schwander, Karen, Kraja, Aldi T, Guo, Xiuqing, Franceschini, Nora, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Huffman, Jennifer E, Musani, Solomon K, Li, Changwei, Feitosa, Mary F, Richard, Melissa A, Noordam, Raymond, Aschard, Hugue, Bartz, Traci M, Bielak, Lawrence F, Deng, Xuan, Dorajoo, Rajkumar, Lohman, Kurt K, Manning, Alisa K, Rankinen, Tuomo, Smith, Albert V, Tajuddin, Salman M, Evangelou, Evangelo, Graff, Mariaelisa, Alver, Mari, Boissel, Mathilde, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Gandin, Ilaria, Gao, Chuan, Goel, Anuj, Hagemeijer, Yanick, Harris, Sarah E, Hartwig, Fernando P, He, Meian, Horimoto, Andrea R V R, Hsu, Fang-Chi, Jackson, Anne U, Kasturiratne, Anuradhani, Komulainen, Pirjo, Kühnel, Brigitte, Laguzzi, Federica, Lee, Joseph H, Luan, Jian'An, Lyytikäinen, Leo-Pekka, Matoba, Nana, Nolte, Ilja M, Pietzner, Maik, Riaz, Muhammad, Said, M Abdullah, Scott, Robert A, Sofer, Tamar, Stancáková, Alena, Takeuchi, Fumihiko, Tayo, Bamidele O, van der Most, Peter J, Varga, Tibor V, Wang, Yajuan, Ware, Erin B, Wen, Wanqing, Yanek, Lisa R, Zhang, Weihua, Zhao, Jing Hua, Afaq, Saima, Amin, Najaf, Amini, Marzyeh, Arking, Dan E, Aung, Tin, Ballantyne, Christie, Boerwinkle, Eric, Broeckel, Ulrich, Campbell, Archie, Canouil, Mickaël, Charumathi, Sabanayagam, Chen, Yii-Der Ida, Connell, John M, de Faire, Ulf, de Las Fuentes, Lisa, de Mutsert, Renée, de Silva, H Janaka, Ding, Jingzhong, Dominiczak, Anna F, Duan, Qing, Eaton, Charles B, Eppinga, Ruben N, Faul, Jessica D, Fisher, Virginia, Forrester, Terrence, Franco, Oscar H, Friedlander, Yechiel, Ghanbari, Mohsen, Giulianini, Franco, Grabe, Hans J, Grove, Megan L, Gu, C Charle, Harris, Tamara B, Heikkinen, Sami, Heng, Chew-Kiat, Hirata, Makoto, Hixson, James E, Howard, Barbara V, Ikram, M Arfan, Jacobs, David R, Johnson, Craig, Jonas, Jost Bruno, Kammerer, Candace M, Katsuya, Tomohiro, Khor, Chiea Chuen, Kilpeläinen, Tuomas O, Koh, Woon-Puay, Koistinen, Heikki A, Kolcic, Ivana, Kooperberg, Charle, Krieger, Jose E, Kritchevsky, Steve B, Kubo, Michiaki, Kuusisto, Johanna, Lakka, Timo A, Langefeld, Carl D, Langenberg, Claudia, Launer, Lenore J, Lehne, Benjamin, Lemaitre, Rozenn N, Li, Yize, Liang, Jingjing, Liu, Jianjun, Liu, Kiang, Loh, Marie, Louie, Tin, Mägi, Reedik, Manichaikul, Ani W, Mckenzie, Colin A, Meitinger, Thoma, Metspalu, Andre, Milaneschi, Yuri, Milani, Lili, Mohlke, Karen L, Mosley, Thomas H, Mukamal, Kenneth J, Nalls, Mike A, Nauck, Matthia, Nelson, Christopher P, Sotoodehnia, Nona, O'Connell, Jeff R, Palmer, Nicholette D, Pazoki, Raha, Pedersen, Nancy L, Peters, Annette, Peyser, Patricia A, Polasek, Ozren, Poulter, Neil, Raffel, Leslie J, Raitakari, Olli T, Reiner, Alex P, Rice, Treva K, Rich, Stephen S, Robino, Antonietta, Robinson, Jennifer G, Rose, Lynda M, Rudan, Igor, Schmidt, Carsten O, Schreiner, Pamela J, Scott, William R, Sever, Peter, Shi, Yuan, Sidney, Stephen, Sims, Mario, Smith, Blair H, Smith, Jennifer A, Snieder, Harold, Starr, John M, Strauch, Konstantin, Tan, Nichola, Taylor, Kent D, Teo, Yik Ying, Tham, Yih Chung, Uitterlinden, André G, van Heemst, Diana, Vuckovic, Dragana, Waldenberger, Melanie, Wang, Lihua, Wang, Yujie, Wang, Zhe, Wei, Wen Bin, Williams, Christine, Wilson, Gregory, Wojczynski, Mary K, Yao, Jie, Yu, Bing, Yu, Caizheng, Yuan, Jian-Min, Zhao, Wei, Zonderman, Alan B, Becker, Diane M, Boehnke, Michael, Bowden, Donald W, Chambers, John C, Deary, Ian J, Esko, Tõnu, Farrall, Martin, Franks, Paul W, Freedman, Barry I, Froguel, Philippe, Gasparini, Paolo, Gieger, Christian, Horta, Bernardo L, Kamatani, Yoichiro, Kato, Norihiro, Kooner, Jaspal S, Laakso, Markku, Leander, Karin, Lehtimäki, Terho, Magnusson, Patrik K E, Penninx, Brenda, Pereira, Alexandre C, Rauramaa, Rainer, Samani, Nilesh J, Scott, Jame, Shu, Xiao-Ou, van der Harst, Pim, Wagenknecht, Lynne E, Wang, Ya Xing, Wareham, Nicholas J, Watkins, Hugh, Weir, David R, Wickremasinghe, Ananda R, Zheng, Wei, Elliott, Paul, North, Kari E, Bouchard, Claude, Evans, Michele K, Gudnason, Vilmundur, Liu, Ching-Ti, Liu, Yongmei, Psaty, Bruce M, Ridker, Paul M, van Dam, Rob M, Kardia, Sharon L R, Zhu, Xiaofeng, Rotimi, Charles N, Mook-Kanamori, Dennis O, Fornage, Myriam, Kelly, Tanika N, Fox, Ervin R, Hayward, Caroline, van Duijn, Cornelia M, Tai, E Shyong, Wong, Tien Yin, Liu, Jingmin, Rotter, Jerome I, Gauderman, W Jame, Province, Michael A, Munroe, Patricia B, Rice, Kenneth, Chasman, Daniel I, Cupples, L Adrienne, Rao, Dabeeru C, Morrison, Alanna C, and Academic Medical Center
Subjects: Male, Epidemiology, Genome-wide association study, Cardiovascular, MESH: Genotype, Substance Misuse, Alcohol Use and Health, 0302 clinical medicine, Aetiology, triglycerides, 11 Medical and Health Sciences, Public, Environmental & Occupational Health, [STAT.AP]Statistics [stat]/Applications [stat.AP], MESH: Middle Aged, MESH: Life Style, genome wide, gene-alcohol interaction, lipid levels, Lipid Measurement, Lifelines Cohort, DENSITY-LIPOPROTEIN CHOLESTEROL, MESH: Young Adult, 030220 oncology & carcinogenesis, Kexin, LOW-FREQUENCY, MESH: Cholesterol, HDL, MESH: Cholesterol, LDL, MESH: Triglycerides, HDL, Alcohol Drinking, Genotype, alcohol consumption, MESH: Phenotype, LDL, lipids, 03 medical and health sciences, Genetics, Humans, Life Style, METAANALYSIS, 01 Mathematical Sciences, Aged, MESH: Adolescent, HDL CHOLESTEROL, MESH: Humans, Science & Technology, Cholesterol, APOBEC1, Lifelines Cohort, Groningen, The Netherlands (Lifelines Cohort Study), MESH: Vascular Endothelial Growth Factor B, Racial Groups, cholesterol, The Netherlands, MESH: Adult, CONSUMPTION, chemistry, MESH: Genome-Wide Association Study, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Lipid profile, MESH: Female, MESH: Alcohol Drinking, MESH: Continental Population Groups, Vascular Endothelial Growth Factor B, Original Contributions, Blood lipids, VEGF-B, Medical and Health Sciences, Mathematical Sciences, BLOOD-LIPIDS, chemistry.chemical_compound, 2.1 Biological and endogenous factors, 030212 general & internal medicine, MESH: Aged, medicine.diagnostic_test, PLASMA, gene-environment interactions, Middle Aged, 3142 Public health care science, environmental and occupational health, Alcoholism, Phenotype, Female, gene-lifestyle interactions, genome-wide association studies, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Life Sciences & Biomedicine, Groningen, Adult, Adolescent, Biology, Young Adult, medicine, CORONARY-HEART-DISEASE, Human Genome, Cholesterol, HDL, Lipid metabolism, Cholesterol, LDL, InterAct Consortium, MESH: Lipids, MESH: Male, INDIVIDUALS, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Genome-Wide Association Study
Abstract: © The Author(s) 2019. A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-Alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2- degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10?6) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 × 10?8 using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models. National Heart, Lung, and Blood Institute; American Heart Association Grant
Published: 2019

18. Genome-wide association study of breakfast skipping links clock regulation with food timing

Author: Jacqueline M. Lane, Marta Garaulet, Sirimon Reutrakul, Hoirun Nisa, Kristen L. Knutson, Lydia A. Bazzano, Yanwei Song, Lu Qi, Ruifang Li-Gao, Toshiko Tanaka, Marian L. Neuhouser, Bruce M. Psaty, Martin K. Rutter, Frank A.J.L. Scheer, Tahani Alshehri, Renée de Mutsert, Nicola M. McKeown, Rozenn N. Lemaitre, Richa Saxena, Vesna Boraska Perica, Dennis O. Mook-Kanamori, Dianjianyi Sun, Hassan S. Dashti, Jordi Merino, Traci M. Bartz, Chandler Tucker, Caren E. Smith, and Medical and Clinical Psychology
Subjects: 0301 basic medicine, Time Factors, Genotype, Medicine (miscellaneous), 030209 endocrinology & metabolism, Genome-wide association study, Biology, GENOTYPE IMPUTATION, food timing, breakfast, GWAS, chronobiology, circadian clock, 03 medical and health sciences, 0302 clinical medicine, food, Biological Clocks, DIETARY-INTAKE, GENETIC-VARIANTS, Mendelian randomization, Genetic variation, UK BIOBANK, Humans, EATING PATTERNS, OXFORD WEBQ, 2. Zero hunger, Genetics, Meal, Nutrition and Dietetics, CARDIOMETABOLIC RISK-FACTORS, digestive, oral, and skin physiology, Genetic Variation, food and beverages, Breakfast cereal, Feeding Behavior, Heritability, food.food, United Kingdom, 3. Good health, Original Research Communications, 030104 developmental biology, Gene Expression Regulation, Meta-analysis, MENDELIAN RANDOMIZATION, HEALTH, TYPE-2 DIABETES RISK, Body mass index, Genome-Wide Association Study
Abstract: BackgroundLittle is known about the contribution of genetic variation to food timing, and breakfast has been determined to exhibit the most heritable meal timing. As breakfast timing and skipping are not routinely measured in large cohort studies, alternative approaches include analyses of correlated traits.ObjectivesThe aim of this study was to elucidate breakfast skipping genetic variants through a proxy-phenotype genome-wide association study (GWAS) for breakfast cereal skipping, a commonly assessed correlated trait.MethodsWe leveraged the statistical power of the UK Biobank (n = 193,860) to identify genetic variants related to breakfast cereal skipping as a proxy-phenotype for breakfast skipping and applied several in silico approaches to investigate mechanistic functions and links to traits/diseases. Next, we attempted validation of our approach in smaller breakfast skipping GWAS from the TwinUK (n = 2,006) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium (n = 11,963).ResultsIn the UK Biobank, we identified 6 independent GWAS variants, including those implicated for caffeine (ARID3B/CYP1A1), carbohydrate metabolism (FGF21), schizophrenia (ZNF804A), and encoding enzymes important for N6-methyladenosine RNA transmethylation (METTL4, YWHAB, and YTHDF3), which regulates the pace of the circadian clock. Expression of identified genes was enriched in the cerebellum. Genome-wide correlation analyses indicated positive correlations with anthropometric traits. Through Mendelian randomization (MR), we observed causal links between genetically determined breakfast skipping and higher body mass index, more depressive symptoms, and smoking. In bidirectional MR, we demonstrated a causal link between being an evening person and skipping breakfast, but not vice versa. We observed association of our signals in an independent breakfast skipping GWAS in another British cohort (P = 0.032), TwinUK, but not in a meta-analysis of non-British cohorts from the CHARGE consortium (P = 0.095).ConclusionsOur proxy-phenotype GWAS identified 6 genetic variants for breakfast skipping, linking clock regulation with food timing and suggesting a possible beneficial role of regular breakfast intake as part of a healthy lifestyle.
Published: 2019

19. Normal and reference values for cardiovascular magnetic resonance-based pulse wave velocity in the middle-aged general population

Author: Martin J. Schalij, Hildo J. Lamb, J. Wouter Jukema, Max J P van Hout, Ralph L. Widya, Frits R. Rosendaal, Ilona A. Dekkers, Renée de Mutsert, Albert de Roos, Arthur J.H.A. Scholte, and Jos J.M. Westenberg
Subjects: Male, Epidemiology, Pulse Wave Velocity, 030204 cardiovascular system & hematology, 030218 nuclear medicine & medical imaging, 0302 clinical medicine, Reference Values, Pulse wave velocity, Aorta, Netherlands, education.field_of_study, Radiological and Ultrasound Technology, Age Factors, Middle Aged, Cardiovascular disease, Magnetic Resonance Imaging, Arterial stiffness, Cardiovascular Diseases, Cardiology, cardiovascular system, Aortic stiffness, Female, Cardiology and Cardiovascular Medicine, circulatory and respiratory physiology, medicine.medical_specialty, Population, Pulse Wave Analysis, 03 medical and health sciences, Sex Factors, Vascular Stiffness, Predictive Value of Tests, Internal medicine, Diabetes mellitus, medicine, Diseases of the circulatory (Cardiovascular) system, Humans, Radiology, Nuclear Medicine and imaging, Arterial Pressure, cardiovascular diseases, education, Angiology, business.industry, Research, medicine.disease, Blood pressure, Cross-Sectional Studies, RC666-701, business, Magnetic Resonance Angiography
Abstract: Background Aortic stiffness, assessed through pulse wave velocity (PWV), is an independent predictor for cardiovascular disease risk. However, the scarce availability of normal and reference values for cardiovascular magnetic resonance imaging (CMR) based PWV is limiting clinical implementation. The aim of this study was to determine normal and reference values for CMR assessed PWV in the general population. Methods From the 2,484 participants of the Netherlands Epidemiology of Obesity (NEO) study that have available CMR-PWV data, 1,394 participants free from cardiovasculard disease, smokers or treatment for diabetes, hypertension or dyslipidaemia were selected (45–65 years, 51% female). Participants were divided into sex, age and blood pressure (BP) subgroups. Normal values were specified for participants with a BP Results Normal mean PWV was 6.0 m/s [95% CI 5.8–6.1]. PWV increased with advancing age and BP categories (both p 140/90 mmHg women had a higher PWV (p = 0.005). The interpercentile ranges were smaller for participants Conclusion This study provides normal and reference values for CMR-assessed PWV per sex, age and blood pressure category in the general population.
Published: 2021

20. Genetic studies of leptin concentrations implicate leptin in the regulation of early adiposity

Author: Daniel I. Chasman, Torben Hansen, Rebecca S. Fine, Kari E. North, Harald Grallert, Jeffrey Haesser, Jie Yao, Arund D. Pradhan, Peter Kovacs, Mariaelisa Graff, Rebecca D. Jackson, Zoltán Kutalik, James G. Wilson, Neil Robertson, Mika Kähönen, Linda S. Adair, Jennifer Kriebel, Ruth J. F. Loos, Massimo Mangino, Jayne F. Martin Carli, Yiying Zhang, M. Arfan Ikram, Paraskevi Christofidou, Linda Broer, Paul M. Ridker, Barbara McKnight, Satu Männistö, Sophia Metz, Tea Skaaby, Jette Bork-Jensen, Craig E. Pennell, Sophie Molnos, Michael A. Province, Xiuqing Guo, Laura B. L. Wittemans, Stephen J. Lye, Cornelia M. van Duijn, Samuli Ripatti, Ko Willems van Dijk, Tim Kacprowski, America A. Sandoval-Zárate, Hermina Jakupović, Tuomas O. Kilpeläinen, Michael Preuss, Jaeyoung Hong, Cristina Venturini, Ying Wu, Germán D. Carrasquilla, Ivana Prokic, Mary F. Feitosa, Melissa E. Garcia, Paul L. Auer, Leslie A. Lange, Leo-Pekka Lyytikäinen, Kristin L. Young, Tugce Karaderi, Alexander P. Reiner, Tim D. Spector, Anubha Mahajan, Claudia Schurmann, Jerome I. Rotter, Rudolph L. Leibel, Georg Homuth, Claudia A. Doege, Hakon Hakonarson, Nicholas J. Wareham, Najaf Amin, Shuai Wang, Matthias Blüher, Ayse Demirkan, Andrew P. Morris, Charles A. LeDuc, Claudia Langenberg, Hanieh Yaghootkar, Mike A. Nalls, Erik Ingelsson, Dennis O. Mook-Kanamori, Jorge R. Kizer, Carolina Medina-Gomez, Timothy M. Frayling, Colleen M. Sitlani, David A. Mackey, Bruce M. Psaty, Matthias Nauck, Struan F.A. Grant, Konstantin Strauch, Olli T. Raitakari, Alexander Teumer, Mark Walker, Jonathan P. Bradfield, Judith B. Borja, Karen L. Mohlke, Lars Lind, André G. Uitterlinden, Renée de Mutsert, Ruifang Li-Gao, Cassandra N. Spracklen, Jin Li, Anne E. Justice, Cecilia M. Lindgren, Kaiying Guo, Terho Lehtimäki, Pekka Jousilahti, Yingchang Lu, Yii-Der Ida Chen, Sara M. Willems, Tamara B. Harris, Matthew A. Allison, Carol A. Wang, Niels Grarup, Lam Opal Huang, Veikko Salomaa, Jian'an Luan, Robert A. Scott, Kent D. Taylor, James B. Meigs, Ophthalmology, Epidemiology, Internal Medicine, Clinical Genetics, Department of Organisation and Personnel Management, Health Services Management & Organisation (HSMO), Yaghootkar, Hanieh [0000-0001-9672-9477], Kilpeläinen, Tuomas O [0000-0002-8349-3028], and Apollo - University of Cambridge Repository
Subjects: 0301 basic medicine, Leptin, Models, Molecular, medicine.medical_specialty, Genotype, Protein Conformation, Endocrinology, Diabetes and Metabolism, 030209 endocrinology & metabolism, Genome-wide association study, KLF14, Biology, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Internal Medicine, medicine, Missense mutation, Humans, Allele, Exome, Adiposity, 2. Zero hunger, Racial Groups, digestive, oral, and skin physiology, Gene Expression Regulation, Developmental, Genetic Variation, Genetics/Genomes/Proteomics/Metabolomics, medicine.disease, Obesity, 030104 developmental biology, Endocrinology, hormones, hormone substitutes, and hormone antagonists
Abstract: Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only and its association with lower leptin concentrations was specific to this ancestry (P=2x10-16, n=3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting leptin regulates early adiposity.
Published: 2020

21. Effects of dietary macronutrients on liver fat content in adults: a systematic review and meta-analysis of randomized controlled trials

Author: Vera B. Schrauwen-Hinderling, Babette G. de Roos, Harry P. F. Peters, Esther Winters-van Eekelen, Marjan Alssema, Peter L. Zock, Kay H. M. Roumans, Jan W. Schoones, Frits R. Rosendaal, Inge Verkouter, Patrick Schrauwen, Olaf M. Dekkers, and Renée de Mutsert
Subjects: Saturated fat, PROTEIN, Medicine (miscellaneous), Cochrane Library, DISEASE, law.invention, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Insulin resistance, Randomized controlled trial, law, FRUCTOSE, medicine, STEATOSIS, 030212 general & internal medicine, Food science, METABOLIC SYNDROME, ACCUMULATION, 030304 developmental biology, 2. Zero hunger, INSULIN-RESISTANCE, 0303 health sciences, Nutrition and Dietetics, medicine.diagnostic_test, business.industry, Unsaturated fat, WOMEN, CONSUMPTION, medicine.disease, 3. Good health, HEPATIC FAT, chemistry, Liver biopsy, Steatosis, Metabolic syndrome, business
Abstract: Dietary macronutrient composition may affect hepatic liver content and its associated diseases, but the results from human intervention trials have been equivocal or underpowered. We aimed to assess the effects of dietary macronutrient composition on liver fat content by conducting a systematic review and meta-analysis of randomized controlled trials in adults. Four databases (PubMed, Embase, Web of Science, and COCHRANE Library) were systematically searched for trials with isocaloric diets evaluating the effect of dietary macronutrient composition (energy percentages of fat, carbohydrates, and protein, and their specific types) on liver fat content as assessed by magnetic resonance techniques, computed tomography or liver biopsy. Data on change in liver fat content were pooled by random or fixed-effects meta-analyses and expressed as standardized mean difference (SMD). We included 26 randomized controlled trials providing data for 32 comparisons on dietary macronutrient composition. Replacing dietary fat with carbohydrates did not result in changes in liver fat (12 comparisons, SMD 0.01 (95% CI -0.36; 0.37)). Unsaturated fat as compared with saturated fat reduced liver fat content (4 comparisons, SMD -0.80 (95% CI -1.09; -0.51)). Replacing carbohydrates with protein reduced liver fat content (5 comparisons, SMD -0.33 (95% CI -0.54; -0.12)). Our meta-analyses showed that replacing carbohydrates with total fat on liver fat content was not effective, while replacing carbohydrates with proteins and saturated fat with unsaturated fat was. More well-performed and well-described studies on the effect of types of carbohydrates and proteins on liver fat content are needed, especially studies comparing proteins with fats.
Published: 2020

22. Adiposity is a confounding factor which largely explains the association of serum vitamin D concentrations with C-reactive protein, leptin and adiponectin

Author: Rachida Rafiq, Christa M. Cobbaert, Pieter S. Hiemstra, Hassana El Haddaoui, Frits R. Rosendaal, Renée de Mutsert, Martin den Heijer, Renate T. de Jongh, Internal medicine, Amsterdam Movement Sciences, APH - Aging & Later Life, Amsterdam Movement Sciences - Restoration and Development, Amsterdam Movement Sciences - Rehabilitation & Development, AGEM - Endocrinology, metabolism and nutrition, ACS - Diabetes & metabolism, and AMS - Ageing & Vitality
Subjects: 0301 basic medicine, Male, Leptin, medicine.medical_specialty, Waist, Immunology, Population, Biochemistry, C-reactive protein, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Internal medicine, medicine, Vitamin D and neurology, Immunology and Allergy, Humans, Vitamin D, education, Molecular Biology, Aged, Adiposity, Inflammation, education.field_of_study, Creatinine, biology, Adiponectin, business.industry, Confounding, Hematology, Middle Aged, 030104 developmental biology, Endocrinology, Cross-Sectional Studies, chemistry, 030220 oncology & carcinogenesis, biology.protein, Female, business
Abstract: Objective: The role of adiposity in the relationship between vitamin D and inflammation is unknown. Our aim was therefore to assess the association of serum 25-hydroxyvitamin D (25(OH)D) with C-reactive protein (CRP), leptin and adiponectin and the role of adiposity in this relationship. Methods: This is a cross-sectional analysis of The Netherlands Epidemiology of Obesity Study (NEO), a population-based cohort study in men and women aged 45 to 65 years. Main outcome measures were CRP, leptin and adiponectin. In the linear regression analyses we adjusted for age, sex, ethnicity, creatinine, education, alcohol use, smoking status, physical activity, number of chronic diseases, season, total body fat and waist circumference. Results: Of the 6287 participants, 21% were vitamin D deficient (serum 25(OH)D < 50 nmol/L). Mean (SD) age and BMI were 56 (6) years and 26.3 (4.4) kg/m2, respectively. Although after adjustment for most examined potential confounders, each 10 nmol/L increase in serum 25(OH)D was associated with 2.3% (95%CI: −4.0 to −0.5) lower CRP, 3.5% (−4.7 to −2.2) lower leptin, and 0.13 ng/mL (0.04–0.21) higher adiponectin, most of these associations seemed to largely stem from an additional potential confounder – adiposity – as they either disappeared (leptin and CRP) or were largely diminished (adiponectin) upon further adjustment for adiposity indices (total body fat and waist circumference). Conclusion: We found that measures of adiposity largely explained the negative association of serum 25(OH)D with the pro-inflammatory CRP and leptin, and the positive association with the anti-inflammatory adiponectin. These results suggest that future studies should take the effect of adiposity into account.
Published: 2020

23. Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose

Author: Yingchang Lu, Denis Rybin, Paul M. Ridker, Tamara B. Harris, Ruth J. F. Loos, Tuomo Rankinen, Patricia A. Peyser, Nora Franceschini, Adolfo Correa, Caroline Hayward, Jerome I. Rotter, Ayse Demirkan, Mohsen Ghanbari, Alison D. Murray, Jonathan Marten, Peitao Wu, Mike A. Nalls, Lawrence F. Bielak, Cornelia M. van Duijn, Salman M. Tajuddin, Yize Li, Michael M. Province, Jingmin Liu, Lynda M. Rose, André G. Uitterlinden, D. C. Rao, Solomon K. Musani, Vilmundur Gudnason, Albert V. Smith, Sharon L.R. Kardia, Raymond Noordam, Susan Redline, Erwin P. Bottinger, Daniel I. Chasman, Lenore J. Launer, Alan B. Zonderman, Renée de Mutsert, Mary F. Feitosa, Ching-Ti Liu, James G. Wilson, Dina Vojinovic, Charles Kooperberg, Josée Dupuis, Najaf Amin, Claude Bouchard, Jose C. Florez, Linda Kao, Dennis O. Mook-Kanamori, Karen Schwander, Blair H. Smith, Michele K. Evans, David S. Siscovick, Jason L. Vassy, James B. Meigs, Sridharan Raghavan, Donna K. Arnett, Trudy Voortman, Jun Liu, Epidemiology, Internal Medicine, Li, Yize [0000-0003-1074-281X], Marten, Jonathan [0000-0001-6916-2014], Raghavan, Sridharan [0000-0003-0643-4873], Ghanbari, Mohsen [0000-0002-9476-7143], Liu, Jun [0000-0001-5288-3042], Voortman, Trudy [0000-0003-2830-6813], Bouchard, Claude [0000-0002-0048-491X], Dupuis, Josée [0000-0003-2871-3603], Vassy, Jason L [0000-0001-6113-5564], Apollo - University of Cambridge Repository, Meyre, David, Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, and University of Iceland
Subjects: Male, Oncology, Aging, Epidemiology, Social Sciences, Genome-wide association study, Endocrinology, 0302 clinical medicine, Sociology, Smoking Habits, Psychology, Aetiology, Incidence, Statistics, Genomics, Fasting, Type 2 Diabetes, 3. Good health, Physical Sciences, Medicine, Type 2, medicine.medical_specialty, Genotype, Endocrine Disorders, Science, Single-nucleotide polymorphism, White People, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Clinical Research, Diabetes Mellitus, Genetics, Genome-Wide Association Studies, Humans, SNP, Smoking habits, Polymorphism, Statistical Methods, Trait Locus Analysis, Aged, Behavior, Tobacco Smoke and Health, Prevention, Biology and Life Sciences, Computational Biology, medicine.disease, Glucose, 030104 developmental biology, Diabetes Mellitus, Type 2, Genetic Loci, Feasibility Studies, TCF7L2, Mathematics, Blood Glucose, 0301 basic medicine, Candidate gene, Type 2 diabetes, Cohort Studies, Habits, Mathematical and Statistical Techniques, Consortia, Polymorphism (computer science), Medicine and Health Sciences, 2.1 Biological and endogenous factors, Multidisciplinary, Diabetes, Epidemiology of Aging, Single Nucleotide, Metaanalysis, Middle Aged, Female, Reykingar, Research Article, Adult, Risk, General Science & Technology, Black People, 030209 endocrinology & metabolism, Research and Analysis Methods, Polymorphism, Single Nucleotide, Cigarette Smoking, Sykursýki, Internal medicine, Tobacco, medicine, Erfðafræði, Nutrition, business.industry, Human Genome, Human Genetics, Genome Analysis, Good Health and Well Being, Metabolic Disorders, business, Genome-Wide Association Study
Abstract: Publisher's version (útgefin grein), Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p, WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C. The grant funding of WHI are R21 HL123677, R56 DK104806 and R01 MD012765 to NF. The FamHS was funded by R01HL118305 and R01HL117078 NHLBI grants, and 5R01DK07568102 and 5R01DK089256 NIDDK grant." and "The Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study was supported by the Intramural Research Program of the National Institute on Aging, National Institutes of Health (project # Z01-AG000513 and human subjects protocol number 09-AGN248). Support for GENOA was provided by the National Heart, Lung and Blood Institute (HL119443, HL087660, HL054464, HL054457, and HL054481) of the National Institutes of Health. Ruth loos is supported by the NIH (R01DK110113, U01HG007417, R01DK101855, R01DK107786). The Rotterdam Study GWAS datasets are supported by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012), the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), and the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) Netherlands Consortium for Healthy Aging (NCHA), project nr. 050-060-810. The ERF study as a part of EUROSPAN (European Special Populations Research Network) was supported by European Commission FP6 STRP grant number 018947 (LSHG-CT-2006- 01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007-2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme "Quality of Life and Management of the Living Resources" of 5th Framework Programme (no. QLG2-CT-2002- 01254). The ERF study was further supported by ENGAGE consortium and CMSB. Highthroughput analysis of the ERF data was supported by joint grant from Netherlands Organisation for Scientific Research and the Russian Foundation for Basic Research (NWORFBR 047.017.043).ERF was further supported by the ZonMw grant (project 91111025), and this work was partially supported by the National Heart, Lung and Blood Institute’s Framingham Heart Study (Contract No. N01-HC25195) and its contract with Affymetrix, Inc for genotyping services (Contract No. N02-HL-6- 4278). This study is also supported by National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) R01 DK078616 to Drs. Meigs, Dupuis and Florez, NIDDK K24 DK080140 to Dr. Meigs, and a Doris Duke Charitable Foundation Clinical Scientist Development Award to Dr. Florez. The HERITAGE Family Study was supported by National Heart, Lung, and Blood Institute grant HL-45670. The Women's Genome Health Study is supported by the National Heart, Lung, and Blood Instutute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913). Additional support for endpoint collection was provided by the National Heart, Lung, and Blood Institute under ARRA funding (HL099355). HyperGEN (Hypertension Genetic Epidemiology Network): The hypertension network is funded by cooperative agreements (U10) with NHLBI: HL54471, HL54472, HL54473, HL54495, HL54496, HL54497, HL54509, HL54515, and 2 R01 HL55673- 12. The AGES study has been funded by NIH contracts N01-AG-1-2100 and 271201200022C. Caroline Hayward is supported by an MRC University Unit Programme Grant MC_UU_00007/10 (QTL in Health and Disease)”and “Generation Scotland received core funding from the Chief Scientist Office of the Scottish Government Health Directorate CZD/16/6, the Scottish Funding Council HR03006 and the Wellcome Trust through a Strategic Award (reference 104036/Z/14/Z) for Stratifying Resilience and Depression Longitudinally (STRADL). Genotyping was funded by the UK's Medical Research Council. Jose C. Florez, NIDDK K24 DK110550 The MESA project is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1-TR-001881, and DK063491. Additionally, one or more authors are affiliated with the following commercial entities: Interleukin Genetics, GlaxoSmithKline, Daiichi-Sankyo, AstraZeneca, Data Tecnica International LLC, Illumina Inc., University of California Healthcare, Janssen Pharmaceuticals, Goldfinch Bio, and Novo Nordisk. Please see the Competing Interests Statement for additional details. The funders provided support in the form of salaries for authors but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.
Published: 2020

24. The contribution of tissue-grouped BMI-associated gene sets to cardiometabolic-disease risk: a Mendelian randomization study

Author: Inge Verkouter, Roelof A.J. Smit, Stella Trompet, Ko Willems van Dijk, Raymond Noordam, Renée de Mutsert, Diana van Heemst, and Frits R. Rosendaal
Subjects: 0301 basic medicine, Epidemiology, type 2 diabetes mellitus, Genome-wide association study, Computational biology, 030204 cardiovascular system & hematology, Biology, Polymorphism, Single Nucleotide, Body Mass Index, Coronary artery disease, 03 medical and health sciences, 0302 clinical medicine, Mendelian Randomization, Risk Factors, Mendelian randomization, medicine, Humans, AcademicSubjects/MED00860, Gene, Genetic association, Adiposity, anthropometry, nutritional and metabolic diseases, Mendelian Randomization Analysis, General Medicine, medicine.disease, waist circumference, Obesity, 030104 developmental biology, Diabetes Mellitus, Type 2, Cardiovascular Diseases, Disease Susceptibility, Body mass index, coronary artery disease, Genome-Wide Association Study
Abstract: Background Body mass index (BMI)-associated loci are used to explore the effects of obesity using Mendelian randomization (MR), but the contribution of individual tissues to risks remains unknown. We aimed to identify tissue-grouped pathways of BMI-associated loci and relate these to cardiometabolic disease using MR analyses. Methods Using Genotype-Tissue Expression (GTEx) data, we performed overrepresentation tests to identify tissue-grouped gene sets based on mRNA-expression profiles from 634 previously published BMI-associated loci. We conducted two-sample MR with inverse-variance-weighted methods, to examine associations between tissue-grouped BMI-associated genetic instruments and type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD), with use of summary-level data from published genome-wide association studies (T2DM: 74 124 cases, 824 006 controls; CAD: 60 801 cases, 123 504 controls). Additionally, we performed MR analyses on T2DM and CAD using randomly sampled sets of 100 or 200 BMI-associated genetic variants. Results We identified 17 partly overlapping tissue-grouped gene sets, of which 12 were brain areas, where BMI-associated genes were differentially expressed. In tissue-grouped MR analyses, all gene sets were similarly associated with increased risks of T2DM and CAD. MR analyses with randomly sampled genetic variants on T2DM and CAD resulted in a distribution of effect estimates similar to tissue-grouped gene sets. Conclusions Overrepresentation tests revealed differential expression of BMI-associated genes in 17 different tissues. However, with our biology-based approach using tissue-grouped MR analyses, we did not identify different risks of T2DM or CAD for the BMI-associated gene sets, which was reflected by similar effect estimates obtained by randomly sampled gene sets.
Published: 2020

25. Metabolomics Profile in Depression: A Pooled Analysis of 230 Metabolic Markers in 5283 Cases With Depression and 10,145 Controls

Author: Mariska Bot, Yuri Milaneschi, Tahani Al-Shehri, Najaf Amin, Sanzhima Garmaeva, Gerrit L.J. Onderwater, Rene Pool, Carisha S. Thesing, Lisanne S. Vijfhuizen, Nicole Vogelzangs, Ilja C.W. Arts, Ayse Demirkan, Cornelia van Duijn, Marleen van Greevenbroek, Carla J.H. van der Kallen, Sebastian Köhler, Lannie Ligthart, Arn M.J.M. van den Maagdenberg, Dennis O. Mook-Kanamori, Renée de Mutsert, Henning Tiemeier, Miranda T. Schram, Coen D.A. Stehouwer, Gisela M. Terwindt, Ko Willems van Dijk, Jingyuan Fu, Alexandra Zhernakova, Marian Beekman, P. Eline Slagboom, Dorret I. Boomsma, Brenda W.J.H. Penninx, M. Beekman, H.E.D. Suchiman, J. Deelen, N. Amin, J.W. Beulens, J.A. van der Bom, N. Bomer, A. Demirkan, J.A. van Hilten, J.M.T.A. Meessen, R. Pool, M.H. Moed, J. Fu, G.L.J. Onderwater, F. Rutters, C. So-Osman, W.M. van der Flier, A.A.W.A. van der Heijden, A. van der Spek, F.W. Asselbergs, E. Boersma, P.M. Elders, J.M. Geleijnse, M.A. Ikram, M. Kloppenburg, I. Meulenbelt, S.P. Mooijaart, R.G.H.H. Nelissen, M.G. Netea, B.W.J.H. Penninx, C.D.A. Stehouwer, C.E. Teunissen, G.M. Terwindt, L.M. ’t Hart, A.M.J.M. van den Maagdenberg, P. van der Harst, I.C.C. van der Horst, C.J.H. van der Kallen, M.M.J. van Greevenbroek, W.E. van Spil, C. Wijmenga, A.H. Zwinderman, A. Zhernikova, J.W. Jukema, N. Sattar, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, APH - Mental Health, APH - Methodology, Epidemiology, Clinical Genetics, Psychiatry, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Digital Health, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Translational Immunology Groningen (TRIGR), Center for Liver, Digestive and Metabolic Diseases (CLDM), Neurosurgery, Amsterdam Neuroscience - Systems & Network Neuroscience, Amsterdam Neuroscience - Neurodegeneration, Dermatology, Obstetrics and Gynaecology, Graduate School, Cardiology, Public and occupational health, Gastroenterology and Hepatology, RS: FHML MaCSBio, RS: Carim - V01 Vascular complications of diabetes and metabolic syndrome, Epidemiologie, RS: FSE MaCSBio, RS: FPN MaCSBio, Interne Geneeskunde, Psychiatrie & Neuropsychologie, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, MUMC+: HVC Pieken Maastricht Studie (9), MUMC+: MA Interne Geneeskunde (3), MUMC+: MA Med Staf Artsass Interne Geneeskunde (9), MUMC+: MA Endocrinologie (9), MUMC+: MA Maag Darm Lever (9), MUMC+: MA Hematologie (9), MUMC+: MA Medische Oncologie (9), MUMC+: MA Nefrologie (9), and MUMC+: MA Reumatologie (9)
Subjects: 0301 basic medicine, Netherlands Twin Register (NTR), Apolipoprotein B, Nutrition and Disease, Metabolite, Cardiovascular, chemistry.chemical_compound, 0302 clinical medicine, Voeding en Ziekte, Metabolites, EPIDEMIOLOGY, Medicine, HETEROGENEITY, Depression (differential diagnoses), RISK, chemistry.chemical_classification, INSULIN-RESISTANCE, biology, Depression, CHOLESTEROL, Fatty Acids, ASSOCIATION, Apolipoprotein A1, lipids (amino acids, peptides, and proteins), medicine.medical_specialty, Pooled analysis, 03 medical and health sciences, MAGNETIC-RESONANCE METABOLOMICS, INFLAMMATION, SDG 3 - Good Health and Well-being, Internal medicine, Humans, Metabolomics, Triglycerides, METAANALYSIS, Biological Psychiatry, VLAG, Triglyceride, business.industry, Fatty acid, MAJOR DEPRESSION, 030104 developmental biology, Endocrinology, chemistry, biology.protein, business, Body mass index, 030217 neurology & neurosurgery, Biomarkers, Lipoprotein
Abstract: BACKGROUND: Depression has been associated with metabolic alterations, which adversely impact cardiometabolic health. Here, a comprehensive set of metabolic markers, predominantly lipids, was compared between depressed and nondepressed persons.METHODS: Nine Dutch cohorts were included, comprising 10,145 control subjects and 5283 persons with depression, established with diagnostic interviews or questionnaires. A proton nuclear magnetic resonance metabolomics platform provided 230 metabolite measures: 51 lipids, fatty acids, and low-molecular-weight metabolites; 98 lipid composition and particle concentration measures of lipoprotein subclasses; and 81 lipid and fatty acids ratios. For each metabolite measure, logistic regression analyses adjusted for gender, age, smoking, fasting status, and lipid-modifying medication were performed within cohort, followed by random-effects meta-analyses.RESULTS: Of the 51 lipids, fatty acids, and low-molecular-weight metabolites, 21 were significantly related to depression (false discovery rate q < .05). Higher levels of apolipoprotein B, very-low-density lipoprotein cholesterol, triglycerides, diglycerides, total and monounsaturated fatty acids, fatty acid chain length, glycoprotein acetyls, tyrosine, and isoleucine and lower levels of high-density lipoprotein cholesterol, acetate, and apolipoprotein A1 were associated with increased odds of depression. Analyses of lipid composition indicators confirmed a shift toward less high-density lipoprotein and more very-low-density lipoprotein and triglyceride particles in depression. Associations appeared generally consistent across gender, age, and body mass index strata and across cohorts with depressive diagnoses versus symptoms.CONCLUSIONS: This large-scale meta-analysis indicates a clear distinctive profile of circulating lipid metabolites associated with depression, potentially opening new prevention or treatment avenues for depression and its associated cardiometabolic comorbidity.
Published: 2020

26. Hormonal Treatment and Cardiovascular Risk Profile in Transgender Adolescents

Author: Martin den Heijer, Renée de Mutsert, Maartje Klaver, Maria A T C van der Loos, Daniel T Klink, Chantal M. Wiepjes, Jos W. R. Twisk, Joost Rotteveel, Internal medicine, Epidemiology and Data Science, ACS - Atherosclerosis & ischemic syndromes, AGEM - Endocrinology, metabolism and nutrition, Amsterdam Movement Sciences - Rehabilitation & Development, Amsterdam Movement Sciences - Restoration and Development, APH - Aging & Later Life, Amsterdam Movement Sciences, Pediatric surgery, ACS - Diabetes & metabolism, Amsterdam Reproduction & Development (AR&D), APH - Quality of Care, APH - Methodology, and APH - Health Behaviors & Chronic Diseases
Subjects: Male, Pediatric Obesity, medicine.medical_specialty, Adolescent, Risk Assessment, Cohort Studies, Gonadotropin-Releasing Hormone, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Insulin resistance, 030225 pediatrics, Internal medicine, Prevalence, Humans, Medicine, Gonadal Steroid Hormones, Dyslipidemias, Retrospective Studies, business.industry, Retrospective cohort study, medicine.disease, Obesity, Confidence interval, Blood pressure, Cardiovascular Diseases, Pediatrics, Perinatology and Child Health, Homeostatic model assessment, Female, business, Transsexualism, Dyslipidemia, Cohort study
Abstract: BACKGROUND AND OBJECTIVES: The effects of endocrinological treatment on cardiovascular risk profile in transgender adolescents are unknown. In this retrospective cohort study, we aim to investigate these effects and assess obesity and dyslipidemia prevalence in transgender adolescents at 22 years compared with peers. METHODS: Changes in BMI, systolic blood pressure (SBP), diastolic blood pressure (DBP), glucose, homeostatic model assessment for insulin resistance (HOMA-IR), and lipid values during treatment, along with the prevalence of obesity and dyslipidemia at 22 years, were recorded in 71 transwomen and 121 transmen who started gonadotropin-releasing hormone agonists in their adolescence (15 years), with a subsequent addition of sex hormones (17 years). RESULTS: In transwomen, changes in BMI (+3.0; 95% confidence interval [CI] 1.6 to 4.4), SBP (−2 mm Hg; 95% CI −7 to 3), DBP (+10 mm Hg; 95% CI 7 to 14), glucose (0.0 mmol/L; 95% CI −0.2 to 0.2), HOMA-IR (+0.6; 95% CI −0.6 to 1.9), and lipid values were similar or more favorable compared with peers. The same was true for transmen regarding changes in BMI (+2.3; 95% CI 1.7 to 2.9), SBP (+7 mm Hg; 95% CI 3 to 10), DBP (+7 mm Hg; 95% CI 5 to 10), glucose (+0.1 mmol/L; 95% CI −0.1 to 0.3), HOMA-IR (−0.2; 95% CI −0.8 to 0.3), and lipid values. At age 22, obesity prevalence was 9.9% in transwomen, 6.6% in transmen, 2.2% in ciswomen, and 3.0% in cismen. CONCLUSIONS: Generally, endocrinological treatment in transgender adolescents is safe regarding cardiovascular risk. Because obesity is more prevalent in transgender adolescents compared with peers, body weight management should be important during the medical trajectory.
Published: 2020

27. The role of insulin resistance in the relation of visceral, abdominal subcutaneous and total body fat to cardiovascular function

Author: Hildo J. Lamb, Frits R. Rosendaal, J. Wouter Jukema, Elisabeth H.M. Paiman, Renée de Mutsert, and Ralph L. Widya
Subjects: Aortic arch, Male, medicine.medical_specialty, Subcutaneous adipose tissue, Diabetic Cardiomyopathies, Endocrinology, Diabetes and Metabolism, Population, Medicine (miscellaneous), Adipose tissue, 030209 endocrinology & metabolism, Type 2 diabetes, 030204 cardiovascular system & hematology, Intra-Abdominal Fat, Risk Assessment, Ventricular Function, Left, 03 medical and health sciences, Ventricular Dysfunction, Left, 0302 clinical medicine, Insulin resistance, medicine.artery, Internal medicine, Medicine, Humans, Obesity, education, Pulse wave velocity, Adiposity, Aged, Netherlands, Left ventricular dysfunction, education.field_of_study, Nutrition and Dietetics, Ventricular Remodeling, business.industry, Confounding, nutritional and metabolic diseases, Total body, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Subcutaneous Fat, Abdominal, Cross-Sectional Studies, Visceral adipose tissue, Heart Disease Risk Factors, Cardiology, Female, Insulin Resistance, Cardiology and Cardiovascular Medicine, business
Abstract: Background and aims: The separate cardiovascular effects of type 2 diabetes and adiposity remain to be examined. This study aimed to investigate the role of insulin resistance in the relations of visceral (VAT), abdominal subcutaneous (aSAT) adipose tissue and total body fat (TBF) to cardiovascular remodeling.Methods and results: In this cross-sectional analysis of the population-based Netherlands Epidemiology of Obesity study, 914 middle-aged individuals (46% men) were included. Participants underwent magnetic resonance imaging. Standardized linear regression coefficients (95%CI) were calculated, adjusted for potential confounding factors. All fat depots and insulin resistance (HOMA-IR), separate from VAT and TBF, were associated with lower mitral early and late peak filling rate ratios (E/A): -0.04 (-0.09;0.01) per SD (54 cm(2)) VAT; -0.05 (-0.10;0.00) per SD (94 cm(2)) aSAT; -0.09 (-0.16;-0.02) per SD (8%) TBF; -0.11 (-0.17;-0.05) per 10-fold increase in HOMA-IR, whereas VAT and TBF were differently associated with left ventricular (LV) end-diastolic volume: -8.9 (-11.7;-6.1) mL per SD VAT; +5.4 (1.1;9.7) mL per SD TBF. After adding HOMA- IR to the model to evaluate the mediating role of insulin resistance, change in E/A was -0.02 (-0.07;0.04) per SD VAT; -0.03 (-0.08;0.02) per SD aSAT; -0.06 (- 0.13;0.01) per SD TBF, and change in LV end-diastolic volume was -7.0 (-9.7;-4.3) mL per SD VAT. In women, adiposity but not HOMA-IR was related to higher aortic arch pulse wave velocity.Conclusion: Insulin resistance was associated with reduced diastolic function, separately from VAT and TBF, and partly mediated the associations between adiposity depots and lower diastolic function. (C) 2020 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.
Published: 2020

28. Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood

Author: George Dedoussis, Frédéric Fumeron, Zhonghan Sun, E-Shyong Tai, Bruce M. Psaty, Paul M. Ridker, Kim Overvad, Marcus E. Kleber, Wolfgang Lieb, Marju Orho-Melander, Xueling Sim, Philippe Froguel, Mark I. McCarthy, Tiange Wang, Diana van Heemst, Emily Sonestedt, Veit Grote, Karen L. Mohlke, Inke R. König, Tibor V. Varga, Chris Power, Matthias Munz, Ulrika Ericson, Luc Djoussé, Dariush Mozaffarian, Tuomas O. Kilpeläinen, Jorma Viikari, Ralph Burkhardt, Chao-Qiang Lai, Klaus Bønnelykke, Mariaelisa Graff, Woon-Puay Koh, Jin-Fang Chai, Nanette R. Lee, Harri Niinikoski, Torben Hansen, Christina-Alexandra Schulz, Caizheng Yu, Renée de Mutsert, Colin Boreham, Jean Dallongeville, Anne Tjønneland, Philippe Amouyel, Tao Zhang, Markus Scholz, Elina Hyppönen, Tarunveer S. Ahluwalia, Niina Pitkänen, Fernando Rivadeneira, Rebecca K. Vinding, Donna K. Arnett, Craig E. Pennell, Joachim Thiery, Jose M. Ordovas, Thorkild I. A. Sørensen, Lu Qi, Oscar Coltell, Daniel I. Chasman, Olli T. Raitakari, Preeti Gupta, Dariusz Gruszfeld, Rajkumar Dorajoo, Berthold Koletzko, Seang-Mei Saw, Tangchun Wu, Charumathi Sabanayagam, Rozenn N. Lemaitre, Meian He, Tao Huang, Carol A. Wang, Graciela E. Delgado, Rob M. van Dam, Luis A. Moreno, Peter Rossing, Mika Kähönen, Aline Meirhaeghe, Christina Ellervik, Frédéric Gottrand, Yan Zheng, Katherine L. Tucker, Ying Wu, Lavinia Paternoster, Lingyao Zeng, Joaquin Escribano, David A. Mackey, Raymond Noordam, Masato Akiyama, Dolores Corella, Thorsten Kessler, Frank J. A. van Rooij, Terho Lehtimäki, Jeanette Erdmann, Ang Zhou, Michiaki Kubo, Winfried März, Frits R. Rosendaal, Kari E. North, Cécile Lecoeur, Cornelia Enzenbach, Albert Hofman, Elvira Verduci, Tien Yin Wong, Hans Bisgaard, Zhendong Mei, Trudy Voortman, Yujie Wang, Heribert Schunkert, Beverley Balkau, Annette Peters, Dennis O. Mook-Kanamori, Vincent W. V. Jaddoe, Peter Rzehak, Christina Willenborg, Katja Pahkala, Jean-Paul Langhendries, Janine F. Felix, Angela C. Estampador, Ramon Estruch, Centre de recherche en épidémiologie et santé des populations (CESP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Institute for Translational Research in Inflammation - U 1286 (INFINITE (Ex-Liric)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université de Paris (UP), Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning National Basic Research Program of China (973 Program): 2016YFC1304801 2017SHZDZX01, This work was supported by Shanghai Municipal Science and Technology Major Project (Grant No. 2017SHZDZX01) and the National Key Research and Development Program of China (Grant No. 2016YFC1304801). YZ was supported by the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning. For the funding information of each study within CHARGE-BIG consortium, please see Supplemental Table 8., CHU Lille, CNRS, Inserm, Université de Lille, Génomique Intégrative et Modélisation des Maladies Métaboliques (EGID) - UMR 8199, Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 [EGENODIA (GI3M)], Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement (RID-AGE) - U1167, Lille Inflammation Research International Center (LIRIC) - U995, Epidemiology, Erasmus MC other, Pediatrics, Internal Medicine, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité), Zheng, Yan, Huang, Tao, Wang, Tiange, Mei, Zhendong, Zhou, A, Hypponen, E, and Qi, L
Subjects: Adult, Male, medicine.medical_specialty, Epidemiology, Birth weight, [SDV]Life Sciences [q-bio], Birthweight, 030204 cardiovascular system & hematology, Polymorphism, Single Nucleotide, Article, Body Mass Index, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Mendelian randomization, medicine, Birth Weight, Humans, Hypertension, Blood pressure, Causal association, Genetic Predisposition to Disease, 030212 general & internal medicine, business.industry, Infant, Newborn, Mendelian Randomization Analysis, Odds ratio, Infant, Low Birth Weight, 3. Good health, Pulse pressure, Cohort, Female, business, Genome-Wide Association Study
Abstract: International audience; Epidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (β = − 0.76, 95% CI − 2.45 to 1.08 mmHg), 0.06 mmHg lower diastolic blood pressure (β = − 0.06, 95% CI − 0.93 to 0.87 mmHg), or pulse pressure (β = − 0.65, 95% CI − 1.38 to 0.69 mmHg, all p > 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses.
Published: 2020

29. Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction

Author: Dennis O. Mook-Kanamori, Yalda Jamshidi, Peter K. Joshi, Seung Hoan Choi, Henry J. Lin, Rebecca D. Jackson, Alison D. Murray, May E. Montasser, Veikko Salomaa, Charles Kooperberg, Moritz F. Sinner, Gianfranco Sinagra, Luisa Foco, James G. Wilson, Johan Sundström, Kathleen A. Ryan, Eric A. Whitsel, Bruno H. Stricker, Sandosh Padmanabhan, Christopher Newton-Cheh, Ozren Polasek, Unnur Thorsteinsdottir, Niek Verweij, Pier D. Lambiase, Nathan R. Tucker, Stefan Kääb, Jun Ding, Stefan Weiss, Daniel F. Gudbjartsson, David Conen, Lars Lind, Ivana Kolcic, Lu-Chen Weng, J. Wouter Jukema, Kirill V. Tarasov, Xiuqing Guo, Stella Trompet, Patricia B. Munroe, Albert V. Smith, Elsayed Z. Soliman, Andrew Tinker, Antti Jula, J. Gustav Smith, Alexander P. Reiner, Sébastien Thériault, Kathryn L. Lunetta, Vilmundur Gudnason, Mika Kähönen, Massimo Mangino, Raymond Noordam, Joshua C. Bis, Alan R. Shuldiner, Tim D. Spector, Borbala Mifsud, Stefan van Duijvenboden, Jeffrey R. O'Connell, Emelia J. Benjamin, M. Benjamin Shoemaker, Stephan B. Felix, Peter W. Macfarlane, Lorenz Risch, Uwe Völker, Stephanie M. Gogarten, Maria Fernanda Lima-Costa, Julia Ramirez, Morten S. Olesen, Konstantin Strauch, Annette Peters, Aaron Isaacs, Steven A. Lubitz, Eric Boerwinkle, Carolina Roselli, James H. Cartwright, Nathalia M. Araujo, Ruth J. F. Loos, Diane Fatkin, Harry Campbell, Blair H. Smith, Thomas Meitinger, André G. Uitterlinden, Paul L. Huang, Tamara B. Harris, Kathleen F. Kerr, David J. Porteous, Martina Müller-Nurasyid, Francesco Cucca, Michiel Rienstra, Davíð O. Arnar, Amanda A. Seyerle, Caroline Hayward, M. Abdullah Said, Catriona L. K. Barnes, Kent D. Taylor, Nona Sotoodehnia, Nina Mononen, Dan M. Roden, Jonathan Marten, Terho Lehtimäki, Dan E. Arking, Anna F. Dominiczak, Jan A. Kors, Olli T. Raitakari, Igor Rudan, Yordi J. van de Vegte, Christopher P. Nelson, Erik Ingelsson, Ulrike Peters, Girish N. Nadkarni, Eduardo Tarazona-Santos, Edward G. Lakatta, Nina Hutri-Kähönen, Bruce M. Psaty, Patrick T. Ellinor, Christian Fuchsberger, Katharina Schramm, Amelia W. Hall, M. Yldau van der Ende, Alvaro Alonso, James F. Wilson, Sheila Ulivi, Rosa B. Thorolfsdottir, Stefanie Aeschbacher, Mary L. Biggs, Marten E. van den Berg, Nilesh J. Samani, Thibaud Boutin, Vilmantas Giedraitis, Honghuang Lin, Kjell Nikus, Helen R. Warren, Arie C. Maan, James J. Cranley, Adolfo Correa, Martin Gögele, Ian Ford, Katri Sääksjärvi, Georg Ehret, Michele Orini, Susan R. Heckbert, Cecilia M. Lindgren, Jie Yao, Maria Pina Concas, Pim van der Harst, Ioanna Ntalla, Jeffrey Haessler, Jerome I. Rotter, Pashupati P. Mishra, Michael J. Cutler, Erwin P. Bottinger, Cornelia M. van Duijn, Jennifer A. Brody, Paolo Gasparini, Lenore J. Launer, Andrew P. Morris, Renée de Mutsert, Aki S. Havulinna, James P. Cook, Hilma Holm, Patrick Sulem, Alessandro De Grandi, Cristian Pattaro, Gardar Sveinbjornsson, Antonio Luiz Pinho Ribeiro, Mark J. Caulfield, Gudmar Thorleifsson, Marcus Dörr, Muhammad B. Riaz, Peter P. Pramstaller, Yong Qian, Anubha Mahajan, Cathy C. Laurie, Kenneth Rice, Mark Chaffin, Kari Stefansson, Andrew A. Hicks, Solmaz Assa, Hao Mei, Leo-Pekka Lyytikäinen, Fabiola Del Greco M, Renan P. Souza, Michael Preuss, Adrienne M. Stilp, Barry London, Melanie Waldenberger, Christy L. Avery, Daniel Levy, Michael R. Barnes, Medical Informatics, Epidemiology, Internal Medicine, Weng, Lu-Chen [0000-0003-1475-4930], Hall, Amelia Weber [0000-0002-7915-0313], Tucker, Nathan R [0000-0002-5071-4218], Chaffin, Mark D [0000-0002-1234-5562], Roselli, Carolina [0000-0001-5267-6756], Barnes, Michael R [0000-0001-9097-7381], Mifsud, Borbala [0000-0003-3429-3094], Hayward, Caroline [0000-0002-9405-9550], Concas, Maria Pina [0000-0003-3598-2537], Boutin, Thibaud [0000-0003-4754-1675], Kolcic, Ivana [0000-0001-7918-6052], Rudan, Igor [0000-0001-6993-6884], Souza, Renan P [0000-0002-9479-4432], Giedraitis, Vilmantas [0000-0003-3423-2021], Ingelsson, Erik [0000-0003-2256-6972], Mahajan, Anubha [0000-0001-5585-3420], Morris, Andrew P [0000-0002-6805-6014], Hicks, Andrew A [0000-0001-6320-0411], Sundström, Johan [0000-0003-2247-8454], Nelson, Christopher P [0000-0001-8025-2897], Riaz, Muhammad B [0000-0002-5512-1745], Sinagra, Gianfranco [0000-0003-2700-8478], Mishra, Pashupati P [0000-0001-5177-3431], Caulfield, Mark J [0000-0001-9295-3594], Dominiczak, Anna [0000-0003-4913-3608], Risch, Lorenz [0000-0003-2692-6699], Joshi, Peter K [0000-0002-6361-5059], Wilson, James F [0000-0001-5751-9178], Isaacs, Aaron [0000-0001-5037-4834], van Duijn, Cornelia M [0000-0002-2374-9204], Gudnason, Vilmundur [0000-0001-5696-0084], Smith, Albert V [0000-0003-1942-5845], Loos, Ruth JF [0000-0002-8532-5087], Preuss, Michael H [0000-0001-5266-8465], Correa, Adolfo [0000-0002-9501-600X], Müller-Nurasyid, Martina [0000-0003-3793-5910], Waldenberger, Melanie [0000-0003-0583-5093], Mangino, Massimo [0000-0002-2167-7470], Rienstra, Michiel [0000-0002-2581-070X], van der Harst, Pim [0000-0002-2713-686X], Verweij, Niek [0000-0002-4303-7685], Fatkin, Diane [0000-0002-9010-9856], Brody, Jennifer A [0000-0001-8509-148X], Rice, Kenneth [0000-0002-3071-7278], Pattaro, Cristian [0000-0002-4119-0109], Wouter Jukema, J [0000-0002-3246-8359], Weiss, Stefan [0000-0002-3553-4315], Havulinna, Aki S [0000-0002-4787-8959], Sääksjärvi, Katri [0000-0002-5061-4911], Salomaa, Veikko [0000-0001-7563-5324], Rotter, Jerome I [0000-0001-7191-1723], Taylor, Kent D [0000-0002-2756-4370], Lakatta, Edward G [0000-0002-4772-0035], Lin, Honghuang [0000-0003-3043-3942], Lunetta, Kathryn L [0000-0002-9268-810X], Murray, Alison D [0000-0003-4915-4847], Porteous, David J [0000-0003-1249-6106], Smith, Blair H [0000-0002-5362-9430], Uitterlinden, André [0000-0002-7276-3387], Peters, Ulrike [0000-0001-5666-9318], Alonso, Alvaro [0000-0002-2225-8323], Ehret, Georg B [0000-0002-5730-0675], Soliman, Elsayed Z [0000-0001-5632-8150], Gogarten, Stephanie M [0000-0002-7231-9745], Kerr, Kathleen F [0000-0002-6438-9583], Abdullah Said, M [0000-0003-2920-7745], Orini, Michele [0000-0001-5773-0344], Ramirez, Julia [0000-0003-4130-5866], Van Duijvenboden, Stefan [0000-0001-8897-558X], Gudbjartsson, Daniel F [0000-0002-5222-9857], Sulem, Patrick [0000-0001-7123-6123], Thorolfsdottir, Rosa B [0000-0001-7475-0398], Benjamin, Emelia J [0000-0003-4076-2336], Stefansson, Kari [0000-0003-1676-864X], Ellinor, Patrick T [0000-0002-2067-0533], Jamshidi, Yalda [0000-0003-0151-6482], Lubitz, Steven A [0000-0002-9599-4866], Munroe, Patricia B [0000-0002-4176-2947], Apollo - University of Cambridge Repository, Medicum, Institute for Molecular Medicine Finland, Complex Disease Genetics, Helsinki Institute of Life Science HiLIFE, University of Helsinki, Cardiovascular Centre (CVC), Ntalla, I., Weng, L. -C., Cartwright, J. H., Hall, A. W., Sveinbjornsson, G., Tucker, N. R., Choi, S. H., Chaffin, M. D., Roselli, C., Barnes, M. R., Mifsud, B., Warren, H. R., Hayward, C., Marten, J., Cranley, J. J., Concas, M. P., Gasparini, P., Boutin, T., Kolcic, I., Polasek, O., Rudan, I., Araujo, N. M., Lima-Costa, M. F., Ribeiro, A. L. P., Souza, R. P., Tarazona-Santos, E., Giedraitis, V., Ingelsson, E., Mahajan, A., Morris, A. P., Del Greco M, F., Foco, L., Gogele, M., Hicks, A. A., Cook, J. P., Lind, L., Lindgren, C. M., Sundstrom, J., Nelson, C. P., Riaz, M. B., Samani, N. J., Sinagra, G., Ulivi, S., Kahonen, M., Mishra, P. P., Mononen, N., Nikus, K., Caulfield, M. J., Dominiczak, A., Padmanabhan, S., Montasser, M. E., O'Connell, J. R., Ryan, K., Shuldiner, A. R., Aeschbacher, S., Conen, D., Risch, L., Theriault, S., Hutri-Kahonen, N., Lehtimaki, T., Lyytikainen, L. -P., Raitakari, O. T., Barnes, C. L. K., Campbell, H., Joshi, P. K., Wilson, J. F., Isaacs, A., Kors, J. A., van Duijn, C. M., Huang, P. L., Gudnason, V., Harris, T. B., Launer, L. J., Smith, A. V., Bottinger, E. P., Loos, R. J. F., Nadkarni, G. N., Preuss, M. H., Correa, A., Mei, H., Wilson, J., Meitinger, T., Muller-Nurasyid, M., Peters, A., Waldenberger, M., Mangino, M., Spector, T. D., Rienstra, M., van de Vegte, Y. J., van der Harst, P., Verweij, N., Kaab, S., Schramm, K., Sinner, M. F., Strauch, K., Cutler, M. J., Fatkin, D., London, B., Olesen, M., Roden, D. M., Benjamin Shoemaker, M., Gustav Smith, J., Biggs, M. L., Bis, J. C., Brody, J. A., Psaty, B. M., Rice, K., Sotoodehnia, N., De Grandi, A., Fuchsberger, C., Pattaro, C., Pramstaller, P. P., Ford, I., Wouter Jukema, J., Macfarlane, P. W., Trompet, S., Dorr, M., Felix, S. B., Volker, U., Weiss, S., Havulinna, A. S., Jula, A., Saaksjarvi, K., Salomaa, V., Guo, X., Heckbert, S. R., Lin, H. J., Rotter, J. I., Taylor, K. D., Yao, J., de Mutsert, R., Maan, A. C., Mook-Kanamori, D. O., Noordam, R., Cucca, F., Ding, J., Lakatta, E. G., Qian, Y., Tarasov, K. V., Levy, D., Lin, H., Newton-Cheh, C. H., Lunetta, K. L., Murray, A. D., Porteous, D. J., Smith, B. H., Stricker, B. H., Uitterlinden, A., van den Berg, M. E., Haessler, J., Jackson, R. D., Kooperberg, C., Peters, U., Reiner, A. P., Whitsel, E. A., Alonso, A., Arking, D. E., Boerwinkle, E., Ehret, G. B., Soliman, E. Z., Avery, C. L., Gogarten, S. M., Kerr, K. F., Laurie, C. C., Seyerle, A. A., Stilp, A., Assa, S., Abdullah Said, M., Yldau van der Ende, M., Lambiase, P. D., Orini, M., Ramirez, J., Van Duijvenboden, S., Arnar, D. O., Gudbjartsson, D. F., Holm, H., Sulem, P., Thorleifsson, G., Thorolfsdottir, R. B., Thorsteinsdottir, U., Benjamin, E. J., Tinker, A., Stefansson, K., Ellinor, P. T., Jamshidi, Y., Lubitz, S. A., Munroe, P. B., Fysiologie, RS: FHML MaCSBio, RS: Carim - B01 Blood proteins & engineering, Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Verkfræði- og náttúruvísindasvið (HÍ), School of Engineering and Natural Sciences (UI), Háskóli Íslands, and University of Iceland
Subjects: 0301 basic medicine, Male, Multifactorial Inheritance, General Physics and Astronomy, Gene Expression, Genome-wide association study, 030204 cardiovascular system & hematology, Arrhythmias, Genome-wide association studies, CALCINEURIN, Electrocardiography, 0302 clinical medicine, Cardiovascular Disease, Multi-ancestry GWAS, ELEMENTS, Medicine, Cardiac and Cardiovascular Systems, Blóðrásarsjúkdómar, lcsh:Science, RISK, DECREASE, education.field_of_study, Multidisciplinary, Kardiologi, medicine.diagnostic_test, 1184 Genetics, developmental biology, physiology, Atrial fibrillation, 3142 Public health care science, environmental and occupational health, 3. Good health, Endophenotype, Arrhythmias, Cardiac, Cardiovascular Diseases, Endophenotypes, Female, Genetic Loci, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Quantitative Trait Loci, cardiovascular system, Cardiology, medicine.symptom, Erfðarannsóknir, Cardiac, Medical Genetics, Human, Bradycardia, medicine.medical_specialty, Science, GENOME-WIDE ASSOCIATION, ATRIAL-FIBRILLATION, MUTATIONS, DURATION, CARDIOMYOPATHY, BRADYCARDIA, Population, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Internal medicine, Cardiac conduction, PR interval, education, Medicinsk genetik, business.industry, Cardiovascular genetics, General Chemistry, Arfgengi, medicine.disease, 030104 developmental biology, lcsh:Q, business
Abstract: Publisher's version (útgefin grein), The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease., We provide all investigator and study-specific acknowledgements in Supplementary Note 1, and funding sources in Supplementary Note 2.
Published: 2020

30. Adherence to dietary guidelines in relation to visceral fat and liver fat in middle-aged men and women: the NEO study

Author: Marjan Alssema, Hildo J. Lamb, Albert de Roos, Renée de Mutsert, Esther van Eekelen, Frits R. Rosendaal, Anouk Geelen, Epidemiology and Data Science, and APH - Methodology
Subjects: Male, Nutrition and Disease, Epidemiology, Cross-sectional study, Endocrinology, Diabetes and Metabolism, Medicine (miscellaneous), Adipose tissue, Physiology, 030209 endocrinology & metabolism, Intra-Abdominal Fat, Article, Nutrition Policy, 03 medical and health sciences, 0302 clinical medicine, Voeding en Ziekte, Liver fat, Life Science, Humans, Medicine, Processed meat, 030212 general & internal medicine, Restricted diet, Exercise, Visceral fat, Netherlands, VLAG, Nutrition and Dietetics, business.industry, Middle Aged, Magnetic Resonance Imaging, Fatty Liver, Cross-Sectional Studies, Liver, Risk factors, Basal metabolic rate, Red meat, Female, Energy Intake, business, Attitude to Health
Abstract: Background: It is unclear to what extent adherence to dietary guidelines may specifically affect visceral fat and liver fat. We aimed to study the association between the Dutch Healthy Diet Index (DHD-index) and total body fat, visceral adipose tissue (VAT) and hepatic triglyceride content (HTGC) in middle-aged men and women. Design: In this cross-sectional study, VAT was assessed by magnetic resonance imaging (MRI) in 2580 participants, and HTGC by proton-MR spectroscopy in 2083 participants. Habitual dietary intake and physical activity were estimated by questionnaire. Adherence to the current Dutch dietary guidelines was estimated by the 2015 DHD-index score based on the thirteen components (vegetables, fruit, wholegrain products, legumes, nuts, dairy, fish, tea, liquid fats, red meat, processed meat, sweetened beverages, and alcohol). The DHD-index ranges between 0 and 130 with a higher score indicating a healthier diet. We used linear regression to examine associations of the DHD-index with VAT and HTGC, adjusted for age, smoking, education, ethnicity, basal metabolic rate, energy restricted diet, menopausal state, physical activity, total energy intake, and total body fat. We additionally excluded the components one by one to examine individual contributions to the associations. Results: Included participants (43% men) had a mean (SD) age of 56 (6) years and DHD-index score of 71 (15). A 10-point higher DHD-index score was associated with 2.3 cm2 less visceral fat (95% CI; −3.5; −1.0 cm2) and less liver fat (0.94 times, 95% CI; 0.90; 0.98). Of all components, exclusion of dairy attenuated the associations with TBF and VAT. Conclusions: Adherence to the dietary guidelines as estimated by the DHD-index was associated with less total body fat, and with less visceral and liver fat after adjustment for total body fat. These findings might contribute to better understanding of the mechanisms underlying associations between dietary habits and cardiometabolic diseases.
Published: 2020

31. The association between overall and abdominal adiposity and depressive mood: A cross-sectional analysis in 6459 participants

Author: Tahani Alshehri, Frits R. Rosendaal, Yuri Milaneschi, Saskia le Cessie, Dennis O. Mook-Kanamori, Brenda W.J.H. Penninx, Sebastiaan C. Boone, Renée de Mutsert, Psychiatry, APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, and APH - Digital Health
Subjects: Male, medicine.medical_specialty, Waist, Cross-sectional study, Endocrinology, Diabetes and Metabolism, Population, Body fat distribution, 03 medical and health sciences, 0302 clinical medicine, Endocrinology, Risk Factors, Internal medicine, Medicine, Humans, Obesity, education, Biological Psychiatry, Body mass index, Adiposity, Aged, Netherlands, education.field_of_study, Endocrine and Autonomic Systems, business.industry, Depression, Depressive disorder, Confounding, Abdominal fat, Odds ratio, Middle Aged, medicine.disease, Confidence interval, 030227 psychiatry, Psychiatry and Mental health, Affect, Cross-Sectional Studies, Obesity, Abdominal, Female, business, 030217 neurology & neurosurgery
Abstract: Objective We aimed to evaluate the association between measures of adiposity with depressive mood and specific depressive symptoms. Methods This study was performed in the Netherlands Epidemiology of Obesity (NEO) study, a population-based study that consists of 6671 middle-aged individuals. We examined the association between measures of overall adiposity (BMI and total body fat), and abdominal adiposity (waist circumference and visceral adipose tissue), with depressive mood severity subgroups and 30 depressive symptoms. Multinomial logistic regression was performed adjusting for potential confounding. Results Measures of adiposity were associated with depressive mood in a graded fashion. Total body fat showed the strongest association with mild (Odds Ratio (OR): 1.59 per standard deviation, 95% Confidence Interval (95% CI): 1.41–1.80) and moderate to very severe (OR: 1.97, 95% CI: 1.59–2.44) depressive mood. Regarding individual symptoms of depressive mood, total body fat was associated with most depressive symptoms (strongest associations for hyperphagia and fatigability). Conclusions In the general population, overall and abdominal adiposity measures were associated with depressive mood. This association encompasses most of the depressive symptoms and appeared to be the strongest with specific ‘’atypical’’ neurovegetative symptoms, which may be an indication of an alteration in the energy homeostasis.
Published: 2019

32. Low Birth Weight and Kidney Function in Middle-Aged Men and Women: The Netherlands Epidemiology of Obesity Study

Author: Roelof A.J. Smit, Ton J. Rabelink, Kevin Esmeijer, Aiko P. J. de Vries, Renée de Mutsert, Johan W. de Fijter, Frits R. Rosendaal, Ellen K. Hoogeveen, and Dennis O. Mook-Kanamori
Subjects: Male, medicine.medical_specialty, Databases, Factual, Birth weight, 030232 urology & nephrology, Kidney Function Tests, Risk Assessment, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Sex Factors, Mendelian randomization, Epidemiology, medicine, Humans, 030212 general & internal medicine, Renal Insufficiency, Chronic, Aged, Netherlands, Retrospective Studies, Academic Medical Centers, business.industry, Age Factors, Infant, Newborn, Retrospective cohort study, Infant, Low Birth Weight, Mendelian Randomization Analysis, Middle Aged, medicine.disease, Middle age, Low birth weight, Nephrology, Cohort, Multivariate Analysis, Disease Progression, Linear Models, Female, Self Report, medicine.symptom, business, Demography, Kidney disease, Glomerular Filtration Rate
Abstract: Rationale & Objective: Chronic kidney disease (CKD), defined as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m(2), is a risk factor for cardiovascular morbidity and mortality. Little is known about low birth weight and risk for CKD in middle-aged adults in the general population. We estimated the causal association between birth weight and eGFR in a Dutch cohort of middle-aged men and women.Study Design: Retrospective cohort study.Setting & Participants: 6,671 participants in the Netherlands Epidemiology of Obesity (NEO) Study. Replication study using data for 133,814 participants studied by the CKDGen consortium.Exposure: Birth weight was self-reported and also based on an instrumental variable, 59 birth weight-associated genetic variants, derived from an independent data source.Outcome: eGFR at the age of 45 to 65 years.Analytical Approach: We assessed the association between self-reported birth weight and eGFR in the NEO Study using multivariable linear regression, adjusted for age, sex, education, smoking, and alcohol use. The effect of the instrument on eGFR was estimated using separate 2-sample Mendelian randomization analyses: one using individual data from the NEO cohort and one using summary data from the CKDGen consortium.Results: At baseline, mean eGFR was 86 +/- 12.4 (SD) mL/min/1.73 m(2). After multivariable adjustment, self-reported birth weight was not associated with kidney function in middle age. Two-sample Mendelian randomization analysis showed that in the NEO cohort, for each 500-g lower birth weight defined using genetic variants, there was a 3.7 (95% CI, 0.5-6.9)-mL/ min/1.73 m(2) lower eGFR at the age of 45 to 65 years. However, using CKDGen summary-level data, there was a smaller nonsignificant relationship between birth weight and eGFR.Limitations: Birth weight was self-reported.Conclusions: Lower birth weight defined using genetic variants was associated with lower eGFRs in Dutch middle-aged adults. However, this finding was not replicated within the CKDGen consortium.
Published: 2019

33. Early Hormonal Treatment Affects Body Composition and Body Shape in Young Transgender Adolescents

Author: Renée de Mutsert, Joost Rotteveel, Maartje Klaver, Daniel Klink, Jos W. R. Twisk, Chantal M. Wiepjes, Martin den Heijer, Internal medicine, AGEM - Endocrinology, metabolism and nutrition, APH - Health Behaviors & Chronic Diseases, Epidemiology and Data Science, ACS - Atherosclerosis & ischemic syndromes, Amsterdam Movement Sciences - Rehabilitation & Development, Amsterdam Movement Sciences - Restoration and Development, APH - Aging & Later Life, Pediatric surgery, ACS - Diabetes & metabolism, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, NCA - Neurobiology of mental health, and Amsterdam Reproduction & Development (AR&D)
Subjects: Male, Adolescent, Urology, Endocrinology, Diabetes and Metabolism, 030209 endocrinology & metabolism, Cross-Sex Hormonal Treatment, Transgender Persons, Body Mass Index, Gonadotropin-Releasing Hormone, 03 medical and health sciences, Absorptiometry, Photon, 0302 clinical medicine, Endocrinology, Transgender, Body Shape, Humans, Medicine, 030212 general & internal medicine, Retrospective Studies, Anthropometry, Waist-Hip Ratio, business.industry, Gonadotropin-Releasing Hormone Analogues, Retrospective cohort study, Total body, Psychiatry and Mental health, Reproductive Medicine, Reference values, Lean body mass, Body Composition, Female, Transgender Person, business, Transsexualism, Hormone, Demography
Abstract: Background Transgender adolescents aspiring to have the body characteristics of the affirmed sex can receive hormonal treatment. However, it is unknown how body shape and composition develop during treatment and whether transgender persons obtain the desired body phenotype. Aim To examine the change in body shape and composition from the start of treatment with gonadotropin-releasing hormone agonists (GnRHa) until 22 years of age and to compare these measurements at 22 years with those of age-matched peers. Methods 71 transwomen (birth-assigned boys) and 121 transmen (birth-assigned girls) who started treatment from 1998 through 2014 were included in this retrospective study. GnRHa treatment was started and cross-sex hormonal treatment was added at 16 years of age. Anthropometric and whole-body dual-energy x-ray absorptiometry data were retrieved from medical records. Linear mixed model regression was performed to examine changes over time. SD scores (SDS) were calculated to compare body shape and composition with those of age-matched peers. Outcomes Change in waist-hip ratio (WHR), total body fat (TBF), and total lean body mass (LBM) during hormonal treatment. SDS of measures of body shape and composition compared with age-matched peers at 22 years of age. Results In transwomen, TBF increased (+10%, 95% CI = 7–11) while total LBM (−10%, 95% CI = −11 to −7) and WHR (−0.04, 95% CI = −0.05 to −0.02) decreased. Compared with ciswomen, SDS at 22 years of age were +0.3 (95% CI = 0.0–0.5) for WHR, and 0.0 (95% CI = −0.2 to 0.3) for TBF. Compared with cismen, SDS were −1.0 (95% CI = −1.3 to −0.7) for WHR, and +2.2 (95% CI = 2.2–2.4) for TBF. In transmen, TBF decreased (−3%, 95% CI = −4 to −1), while LBM (+3%, 95% CI = 1–4) and WHR (+0.03, 95% CI = 0.01–0.04) increased. Compared with ciswomen, SDS at 22 years of age were +0.6 (95% CI = 0.4–0.8) for WHR, and −1.1 (95% CI = −1.4 to −0.9) for TBF. Compared with cismen, SDS were −0.5 (95% CI = −0.8 to −0.3) for WHR, and +1.8 (95% CI = 1.6–1.9) for TBF. Clinical Implications Knowing body shape and composition outcomes at 22 years of age will help care providers in counseling transgender youth on expectations of attaining the desired body phenotype. Strengths and Limitations This study presents the largest group of transgender adults to date who started treatment in their teens. Despite missing data, selection bias was not found. Conclusions During treatment, WHR and body composition changed toward the affirmed sex. At 22 years of age, transwomen compared better to age-matched ciswomen than to cismen, whereas transmen were between reference values for ciswomen and cismen.
Published: 2018

34. Sex differences in body fat distribution are related to sex differences in serum leptin and adiponectin

Author: Tim Christen, Renée de Mutsert, Martin den Heijer, J. Wouter Jukema, Christa M. Cobbaert, Hildo J. Lamb, Ingrid M. Jazet, S. Trompet, Ko Willems van Dijk, Frits R. Rosendaal, Jan B. van Klinken, Raymond Noordam, Internal medicine, AGEM - Endocrinology, metabolism and nutrition, Amsterdam Movement Sciences - Rehabilitation & Development, Amsterdam Movement Sciences - Restoration and Development, APH - Aging & Later Life, and Laboratory for General Clinical Chemistry
Subjects: Leptin, Male, medicine.medical_specialty, Physiology, 030209 endocrinology & metabolism, 030204 cardiovascular system & hematology, Intra-Abdominal Fat, Biochemistry, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Endocrinology, Interquartile range, Internal medicine, Sex differences, medicine, Body Fat Distribution, Humans, Visceral fat, Obesity, Total body fat, Serum adiponectin, Body fat distribution, Aged, Netherlands, Sex Characteristics, Adiponectin, business.industry, Odds ratio, Middle Aged, Cross-Sectional Studies, Serum leptin, Female, business, hormones, hormone substitutes, and hormone antagonists
Abstract: It is debated whether sex differences in adiponectin and leptin are due to sex differences in body fat distribution. In this cross-sectional analysis of the Netherlands Epidemiology of Obesity study, associations of measures of body fat and sex with serum adiponectin and leptin concentrations were examined using linear regression analysis (n = 6494, VAT: n = 2516). Sex differences were additionally adjusted for the measure of body fat that was most strongly associated with adiponectin or leptin concentrations. Median adiponectin concentrations in women and men were 10.5 mg/L (IQR, interquartile range: 7.7–13.9) and 6.1 mg/L (IQR: 4.5–8.2), mean difference 4.6 mg/L (95% CI: 4.3, 4.9). Median leptin concentrations in women and men were 19.2 μg/L (IQR: 11.5–30.0) and 7.1 μg/L (IQR: 4.6–11.1), mean difference 15.1 μg/L (95% CI: 14.4, 15.8). VAT was most strongly associated with adiponectin, total body fat percentage was most strongly associated with leptin. After adjustment for VAT, women had 3.8 mg/L (95% CI: 3.3, 4.3) higher adiponectin than men. After adjustment for total body fat percentage, leptin concentrations in women were 0.4 μg/L lower than in men (95% CI: −1.2, 2.0). One genetic variant (rs4731420) was associated with extreme leptin concentrations (>100 μg/L) in women: odds ratio 2.8 (95% CI: 1.7, 4.6). Total body fat percentage was strongly associated with leptin concentrations. Higher leptin concentrations in women than in men were completely explained by differences in total body fat percentage. Visceral fat was associated with adiponectin concentrations, and did not completely explain higher adiponectin concentrations in women than in men.
Published: 2018

35. Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway: a meta-analysis

Author: Emily Sonestedt, Ilkka Seppälä, Yanping Li, Lyn M. Steffen, Kari E. North, Denis Rybin, Mika Kähönen, Kristin L. Young, David S. Siscovick, Jiantao Ma, Carol A. Wang, Stephen S. Rich, Renée de Mutsert, Vera Mikkilä, Bruce M. Psaty, Danielle E. Haslam, Lu Qi, Oscar H. Franco, Alexis C. Frazier-Wood, Caren E. Smith, Nicola M. McKeown, L. Adrienne Cupples, Elisabeth T.M. Leermakers, Kenneth Rice, Christina-Alexandra Schulz, Josée Dupuis, Rozenn N. Lemaitre, Craig E. Pennell, Wendy H. Oddy, Mark A. Herman, Louise Brunkwall, Terho Lehtimäki, James B. Meigs, Marju Orho-Melander, Kenneth J. Mukamal, Ulrika Ericson, Tao Huang, Frits R. Rosendaal, Toshiko Tanaka, Jorma Viikari, Dariush Mozaffarian, Albert Hofman, Jessica C. Kiefte-de Jong, Mariaelisa Graff, Olli T. Raitakari, André G. Uitterlinden, Ruifang Li-Gao, Dennis O. Mook-Kanamori, Tzu An Chen, Hassan S. Dashti, Epidemiology, Erasmus MC other, Department of Food and Nutrition, and University of Helsinki
Subjects: 0301 basic medicine, Blood Glucose, Male, FGF21, Epidemiology, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Type 2 diabetes, CARDIOVASCULAR RISK-FACTORS, Insulin, METABOLIC SYNDROME, 2. Zero hunger, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Fasting, RANDOMIZED CONTROLLED-TRIAL, ADIPOSE-TISSUE, MACRONUTRIENT INTAKE, Female, 3143 Nutrition, medicine.medical_specialty, Offspring, FRUCTOSE TRANSPORT, Single-nucleotide polymorphism, Carbohydrate metabolism, Biology, Article, Beverages, 03 medical and health sciences, Internal medicine, Internal Medicine, medicine, Genetics, Humans, Nutrition, CONSUMPTION, Fructose transport, medicine.disease, ELEMENT-BINDING PROTEIN, Fibroblast Growth Factors, Meta-analysis, 030104 developmental biology, Endocrinology, Sweetening Agents, 3121 General medicine, internal medicine and other clinical medicine, Metabolic syndrome, RESISTANCE
Abstract: Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits. Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway. In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β ± SE 0.014 ± 0.004 [mmol/l], p = 1.5 × 10−3) and higher fasting insulin (0.030 ± 0.005 [log e pmol/l], p = 2.0 × 10−10). No significant interactions on glycaemic traits were observed between SSB intake and selected SNPs. While a suggestive interaction was observed in the discovery cohorts with a SNP (rs1542423) in the β-Klotho (KLB) locus on fasting insulin (0.030 ± 0.011 log e pmol/l, uncorrected p = 0.006), results in the replication cohorts and combined meta-analyses were non-significant. In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses’ Health Study).
Published: 2018

36. Incidental findings in research: A focus group study about the perspective of the research participant

Author: Yvonne M. Drewes, Ria Reis, Olaf M. Dekkers, Jeanet W. Blom, Renée de Mutsert, Martin den Heijer, Anna W de Boer, Mattijs E. Numans, Hildo J. Lamb, and Albert de Roos
Subjects: education.field_of_study, Truth Disclosure, business.industry, Population, Evidence-based medicine, Focus group, 03 medical and health sciences, 0302 clinical medicine, Informed consent, Research participant, Medicine, Radiology, Nuclear Medicine and imaging, 030212 general & internal medicine, Thematic analysis, education, business, 030217 neurology & neurosurgery, Clinical psychology, Qualitative research
Abstract: Purpose To explore the experiences and preferences of population-based research participants to whom an incidental finding was communicated. Materials and Methods Of the 2580 participants of the Netherlands Epidemiology of Obesity (NEO) study who underwent magnetic resonance imaging (MRI) scanning of the abdomen, heart, and/or brain, an incidental finding with presumed health importance was disclosed to 56 (2%) participants. These participants were invited to discuss their experiences regarding the communication of the finding by the NEO research team in a focus group discussion. Transcripts of the discussions were analyzed using thematic content analysis with an open coding system. Results Twenty-three persons participated in four discussions: 57% male; mean age 58 years; 74% findings were suspect for a malignancy. Overall, the participants were grateful for the disclosure of the incidental finding. They had assumed that any finding would be disclosed, and this was an important reason to participate in research. None regretted their informed consent to be notified about incidental findings. Disclosure of the finding had great impact on the lives of most participants. Difficulties with the transition from research participant to patient were frequently mentioned. Conclusion This study provides information to improve the communication of incidental findings by 1) giving clear information about which findings will be disclosed, and 2) demarcating the transition from research participant to patient, by making clear arrangements with medical specialists to guarantee careful follow-up of the finding. Level of Evidence: 3 J. Magn. Reson. Imaging 2017.
Published: 2017

37. The Association between Adult Weight Gain and Insulin Resistance at Middle Age: Mediation by Visceral Fat and Liver Fat

Author: Rob M. van Dam, Raymond Noordam, Saskia le Cessie, Inge Verkouter, Renée de Mutsert, Frits R. Rosendaal, Diana van Heemst, and Hildo J. Lamb
Subjects: medicine.medical_specialty, medicine.medical_treatment, visceral fat, lcsh:Medicine, 030209 endocrinology & metabolism, Article, 03 medical and health sciences, 0302 clinical medicine, Insulin resistance, Internal medicine, insulin resistance, medicine, 030212 general & internal medicine, fatty liver, business.industry, Insulin, lcsh:R, Fatty liver, Weight change, General Medicine, medicine.disease, Middle age, Endocrinology, Postprandial, Homeostatic model assessment, body weight changes, medicine.symptom, business, Weight gain
Abstract: We aimed to investigate the role of the amount of visceral fat and liver fat in the association between adult weight change and insulin resistance at middle age. In the Netherlands Epidemiology of Obesity study, adult weight change was calculated with recalled body weight at age 20 years and measured body weight at middle age. Measures of insulin resistance were calculated using both fasting and postprandial glucose and insulin concentrations. Visceral fat was assessed by magnetic resonance (MR) imaging and liver fat by proton-MR spectroscopy (N = 1758). We examined the association between adult weight change and insulin resistance with linear regression, adjusted for confounding factors. To investigate mediation, we additionally adjusted for total body fat, visceral fat, and liver fat. In participants who gained &ge, 50% of body weight during adulthood, homeostatic model assessment for insulin resistance (HOMA-IR) was 3.22 (95% CI 2.76, 3.77) times higher than in weight maintainers. In a joint model, total body fat mediated this association for 8.1% (95% CI &minus, 9.2, 25.4), visceral fat for 32.0% (18.6, 45.4%) and liver fat for 22.5% (15.0, 30.1). The association between adult weight gain and insulin resistance at middle age is largely mediated by both visceral fat and liver fat.
Published: 2019

38. Associations of autozygosity with a broad range of human phenotypes

Author: Dennis O. Mook-Kanamori, Salma M. Wakil, Lisa R. Yanek, Dominique P.V. de Kleijn, Gert J. de Borst, Alison D. Murray, Kamran Guity, Vincent W. V. Jaddoe, Mario Pirastu, Carole Ober, Giuseppe Matullo, Charles N. Rotimi, Daniela Ruggiero, Teresa Tusié-Luna, Wolfgang Lieb, Chew-Kiat Heng, John R. B. Perry, Hortensia Moreno-Macías, Jie Zhou, John M. Starr, Juhani Junttila, Lei Yu, Danielle Posthuma, Marcus Dörr, Yingchang Lu, Jonathan P. Bradfield, Einat Granot-Hershkovitz, Karina Meidtner, Wouter van Rheenen, T Esko, Maris Alver, Wen-Jane Lee, Zhengming Chen, Jennifer A. Brody, Paolo Gasparini, Yii-Der Ida Chen, Cinzia Sala, Peter P. Pramstaller, Gauri Prasad, Nana Matoba, Natalie Terzikhan, Simonetta Guarrera, Bjarke Feenstra, Peter Vollenweider, Smeeta Shrestha, Yi-Jen Hung, Lilja Stefansdottir, David R. Weir, Felix R. Day, Antonietta Robino, Liang Zhang, Lluis Quintana-Murci, Nicholas J. Timpson, Robyn E Wootton, Xue W. Mei, Dharambir K. Sanghera, Gisli Masson, Debbie A Lawlor, Thomas Meitinger, Sharon L.R. Kardia, Peter K. Joshi, Frank J. A. van Rooij, Claude Bouchard, Cassandra N. Spracklen, Ken K. Ong, Taulant Muka, Guanjie Chen, Laura J. Scott, Walter Palmas, Daniel I. Chasman, Sarah E. Medland, Krista Fischer, Blair H. Smith, Jon K. Sigurdsson, Leon Straker, Clara Viberti, Yuan Shi, Louis Pérusse, Peter J. van der Most, Timo Tõnis Sikka, Chris Haley, Kuang Lin, Leif Groop, Hester M. den Ruijter, Hakon Hakonarson, Masato Akiyama, Stephan J. L. Bakker, Sonja I. Berndt, Jeffery R. O'Connell, Cisca Wijmenga, Daniele Cusi, Lorena Orozco, Kristjan H. S. Moore, Kevin Sandow, Stephen S. Rich, Stephanie J. Loomis, George Davey Smith, Cornelia M. van Duijn, Sharvari Rahul Shukla, Agnar Helgason, Thorsten Kessler, Anuj Goel, Dan Mason, David W. Clark, James S. Pankow, Simona Vaccargiu, Uwe Völker, Tamara B. Harris, Matthew A. Allison, Clicerio Gonzalez, Sarju Ralhan, I-Te Lee, Matthias Laudes, Yen-Feng Chiu, Neil Poulter, Benjamin Lehne, John Wright, Lawrence F. Bielak, Philip L. De Jager, Reinhold Schmidt, Ya Xing Wang, Matthias Nauck, Diana L. Cousminer, Patrick Deelen, Ani Manichaikul, Stephen J. Chanock, Anders Hamsten, Barry I. Freedman, Gudmar Thorleifsson, Peter Kraft, Ozren Polasek, Jie Yao, Yoshinori Murakami, Paul M. Ridker, Anubha Mahajan, Struan F.A. Grant, Claudia Schurmann, Bjarni Gunnarsson, Catriona L. K. Barnes, Jessica van Setten, Sandosh Padmanabhan, Alena Stančáková, Markus M. Lerch, Anuradha Jagadeesan, Franco Giulianini, Daniel F. Gudbjartsson, Dwaipayan Bharadwaj, Shengchao Alfred Li, Peter S. Sever, Trevor A. Mori, Albertine J. Oldehinkel, Koichi Matsuda, Xueling Sim, Evangelos Evangelou, André G. Uitterlinden, Pekka Jousilahti, Yukihide Momozawa, Ioanna Tzoulaki, Chao A. Hsiung, Ginevra Biino, Murielle Bochud, Hannele Mattsson, Ilja M. Nolte, Sarah H. Wild, Patricia B. Munroe, Jianjun Liu, Bruce M. Psaty, Giriraj R. Chandak, Masahiro Kanai, Tony R. Merriman, Teemu Palviainen, Rodney A. Lea, Janie Corley, Nicholas J. Wareham, Alan B. Zonderman, Makoto Hirata, Matthew J. Bixley, Caroline Hayward, Nora Franceschini, Kristel R van Eijk, Etienne Patin, Daniel Shriner, Niek Verweij, Xiuqing Guo, Fredrik Karpe, Ruth J. F. Loos, Tiinamaija Tuomi, Ashley van der Spek, Patricia A. Peyser, Jessica D. Faul, Christian Fuchsberger, David Cesarini, Alex S. F. Doney, Janine F. Felix, Cornelius A. Rietveld, Jagadish Vangipurapu, Tanguy Corre, Line Skotte, Rajkumar Dorajoo, Catherine Igartua, Meena Kumari, Nona Sotoodehnia, Leonard H. van den Berg, Najaf Amin, Dale R. Nyholt, Harry Campbell, Massimiliano Cocca, Scott D. Gordon, Patrik K. E. Magnusson, John C. Chambers, Traci M. Bartz, Mike A. Nalls, Tin Aung, Nduna Dzimiri, Colin N. A. Palmer, Rob M. van Dam, Johanna Kuusisto, Russell P. Tracy, Anna Damulina, Pierre-Emmanuel Morange, Sylvain Foisy, Jing Hua Zhao, Nicholas G. Martin, Ching-Yu Cheng, Mariaelisa Graff, Rashmi B. Prasad, Alice Stanton, David-Alexandre Trégouët, Yu Guo, Helen R. Warren, Lyn R. Griffiths, Weihua Meng, Annika Tillander, Christa Meisinger, Albert V. Smith, Mark I. McCarthy, Jingyun Yang, Marine Germain, Neil Small, Linda Broer, Vilmundur Gudnason, Gunnar K. Pálsson, Michele K. Evans, Alexander Teumer, Mark J. Caulfield, Giorgia Girotto, Thomas Lumley, Tinca J. C. Polderman, Wei Zhao, Carlos A. Aguilar-Salinas, Jari Lahti, Matthew L. Albert, Yechiel Friedlander, Veikko Salomaa, Iona Y Millwood, Jan H. Veldink, Archie Campbell, Andres Metspalu, Ulf Gyllensten, Grant W. Montgomery, Veronique Vitart, Jai Rup Singh, Saima Afaq, Alan R. Shuldiner, Miao-Li Chee, Adebowale Adeyemo, Jennifer A. Smith, David A. van Heel, Jaspal S. Kooner, Daniela Toniolo, Cristian Pattaro, Jerome I. Rotter, John Whitfield, Melissa C. Smart, Kari E. North, Salman M. Tajuddin, Tallapragada Divya Sri Priyanka, Christopher A. Haiman, Diane M. Becker, Bernhard K. Krämer, Paul Elliott, Lihua Wang, He Gao, Patrick Sulem, Jinyan Huang, Chiea Chuen Khor, Ruifang Li-Gao, Åsa Johansson, Winfried März, Shai Carmi, Ilaria Gandin, Eric Boerwinkle, Gardar Sveinbjornsson, Saskia P. Hagenaars, Sander W. van der Laan, Gerard Pasterkamp, E-Shyong Tai, Hagit Hochner, Yih Chung Tham, Kent D. Taylor, Kari Stefansson, Matt J. Neville, Craig E. Pennell, Yanchun Bao, Annelot M. Dekker, Helena Schmidt, Mehdi Hedayati, Joshua Elliott, Ian J. Deary, Iris E. Jansen, Judith B. Borja, Edith Hofer, Martin Gögele, Igor Rudan, Lude Franke, Matthias Munz, Folkert W. Asselbergs, Bengt Sennblad, Imo Hofer, John D. Rioux, Pim van der Harst, Bahareh Sedaghati-khayat, Giovanni Cugliari, Morris A. Swertz, Francine Grodstein, Erwin P. Bottinger, Carol A. Wang, Andre Franke, Brian F. Meyer, Adele M. Taylor, Klodian Dhana, Jian'an Luan, Constance Turman, Robert A. Scott, May E. Montasser, Alison Pattie, Marco Brumat, Liming Li, Heiner Boeing, Karen L. Mohlke, Clemens Baumbach, Bishwa Raj Sapkota, Unnur Thorsteinsdottir, Naveed Sattar, Amy R. Bentley, Matthias B. Schulze, Ivana Kolcic, Stella Trompet, Sarah E. Harris, Ayo P. Doumatey, Charumathi Sabanayagam, David Eccles, Mary F. Feitosa, Jost B. Jonas, Massimo Mezzavilla, Mark O. Goodarzi, David Ellinghaus, Heribert Schunkert, Christian Gieger, Heikki V. Huikuri, Lingyao Zeng, Johan G. Eriksson, Woon-Puay Koh, Yucheng Jia, Gurpreet Singh Wander, James F. Wilson, Torgny Karlsson, Steven C. Hunt, Weihua Zhang, Maria Pina Concas, Zoltán Kutalik, Rebecca Rohde, Chittaranjan S. Yajnik, Yasaman Saba, Dabeeru C. Rao, Robin G. Walters, Reedik Mägi, Marie Loh, Eero Vuoksimaa, Josyf C. Mychaleckyj, Katri Räikkönen, Philippe Goyette, M. Arfan Ikram, Alicia Huerta-Chagoya, David J. Porteous, Teresa Nutile, J. Wouter Jukema, Noha A. Yousri, Yoichiro Kamatani, Maryam S. Daneshpour, Babette S. Zemel, Rona J. Strawbridge, Tien Yin Wong, Claudia Langenberg, Amy Moore, Marcus E. Kleber, Fereidoun Azizi, Avner Halevy, Erika Salvi, Francis S. Collins, Markku Laakso, Tim Kacprowski, S. Sunna Ebenesersdóttir, William R. Scott, Michael Boehnke, Jin-Fang Chai, Markus Perola, Nicola Pirastu, Wayne Huey-Herng Sheu, Robert Karlsson, Lenore J. Launer, Lili Milani, Renée de Mutsert, Fernando Rivadeneira, David A. Bennett, Nicola D. Kerrison, Paolo Manunta, Graciela E. Delgado, Magnus Johannesson, Carolina Medina-Gomez, Alanna C. Morrison, Kay-Tee Khaw, Jian-Min Yuan, Jaakko Kaprio, Melanie Waldenberger, Ralf Ewert, Hugoline G. de Haan, Andrew A. Hicks, Yukinori Okada, Maria Sabater-Lleal, Marilyn C. Cornelis, Stephanie J. London, Federica Rizzi, Jeanette Erdmann, Marina Ciullo, Michiaki Kubo, University of Edinburgh, Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Osaka University Graduate School of Medicine, Laboratory for Cardiovascular Genomics and Informatics [Yokohama] (RIKEN IMS), RIKEN Center for Integrative Medical Sciences [Yokohama] (RIKEN IMS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN)-RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), deCODE genetics [Reykjavik], Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK (BIHR), Area Science Park, Università degli studi di Trieste = University of Trieste, MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Interfaculty Institute for Genetics and Functional Genomics, Universität Greifswald - University of Greifswald, Harbor UCLA Medical Center [Torrance, Ca.], Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, Department of Electrical and Computer Engineering [Waterloo] (ECE), University of Waterloo [Waterloo], Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet [Stockholm], Institute of Pop. Genetics, CNR, Sassari, Shardna life science Pula Cagliari, Swiss Institute of Bioinformatics [Lausanne] (SIB), Université de Lausanne = University of Lausanne (UNIL), Medstar Research Institute, Florida State University [Tallahassee] (FSU), University Medical Center [Utrecht], Centre for Population Health Sciences, Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Université Pierre et Marie Curie - Paris 6 (UPMC)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), California State University [Sacramento], Department of Thrombosis and Haemostasis, Leiden University Medical Center (LUMC), Universiteit Leiden-Universiteit Leiden, Medical University Graz, Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, University of Heidelberg, Heidelberg, Frederick National Laboratory for Cancer Research (FNLCR), Wellcome Trust Centre of Human Genetics, University of Oxford, Department of Epidemiology, German Institute of Human Nutrition, University Medical Center Groningen [Groningen] (UMCG), Institute of Genetics and Biophysics, National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Department of Medicine, Surgery, and Dentistry, University of Milano, Icelandic Heart Association, Kopavogur, Iceland., Department of Epidemiology [Rotterdam], Erasmus University Medical Center [Rotterdam] (Erasmus MC), University of Glasgow, Department of Cardiology, Leiden University Medical Center, Leiden, Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, Queen Mary University of London (QMUL), General Internal Medicine, Johns Hopkins School of Medicine, Johns Hopkins University School of Medicine [Baltimore], Institut de biologie moléculaire des plantes (IBMP), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Immunobiologie des Cellules dendritiques, Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Recherche Translationnelle - Center for Translational Science (CRT), Institut Pasteur [Paris] (IP), Genentech, Inc., Genentech, Inc. [San Francisco], University of Tartu, Duke-NUS Medical School [Singapore], Deutsches Institut für Ernährungsforschung Potsdam-Rehbrücke (DifE), Leibniz Association, Human Genome Sequencing Center, Baylor College of Medicine, Baylor College of Medicine (BCM), Baylor University-Baylor University, University of San Carlos, Office of Population Studies Foundation, Icahn School of Medicine at Mount Sinai [New York] (MSSM), King‘s College London, Division of Cancer Epidemiology and Genetics, National Cancer Institute [Bethesda] (NCI-NIH), National Institutes of Health [Bethesda] (NIH)-National Institutes of Health [Bethesda] (NIH), University of Oxford, Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty of Mannheim, University of Heidelberg, Division of Molecular & Clinical Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, Department of Internal Medicine B, University Medicine Greifswald, Greifswald, University of Chicago, University of Huddersfield, Infectious diseases division, Department of internal medicine, Washington University in Saint Louis (WUSTL), Section on Nephrology [Winston-Salem, NC, USA] (Department of Internal Medicine), Wake Forest School of Medicine [Winston-Salem], Wake Forest Baptist Medical Center-Wake Forest Baptist Medical Center, Radcliffe Department of Medicine [Oxford], Harvard School of Public Health, Kunming University of Science and Technology (KMUST), Sans affiliation, University of Southern California (USC), National Institute on Aging [Bethesda, USA] (NIA), National Institutes of Health [Bethesda] (NIH), Centre National de Génotypage (CNG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), MRC Centrer for Nutritional Epidemiology and Cancer Prevention and Survival, University of Cambridge [UK] (CAM), National University of Singapore (NUS), Experimental Cardiology Laboratory (ECL), Unirversity Medical Center, Department of Medical Statistics, Epidemiology and Medical Informatics, University of Zagreb, Department of Medical Genetics, Department of Medicine, University of Eastern Finland-Kuopio University Hospital, MRC Epidemiology Unit, University of Cambridge [UK] (CAM)-Institute of Metabolic Science, Capital Normal University [Beijing], Saw Swee Hock School of Public Health, National Institute for Environmental Health Sciences Research Triangle Park, Brown University, MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, Toyota Research Institute, Helmholtz Zentrum München = German Research Center for Environmental Health, Department of Chemistry and Biochemistry [Boulder], University of Colorado [Boulder], Centre recherche en CardioVasculaire et Nutrition = Center for CardioVascular and Nutrition research (C2VN), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Hôpital de la Timone [CHU - APHM] (TIMONE), Metacohorts Consortium, Universiteit Leiden, Institute of Clinical Chemistry and Laboratory Medicine, University of Groningen [Groningen], Medical Research Concil Epidemiology Unit, Institute of Medical Science, Faculty of Medicine, Genetics and Pathology, Imperial College London, Génétique Evolutive Humaine - Human Evolutionary Genetics, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Brigham and Women's Hospital [Boston], Erasmus University Rotterdam, Department of Chronic Disease Prevention, National Institute for Health and Welfare [Helsinki], Department of Biostatistics and Center for Statistical Genetics, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System-School of public health, The University of Hong Kong (HKU)-The University of Hong Kong (HKU), Stockholm Bioinformatics Center (SBC), Stockholm University, Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, INRH, Department of Genetics, Los Angeles Biomedical Research Institute (LA BioMed), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán - National Institute of Medical Science and Nutrition Salvador Zubiran [Mexico], Western General Hospital, German Research Center for Environmental Health - Helmholtz Center München (GmbH), Medical Research Council, Division of Cancer Control and Population Sciences, University of Pittsburgh Cancer Institute-University of Pittsburgh Graduate School of Public Health, Zhengzhou University of Light Industry, Department of Electrical and Electronic Engineering [Niigata Univ.], Niigata University, Genetic Epidemiology Unit, University College of London [London] (UCL), Aston Business School, Aston University [Birmingham], Division of Cancer Epidemiology and Genetics [Bethesda, MD, États-Unis], Centre Hospitalier Universitaire Vaudois (CHUV), Pennington Biomedical Research Center, University of Washington [Seattle], Guy's and St Thomas' Hospitals, Northwestern Polytechnical University [Xi'an] (NPU), Department of Social Medicine, University of Bristol [Bristol], Department of Genomics of Common Disease [London, UK], Imperial College London-Hammersmith Hospital NHS Imperial College Healthcare, Department of Internal Medicine, Institute of Clinical Molecular Biology, Kiel University, Medizinische Klinik II, Universität zu Lübeck = University of Lübeck [Lübeck], Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina, Institute for Social Research, University of Michigan System-University of Michigan System, Division of Statistical Genomics, Washington University School of Medicine, Institute for Clinical Molecular Biology, Christian-Albrechts-Universität zu Kiel (CAU), Department of Physics, RISSC-Lab-University of Naples Federico II = Università degli studi di Napoli Federico II, Lund University [Lund], Icelandic Heart Association, Heart Preventive Clinic and Research Institute, The Center for Applied Genomics, Children’s Hospital of Philadelphia (CHOP ), Génétique moléculaire de la neurotransmission et des processus neurodégénératifs (LGMNPN), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Medical Research Center Oulu, University of Oulu, University of Utah School of Medicine [Salt Lake City], The Generation R Study, Pediatrics, Epidemiology, Center for Translational and Computational Neuroimmunology [New York, NY, États-Unis] (CTCN), Department of Neurology [New York, NY, États-Unis], Columbia University Medical Center (CUMC), Columbia University [New York]-Columbia University [New York]-Columbia University Medical Center (CUMC), Columbia University [New York]-Columbia University [New York], Universität Heidelberg [Heidelberg] = Heidelberg University, Interuniversity Cardiology Institute Netherlands, School of Public Health, University of Michigan [Dearborn], Department of Epidemiology and Public Health, University of Kuopio, Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Institute of Epidemiology and Biobank PopGen, Department of Biostatistics, University of Washington, Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), Clinical Institute of Medical and Chemical Laboratory Diagnostics, Karl-Franzens-Universität Graz, Department of Genetics, Biology and Biochemistry, Università degli studi di Torino = University of Turin (UNITO), Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), QIMR Berghofer Medical Research Institute, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC)-UNC Gillings School of Global Public Health-Carolina Center for Genome Sciences, University of Illinois [Chicago] (UIC), University of Illinois System, Experimental Cardiology Laboratory, Genetic Epidemiology and Clinical Research Group, Umea University Hospital, Functional Genomics, Erasmus Medical Centre, National Human Genome Research Institute (NHGRI), School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California (UC)-University of California (UC), Department of Pathological Biochemistry, Royal Infirmary, German Institute of Human Nutrition Potsdam-Rehbrücke (DIfE), Institute of Metabolic Science, MRC, University of Maryland School of Medicine [Baltimore, MD, USA], Centre for Molecular Epidemiology, Centre for Causal Analyses in Translational Epidemiology, University of Bristol [Bristol]-Medical Research Council, IRCCS San Raffaele Scientific Institute [Milan, Italie], U937, Génomique cardiovasculaire, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire Vaudois [Lausanne] (CHUV), University of Michigan System, HMNC Brain Health, Singapore Eye Research Institute, Partenaires INRAE, Institut d'Électronique et des Technologies du numéRique (IETR), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Institute for Molecular Medicine Finland [Helsinki] (FIMM), Helsinki Institute of Life Science (HiLIFE), Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Department of Psychiatry and Psychotherapy, Rheinische Friedrich-Wilhelms-Universität Bonn, University of Groningen, Department of Genomics of Common Disease, Department of Microbiology, The Freeman Hospital, Department Biostatistics University of North Carolina, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Clark, D. W., Okada, Y., Moore, K. H. S., Mason, D., Pirastu, N., Gandin, I., Mattsson, H., Barnes, C. L. K., Lin, K., Zhao, J. H., Deelen, P., Rohde, R., Schurmann, C., Guo, X., Giulianini, F., Zhang, W., Medina-Gomez, C., Karlsson, R., Bao, Y., Bartz, T. M., Baumbach, C., Biino, G., Bixley, M. J., Brumat, M., Chai, J. -F., Corre, T., Cousminer, D. L., Dekker, A. M., Eccles, D. A., van Eijk, K. R., Fuchsberger, C., Gao, H., Germain, M., Gordon, S. D., de Haan, H. G., Harris, S. E., Hofer, E., Huerta-Chagoya, A., Igartua, C., Jansen, I. E., Jia, Y., Kacprowski, T., Karlsson, T., Kleber, M. E., Li, S. A., Li-Gao, R., Mahajan, A., Matsuda, K., Meidtner, K., Meng, W., Montasser, M. E., van der Most, P. J., Munz, M., Nutile, T., Palviainen, T., Prasad, G., Prasad, R. B., Priyanka, T. D. S., Rizzi, F., Salvi, E., Sapkota, B. R., Shriner, D., Skotte, L., Smart, M. C., Smith, A. V., van der Spek, A., Spracklen, C. N., Strawbridge, R. J., Tajuddin, S. M., Trompet, S., Turman, C., Verweij, N., Viberti, C., Wang, L., Warren, H. R., Wootton, R. E., Yanek, L. R., Yao, J., Yousri, N. A., Zhao, W., Adeyemo, A. A., Afaq, S., Aguilar-Salinas, C. A., Akiyama, M., Albert, M. L., Allison, M. A., Alver, M., Aung, T., Azizi, F., Bentley, A. R., Boeing, H., Boerwinkle, E., Borja, J. B., de Borst, G. J., Bottinger, E. P., Broer, L., Campbell, H., Chanock, S., Chee, M. -L., Chen, G., Chen, Y. -D. I., Chen, Z., Chiu, Y. -F., Cocca, M., Collins, F. S., Concas, M. P., Corley, J., Cugliari, G., van Dam, R. M., Damulina, A., Daneshpour, M. S., Day, F. R., Delgado, G. E., Dhana, K., Doney, A. S. F., Dorr, M., Doumatey, A. P., Dzimiri, N., Ebenesersdottir, S. S., Elliott, J., Elliott, P., Ewert, R., Felix, J. F., Fischer, K., Freedman, B. I., Girotto, G., Goel, A., Gogele, M., Goodarzi, M. O., Graff, M., Granot-Hershkovitz, E., Grodstein, F., Guarrera, S., Gudbjartsson, D. F., Guity, K., Gunnarsson, B., Guo, Y., Hagenaars, S. P., Haiman, C. A., Halevy, A., Harris, T. B., Hedayati, M., van Heel, D. A., Hirata, M., Hofer, I., Hsiung, C. A., Huang, J., Hung, Y. -J., Ikram, M. A., Jagadeesan, A., Jousilahti, P., Kamatani, Y., Kanai, M., Kerrison, N. D., Kessler, T., Khaw, K. -T., Khor, C. C., de Kleijn, D. P. V., Koh, W. -P., Kolcic, I., Kraft, P., Kramer, B. K., Kutalik, Z., Kuusisto, J., Langenberg, C., Launer, L. J., Lawlor, D. A., Lee, I. -T., Lee, W. -J., Lerch, M. M., Li, L., Liu, J., Loh, M., London, S. J., Loomis, S., Lu, Y., Luan, J., Magi, R., Manichaikul, A. W., Manunta, P., Masson, G., Matoba, N., Mei, X. W., Meisinger, C., Meitinger, T., Mezzavilla, M., Milani, L., Millwood, I. Y., Momozawa, Y., Moore, A., Morange, P. -E., Moreno-Macias, H., Mori, T. A., Morrison, A. C., Muka, T., Murakami, Y., Murray, A. D., de Mutsert, R., Mychaleckyj, J. C., Nalls, M. A., Nauck, M., Neville, M. J., Nolte, I. M., Ong, K. K., Orozco, L., Padmanabhan, S., Palsson, G., Pankow, J. S., Pattaro, C., Pattie, A., Polasek, O., Poulter, N., Pramstaller, P. P., Quintana-Murci, L., Raikkonen, K., Ralhan, S., Rao, D. C., van Rheenen, W., Rich, S. S., Ridker, P. M., Rietveld, C. A., Robino, A., van Rooij, F. J. A., Ruggiero, D., Saba, Y., Sabanayagam, C., Sabater-Lleal, M., Sala, C. F., Salomaa, V., Sandow, K., Schmidt, H., Scott, L. J., Scott, W. R., Sedaghati-Khayat, B., Sennblad, B., van Setten, J., Sever, P. J., Sheu, W. H. -H., Shi, Y., Shrestha, S., Shukla, S. R., Sigurdsson, J. K., Sikka, T. T., Singh, J. R., Smith, B. H., Stancakova, A., Stanton, A., Starr, J. M., Stefansdottir, L., Straker, L., Sulem, P., Sveinbjornsson, G., Swertz, M. A., Taylor, A. M., Taylor, K. D., Terzikhan, N., Tham, Y. -C., Thorleifsson, G., Thorsteinsdottir, U., Tillander, A., Tracy, R. P., Tusie-Luna, T., Tzoulaki, I., Vaccargiu, S., Vangipurapu, J., Veldink, J. H., Vitart, V., Volker, U., Vuoksimaa, E., Wakil, S. M., Waldenberger, M., Wander, G. S., Wang, Y. X., Wareham, N. J., Wild, S., Yajnik, C. S., Yuan, J. -M., Zeng, L., Zhang, L., Zhou, J., Amin, N., Asselbergs, F. W., Bakker, S. J. L., Becker, D. M., Lehne, B., Bennett, D. A., van den Berg, L. H., Berndt, S. I., Bharadwaj, D., Bielak, L. F., Bochud, M., Boehnke, M., Bouchard, C., Bradfield, J. P., Brody, J. A., Campbell, A., Carmi, S., Caulfield, M. J., Cesarini, D., Chambers, J. C., Chandak, G. R., Cheng, C. -Y., Ciullo, M., Cornelis, M., Cusi, D., Smith, G. D., Deary, I. J., Dorajoo, R., van Duijn, C. M., Ellinghaus, D., Erdmann, J., Eriksson, J. G., Evangelou, E., Evans, M. K., Faul, J. D., Feenstra, B., Feitosa, M., Foisy, S., Franke, A., Friedlander, Y., Gasparini, P., Gieger, C., Gonzalez, C., Goyette, P., Grant, S. F. A., Griffiths, L. R., Groop, L., Gudnason, V., Gyllensten, U., Hakonarson, H., Hamsten, A., van der Harst, P., Heng, C. -K., Hicks, A. A., Hochner, H., Huikuri, H., Hunt, S. C., Jaddoe, V. W. V., De Jager, P. L., Johannesson, M., Johansson, A., Jonas, J. B., Jukema, J. W., Junttila, J., Kaprio, J., Kardia, S. L. R., Karpe, F., Kumari, M., Laakso, M., van der Laan, S. W., Lahti, J., Laudes, M., Lea, R. A., Lieb, W., Lumley, T., Martin, N. G., Marz, W., Matullo, G., Mccarthy, M. I., Medland, S. E., Merriman, T. R., Metspalu, A., Meyer, B. F., Mohlke, K. L., Montgomery, G. W., Mook-Kanamori, D., Munroe, P. B., North, K. E., Nyholt, D. R., O'Connell, J. R., Ober, C., Oldehinkel, A. J., Palmas, W., Palmer, C., Pasterkamp, G. G., Patin, E., Pennell, C. E., Perusse, L., Peyser, P. A., Pirastu, M., Polderman, T. J. C., Porteous, D. J., Posthuma, D., Psaty, B. M., Rioux, J. D., Rivadeneira, F., Rotimi, C., Rotter, J. I., Rudan, I., Den Ruijter, H. M., Sanghera, D. K., Sattar, N., Schmidt, R., Schulze, M. B., Schunkert, H., Scott, R. A., Shuldiner, A. R., Sim, X., Small, N., Smith, J. A., Sotoodehnia, N., Tai, E. -S., Teumer, A., Timpson, N. J., Toniolo, D., Tregouet, D. -A., Tuomi, T., Vollenweider, P., Wang, C. A., Weir, D. R., Whitfield, J. B., Wijmenga, C., Wong, T. -Y., Wright, J., Yang, J., Yu, L., Zemel, B. S., Zonderman, A. B., Perola, M., Magnusson, P. K. E., Uitterlinden, A. G., Kooner, J. S., Chasman, D. I., Loos, R. J. F., Franceschini, N., Franke, L., Haley, C. S., Hayward, C., Walters, R. G., Perry, J. R. B., Esko, T., Helgason, A., Stefansson, K., Joshi, P. K., Kubo, M., Wilson, J. F., Læknadeild (HÍ), Faculty of Medicine (UI), Félagsfræði-, mannfræði- og þjóðfræðideild (HÍ), Faculty of Sociology, Anthropology and Folkloristics (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), School of Engineering and Natural Sciences (UI), Verkfræði- og náttúruvísindasvið (HÍ), Félagsvísindasvið (HÍ), School of Social Sciences (UI), Háskóli Íslands, University of Iceland, Clark, David W [0000-0002-1025-9185], Okada, Yukinori [0000-0002-0311-8472], Moore, Kristjan H S [0000-0002-9579-4362], Mason, Dan [0000-0002-0026-9216], Pirastu, Nicola [0000-0002-5363-3886], Gandin, Ilaria [0000-0003-3196-2491], Deelen, Patrick [0000-0002-5654-3966], Schurmann, Claudia [0000-0003-4158-9192], Medina-Gomez, Carolina [0000-0001-7999-5538], Karlsson, Robert [0000-0002-8949-2587], Bao, Yanchun [0000-0002-6102-5098], Biino, Ginevra [0000-0002-9936-946X], Brumat, Marco [0000-0003-3268-039X], Chai, Jin-Fang [0000-0003-3770-1137], Eccles, David A [0000-0003-4634-4995], Gordon, Scott D [0000-0001-7623-328X], Harris, Sarah E [0000-0002-4941-5106], Kacprowski, Tim [0000-0002-5393-2413], Karlsson, Torgny [0000-0001-8095-6149], Kleber, Marcus E [0000-0003-0663-7275], Mahajan, Anubha [0000-0001-5585-3420], Matsuda, Koichi [0000-0001-7292-2686], Meng, Weihua [0000-0001-5388-8494], van der Most, Peter J [0000-0001-8450-3518], Munz, Matthias [0000-0002-4728-3357], Palviainen, Teemu [0000-0002-7847-8384], Prasad, Rashmi B [0000-0002-4400-6741], Salvi, Erika [0000-0002-2724-2291], Skotte, Line [0000-0002-7398-1271], van der Spek, Ashley [0000-0001-7136-0159], Spracklen, Cassandra N [0000-0003-3590-7182], Strawbridge, Rona J [0000-0001-8506-3585], Tajuddin, Salman M [0000-0002-7919-8528], Verweij, Niek [0000-0002-4303-7685], Yanek, Lisa R [0000-0001-7117-1075], Zhao, Wei [0000-0001-7388-0692], Albert, Matthew L [0000-0001-7285-6973], Bentley, Amy R [0000-0002-0827-9101], Chanock, Stephen [0000-0002-2324-3393], Chen, Zhengming [0000-0001-6423-105X], Chiu, Yen-Feng [0000-0002-3352-4500], Cocca, Massimiliano [0000-0002-1127-7596], Collins, Francis S [0000-0002-1023-7410], Cugliari, Giovanni [0000-0002-6080-0718], Damulina, Anna [0000-0001-8241-2727], Day, Felix R [0000-0003-3789-7651], Dhana, Klodian [0000-0002-6397-7009], Dzimiri, Nduna [0000-0003-3395-5754], Elliott, Paul [0000-0002-7511-5684], Felix, Janine F [0000-0002-9801-5774], Freedman, Barry I [0000-0003-0275-5530], Girotto, Giorgia [0000-0003-4507-6589], Goel, Anuj [0000-0003-2307-4021], Goodarzi, Mark O [0000-0001-6364-5103], Gudbjartsson, Daniel F [0000-0002-5222-9857], Guity, Kamran [0000-0002-8379-9668], van Heel, David A [0000-0002-0637-2265], Hirata, Makoto [0000-0002-9994-9958], Ikram, M Arfan [0000-0003-0372-8585], Kamatani, Yoichiro [0000-0001-8748-5597], Kanai, Masahiro [0000-0001-5165-4408], Khor, Chiea Chuen [0000-0002-1128-4729], Kolcic, Ivana [0000-0001-7918-6052], Langenberg, Claudia [0000-0002-5017-7344], Lawlor, Deborah A [0000-0002-6793-2262], Liu, Jianjun [0000-0002-3255-3019], London, Stephanie J [0000-0003-4911-5290], Luan, Jian’an [0000-0003-3137-6337], Matoba, Nana [0000-0001-5329-0134], Mei, Xue W [0000-0002-6279-4884], Mezzavilla, Massimo [0000-0002-9000-4595], Milani, Lili [0000-0002-5323-3102], Mori, Trevor A [0000-0002-5264-9229], Murakami, Yoshinori [0000-0002-2826-4396], Murray, Alison D [0000-0003-4915-4847], Mychaleckyj, Josyf C [0000-0003-2595-0005], Neville, Matt J [0000-0002-6004-5433], Nolte, Ilja M [0000-0001-5047-4077], Ong, Ken K [0000-0003-4689-7530], Pálsson, Gunnar [0000-0002-8231-3961], Pankow, James S [0000-0001-7076-483X], Pattaro, Cristian [0000-0002-4119-0109], Quintana-Murci, Lluis [0000-0003-2429-6320], van Rheenen, Wouter [0000-0002-5860-1533], Rich, Stephen S [0000-0003-3872-7793], Rietveld, Cornelius A [0000-0003-4053-1861], Ruggiero, Daniela [0000-0003-3898-7827], Sabanayagam, Charumathi [0000-0002-4042-4719], Sabater-Lleal, Maria [0000-0002-0128-379X], Sala, Cinzia Felicita [0000-0003-2514-2075], Salomaa, Veikko [0000-0001-7563-5324], Scott, Laura J [0000-0002-4886-5084], Sedaghati-Khayat, Bahareh [0000-0002-7665-8648], Sennblad, Bengt [0000-0002-4360-8003], van Setten, Jessica [0000-0002-4934-7510], Smith, Blair H [0000-0002-5362-9430], Stančáková, Alena [0000-0002-1375-0252], Stanton, Alice [0000-0002-4961-165X], Straker, Leon [0000-0002-7786-4128], Sulem, Patrick [0000-0001-7123-6123], Swertz, Morris A [0000-0002-0979-3401], Taylor, Kent D [0000-0002-2756-4370], Tzoulaki, Ioanna [0000-0002-4275-9328], Veldink, Jan H [0000-0001-5572-9657], Vitart, Veronique [0000-0002-4991-3797], Völker, Uwe [0000-0002-5689-3448], Wander, Gurpreet S [0000-0002-4596-4247], Wang, Ya Xing [0000-0003-2749-7793], Wild, Sarah [0000-0001-7824-2569], Yuan, Jian-Min [0000-0002-4620-3108], Asselbergs, Folkert W [0000-0002-1692-8669], Boehnke, Mike [0000-0002-6442-7754], Bouchard, Claude [0000-0002-0048-491X], Brody, Jennifer A [0000-0001-8509-148X], Campbell, Archie [0000-0003-0198-5078], Caulfield, Mark J [0000-0001-9295-3594], Smith, George Davey [0000-0002-1407-8314], Dorajoo, Rajkumar [0000-0001-6608-2051], Ellinghaus, David [0000-0002-4332-6110], Erdmann, Jeanette [0000-0002-4486-6231], Evangelou, Evangelos [0000-0002-5488-2999], Feenstra, Bjarke [0000-0003-1478-649X], Feitosa, Mary [0000-0002-0933-2410], Franke, Andre [0000-0003-1530-5811], Grant, Struan F A [0000-0003-2025-5302], Griffiths, Lyn R [0000-0002-6774-5475], Groop, Leif [0000-0002-0187-3263], Gudnason, Vilmundur [0000-0001-5696-0084], van der Harst, Pim [0000-0002-2713-686X], Heng, Chew-Kiat [0000-0002-7309-9473], Hicks, Andrew A [0000-0001-6320-0411], Jaddoe, Vincent W V [0000-0003-2939-0041], De Jager, Philip L [0000-0002-8057-2505], Johannesson, Magnus [0000-0001-8759-6393], Johansson, Åsa [0000-0002-2915-4498], Jonas, Jost B [0000-0003-2972-5227], Jukema, J Wouter [0000-0002-3246-8359], Kaprio, Jaakko [0000-0002-3716-2455], Laakso, Markku [0000-0002-3394-7749], van der Laan, Sander W [0000-0001-6888-1404], Lahti, Jari [0000-0002-4310-5297], Martin, Nicholas G [0000-0003-4069-8020], Medland, Sarah E [0000-0003-1382-380X], Merriman, Tony R [0000-0003-0844-8726], Metspalu, Andres [0000-0002-3718-796X], Mohlke, Karen L [0000-0001-6721-153X], Montgomery, Grant W [0000-0002-4140-8139], Munroe, Patricia B [0000-0002-4176-2947], Nyholt, Dale R [0000-0001-7159-3040], Ober, Carole [0000-0003-4626-9809], Oldehinkel, Albertine J [0000-0003-3925-3913], Palmer, Colin [0000-0002-6415-6560], Perusse, Louis [0000-0001-6440-9698], Polderman, Tinca J. C. [0000-0001-5564-301X], Porteous, David J [0000-0003-1249-6106], Rioux, John D [0000-0001-7560-8326], Rivadeneira, Fernando [0000-0001-9435-9441], Rotimi, Charles [0000-0001-5759-053X], Rotter, Jerome I [0000-0001-7191-1723], Rudan, Igor [0000-0001-6993-6884], Sattar, Naveed [0000-0002-1604-2593], Sim, Xueling [0000-0002-1233-7642], Smith, Jennifer A [0000-0002-3575-5468], Teumer, Alexander [0000-0002-8309-094X], Timpson, Nicholas J [0000-0002-7141-9189], Tuomi, Tiinamaija [0000-0002-8306-6202], Wang, Carol A [0000-0002-4301-3974], Weir, David R [0000-0002-1661-2402], Whitfield, John B [0000-0002-1103-0876], Magnusson, Patrik K. E. [0000-0002-7315-7899], Uitterlinden, André G [0000-0002-7276-3387], Loos, Ruth J. F. [0000-0002-8532-5087], Franke, Lude [0000-0002-5159-8802], Haley, Chris S [0000-0002-9811-0210], Hayward, Caroline [0000-0002-9405-9550], Walters, Robin G [0000-0002-9179-0321], Joshi, Peter K [0000-0002-6361-5059], Wilson, James F [0000-0001-5751-9178], Apollo - University of Cambridge Repository, Moore, Kristjan HS [0000-0002-9579-4362], Luan, Jian'an [0000-0003-3137-6337], Grant, Struan FA [0000-0003-2025-5302], Jaddoe, Vincent WV [0000-0003-2939-0041], Polderman, Tinca JC [0000-0001-5564-301X], Magnusson, Patrik KE [0000-0002-7315-7899], Loos, Ruth JF [0000-0002-8532-5087], Neurology, Human genetics, Amsterdam Reproduction & Development (AR&D), Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Cardiovascular Centre (CVC), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Stem Cell Aging Leukemia and Lymphoma (SALL), Institute for Molecular Medicine Finland, Department of Psychology and Logopedics, University Management, Developmental Psychology Research Group, Staff Services, Cognitive and Brain Aging, Research Programs Unit, Diabetes and Obesity Research Program, Johan Eriksson / Principal Investigator, Department of General Practice and Primary Health Care, Clinicum, University of Helsinki, Centre of Excellence in Complex Disease Genetics, Department of Public Health, Genetic Epidemiology, Helsinki Collegium for Advanced Studies, HUS Abdominal Center, Endokrinologian yksikkö, Bradford Teaching Hospitals NHS Foundation Trust [Bradford, UK] (BTHFT), University of Trieste, Université de Lausanne (UNIL), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Consiglio Nazionale delle Ricerche (CNR), Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur [Paris], Institut Pasteur [Paris], University of Oxford [Oxford], Medical Genetics, Dept. RSD and Public Health, IRCCS-Burlo Garofolo/University of Trieste, sans affiliation, Helmholtz-Zentrum München (HZM), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Institute of Cardiovascular Science, University College London, Hammersmith Hospital NHS Imperial College Healthcare-Imperial College London, Universität zu Lübeck [Lübeck], University of Ioannina Medical School, Università degli studi di Napoli Federico II-RISSC-Lab, Universität Heidelberg [Heidelberg], University of Turin, University of California-University of California, Nantes Université (NU)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), University of Helsinki-University of Helsinki, Université de Nantes (UN)-Université de Rennes 1 (UR1), Erasmus MC other, Internal Medicine, and Applied Economics
Subjects: 0301 basic medicine, 631/208/1397, Chemistry(all), Health Status, [SDV]Life Sciences [q-bio], LOCI, General Physics and Astronomy, MESH: Haplotype, MESH: Cognition, 030105 genetics & heredity, Runs of Homozygosity, Biochemistry, Consanguinity, Cognition, Inbreeding depression, 2.1 Biological and endogenous factors, Body Size, Inbreeding, Skyldleikarækt, Aetiology, Human phenotypes, lcsh:Science, MESH: Health Status, Genetics, Multidisciplinary, Inbreeding Depression, Confounding, Homozygote, RUNS, 631/208/205, 631/208/721, 3. Good health, genomic inbreeding coefficients, MESH: Risk-Taking, 631/208/730, Autozygosit, homozygosity, Erfðarannsóknir, Medical Genetics, genomic inbreeding coefficient, MESH: Homozygote, Offspring, Science, Autozygosity, Blóðsifjar, 610 Medicine & health, Biology, INBREEDING DEPRESSION, HOMOZYGOSITY, FERTILITY, QUANTIFICATION, Physics and Astronomy(all), General Biochemistry, Genetics and Molecular Biology, Article, Association, 03 medical and health sciences, Risk-Taking, 360 Social problems & social services, Journal Article, Humans, ddc:610, Allele, Alleles, Medicinsk genetik, Genetic association study, MESH: Consanguinity, MESH: Body Size, MESH: Humans, Biochemistry, Genetics and Molecular Biology(all), MESH: Alleles, Haplotype, MESH: Fertility, General Chemistry, Brain Disorders, MESH: Inbreeding Depression, 030104 developmental biology, Fertility, Haplotypes, Genetic markers, lcsh:Q, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, 3111 Biomedicine, Genetics and Molecular Biology(all)
Abstract: Publisher's version (útgefin grein)., In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44–66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding., This paper is the work of the ROHgen consortium. We thank the Sigma T2D Consortium, whose members are detailed in Supplementary Note 3. We thank the UK Biobank Resource, approved under application 19655; we acknowledge funding from the UK Medical Research Council Human Genetics Unit and MRC Doctoral Training Programme in Precision Medicine. We also thank Neil Robertson, Wellcome Trust Centre for Human Genetics, Oxford, for use of his author details management software, Authorial. Finally, we thank all the participants, researchers and funders of ROHgen cohorts. Cohort-specific acknowledgements are in Supplementary Data 2; personal acknowledgements and disclosures are in Supplementary Note 2. We thank Rachel Edwards for administrative assistance.
Published: 2019

39. Metabolomics: a search for biomarkers of visceral fat and liver fat content

Author: Dennis O. Mook-Kanamori, Sebastiaan C. Boone, Albert de Roos, Ko Willems van Dijk, Saskia le Cessie, Frits R. Rosendaal, Martin den Heijer, Renée de Mutsert, Hildo J. Lamb, Internal medicine, AGEM - Endocrinology, metabolism and nutrition, Amsterdam Movement Sciences - Rehabilitation & Development, Amsterdam Movement Sciences - Restoration and Development, and APH - Aging & Later Life
Subjects: Blood Glucose, Male, medicine.medical_specialty, Waist, Endocrinology, Diabetes and Metabolism, Metabolite, Clinical Biochemistry, Adipose tissue, 030209 endocrinology & metabolism, Intra-Abdominal Fat, Biochemistry, Body Mass Index, Plasma, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Metabolomics, Internal medicine, Liver fat, medicine, Humans, Obesity, Visceral fat, Triglycerides, Aged, Netherlands, 030304 developmental biology, 0303 health sciences, business.industry, Total body, Middle Aged, Triglyceride content, Cross-Sectional Studies, Endocrinology, Adipose Tissue, Liver, chemistry, Visceral adipose tissue, Female, Original Article, business, Biomarkers
Abstract: Intoduction Excess visceral and liver fat are known risk factors for cardiometabolic disorders. Metabolomics might allow for easier quantification of these ectopic fat depots, instead of using invasive and costly tools such as MRI or approximations such as waist circumference. Objective We explored the potential use of plasma metabolites as biomarkers of visceral adipose tissue (VAT) and hepatic triglyceride content (HTGC). Methods We performed a cross-sectional analysis of a subset of the Netherlands Epidemiology of Obesity study. Plasma metabolite profiles were determined using the Biocrates AbsoluteIDQ p150 kit in 176 individuals with normal fasting plasma glucose. VAT was assessed with magnetic resonance imaging and HTGC with proton-MR spectroscopy. We used linear regression to investigate the associations of 190 metabolite variables with VAT and HTGC. Results After adjustment for age, sex, total body fat, currently used approximations of visceral and liver fat, and multiple testing, three metabolite ratios were associated with VAT. The strongest association was the lysophosphatidylcholines to total phosphatidylcholines (PCs) ratio [− 14.1 (95% CI − 21.7; − 6.6) cm2 VAT per SD of metabolite concentration]. Four individual metabolites were associated with HTGC, especially the diacyl PCs of which C32:1 was the strongest at a 1.31 (95% CI 1.14; 1.51) fold increased HTGC per SD of metabolite concentration. Conclusion Metabolomics may be a useful tool to identify biomarkers of visceral fat and liver fat content that have added diagnostic value over current approximations. Replication studies are required to validate the diagnostic value of these metabolites.
Published: 2019

40. Association of Birth Weight With Type 2 Diabetes and Glycemic Traits: A Mendelian Randomization Study

Author: Kari E. North, Cécile Lecoeur, Katja Pahkala, Meng Gao, Kim Overvad, Cyrus Cooper, Luis A. Moreno, Keith M. Godfrey, Wanting Zhao, Sing Hui Lim, Emily Sonestedt, Albert Hofman, Karen A. Jameson, Zhe Fang, Frits R. Rosendaal, Yih Chung Tham, Jean-Paul Langhendries, Janine F. Felix, Tao Huang, Frédéric Gottrand, Woon-Puay Koh, Torben Hansen, Lu Qi, Hans Bisgaard, Jorma Viikari, Jianjun Liu, Marju Orho-Melander, Meian He, Beverley Balkau, Xueling Sim, Xiang Li, Peter Rzehak, Oluf Pedersen, Philippe Froguel, Donna K. Arnett, Oscar Coltell, Ulrika Ericson, George Davey Smith, Seang-Mei Saw, Joachim Thiery, Joaquin Escribano, Elvira Verduci, Tien Yin Wong, Nadia R. Fink, Yujie Wang, Eirini Marouli, Tiange Wang, Yan Zheng, Chao-Qiang Lai, Aline Meirhaeghe, Colin Boreham, Daniel I. Chasman, Chiea Chuen Khor, Frédéric Fumeron, Graciela E. Delgado, Katherine L. Tucker, Dennis O. Mook-Kanamori, Dariush Mozaffarian, Tuomas O. Kilpeläinen, Jin-Fang Chai, Thorkild I. A. Sørensen, André G. Uitterlinden, Oscar H. Franco, Trudy Voortman, Jian-Min Yuan, Frank J. A. van Rooij, Vincent W. V. Jaddoe, Fernando Rivadeneira, Rebecca K. Vinding, Astrid Sevelsted, Masato Akiyama, Hazel Inskip, Dolores Corella, Jean Dallongeville, Rajkumar Dorajoo, Jose M. Ordovas, Tao Zhang, Diana van Heemst, Blanche Lim, Nanette R. Lee, Michiaki Kubo, Preeti Gupta, Caizheng Yu, Mariaelisa Graff, Peter Rossing, Carol A. Wang, Tarunveer S. Ahluwalia, Jorge E. Chavarro, Elaine M. Dennison, Yik Ying Teo, Terho Lehtimäki, Alexis C. Frazier-Wood, Christina Ellervik, Chris Power, Marie Standl, Christina-Alexandra Schulz, David A. Mackey, Anne Tjønneland, Panagiotis Deloukas, Ramon Estruch, George Dedoussis, Niina Pitkänen, Paul M. Ridker, Olli T. Raitakari, Charumathi Sabanayagam, Markus Loeffler, Rob M. van Dam, Raymond Noordam, Yoichiro Kamatani, Winfried März, Markus Scholz, Harri Niinikoski, Dariusz Gruszfeld, Tangchun Wu, Elina Hyppönen, Rozenn N. Lemaitre, Marcus E. Kleber, Berthold Koletzko, E-Shyong Tai, Veit Grote, Klaus Bønnelykke, Ching-Yu Cheng, Carla M. T. Tiesler, Karen L. Mohlke, E. Thiering, Renée de Mutsert, Ang Zhou, Mika Kähönen, Luc Djoussé, Philippe Amouyel, Sarah Crozier, Ralph Burkhardt, Yuan Shi, Bruce M. Psaty, Huang, Tao, Wang, Tiange, Zheng, Yan, Ellervik, Christina, Zhou, Ang, Hyppönen, Elina, Qi, Lu, BIRTH-GENE (BIG) Study Working Group, Department of Technology and Operations Management, Epidemiology, Erasmus MC other, and Pediatrics
Subjects: Blood Glucose, Male, Type 2 diabetes, 0302 clinical medicine, Odds Ratio, Birth Weight, Insulin, 030212 general & internal medicine, Original Investigation, 0303 health sciences, Asia, Eastern, Mendelian Randomization Analysis, General Medicine, Middle Aged, 16. Peace & justice, 3. Good health, Online Only, Diabetes and Endocrinology, Female, type 2 diabetes, Adult, medicine.medical_specialty, Diabetes risk, Adolescent, Birth weight, Polymorphism, Single Nucleotide, White People, 03 medical and health sciences, Young Adult, SDG 3 - Good Health and Well-being, Asian People, Diabetes mellitus, Internal medicine, Mendelian randomization, medicine, Humans, 030304 developmental biology, Glycemic, Aged, Glycated Hemoglobin, business.industry, Research, Infant, Newborn, birth weight, Genetic Variation, Odds ratio, medicine.disease, Diabetes Mellitus, Type 2, mendelian randomization study, business
Abstract: Key Points Question Is birth weight associated with type 2 diabetes and glycemic traits? Findings This mendelian randomization study found that a 1-SD decrease in birth weight due to the genetic risk score was associated with a higher risk of type 2 diabetes among European and East Asian populations. In addition, a 1-SD decrease in birth weight was associated with a 0.189-SD increase in fasting glucose concentration, but not with fasting insulin, 2-hour glucose, or hemoglobin A1c level. Meaning A genetic predisposition to lower birth weight was associated with an increased risk of type 2 diabetes and increased fasting glucose, suggesting potential mechanisms through which perturbation of the antenatal and early-life environment affect predisposition to diabetes in later life., This mendelian randomization study examines the association of birth weight with type 2 diabetes and glycemic traits., Importance Observational studies have shown associations of birth weight with type 2 diabetes (T2D) and glycemic traits, but it remains unclear whether these associations represent causal associations. Objective To test the association of birth weight with T2D and glycemic traits using a mendelian randomization analysis. Design, Setting, and Participants This mendelian randomization study used a genetic risk score for birth weight that was constructed with 7 genome-wide significant single-nucleotide polymorphisms. The associations of this score with birth weight and T2D were tested in a mendelian randomization analysis using study-level data. The association of birth weight with T2D was tested using both study-level data (7 single-nucleotide polymorphisms were used as an instrumental variable) and summary-level data from the consortia (43 single-nucleotide polymorphisms were used as an instrumental variable). Data from 180 056 participants from 49 studies were included. Main Outcomes and Measures Type 2 diabetes and glycemic traits. Results This mendelian randomization analysis included 49 studies with 41 155 patients with T2D and 80 008 control participants from study-level data and 34 840 patients with T2D and 114 981 control participants from summary-level data. Study-level data showed that a 1-SD decrease in birth weight due to the genetic risk score was associated with higher risk of T2D among all participants (odds ratio [OR], 2.10; 95% CI, 1.69-2.61; P = 4.03 × 10−5), among European participants (OR, 1.96; 95% CI, 1.42-2.71; P = .04), and among East Asian participants (OR, 1.39; 95% CI, 1.18-1.62; P = .04). Similar results were observed from summary-level analyses. In addition, each 1-SD lower birth weight was associated with 0.189 SD higher fasting glucose concentration (β = 0.189; SE = 0.060; P = .002), but not with fasting insulin, 2-hour glucose, or hemoglobin A1c concentration. Conclusions and Relevance In this study, a genetic predisposition to lower birth weight was associated with increased risk of T2D and higher fasting glucose concentration, suggesting genetic effects on retarded fetal growth and increased diabetes risk that either are independent of each other or operate through alterations of integrated biological mechanisms.
Published: 2019

41. Potential Interplay between Dietary Saturated Fats and Genetic Variants of the NLRP3 Inflammasome to Modulate Insulin Resistance and Diabetes Risk: Insights from a Meta-Analysis of 19 005 Individuals

Author: Ching-Ti Liu, Leanne M Murphy, Fernando Rivadeneira, Peadar Ó Gaora, Jose M. Ordovas, George Dedoussis, Renée de Mutsert, Abbas Dehghan, Aoife M. Murphy, Caren E. Smith, Jack L. Follis, Raymond Noordam, Terho Lehtimäki, André G. Uitterlinden, Rozenn N. Lemaitre, Panagiotis Deloukas, Mika Kähönen, Dennis O. Mook-Kanamori, Jaeyoung Hong, Vera Mikkilä, Oscar H. Franco, Trudy Voortman, Kris Richardson, Olli T. Raitakari, Mohammad Arfan Ikram, Maria Hughes, James B. Meigs, Eirini Marouli, Toshiko Tanaka, Helen M. Roche, Josée Dupuis, Science Foundation Ireland, Epidemiology, and Internal Medicine
Subjects: 0301 basic medicine, medicine.medical_specialty, Diabetes risk, Inflammasomes, medicine.medical_treatment, Single-nucleotide polymorphism, Type 2 diabetes, Biology, Pyrin domain, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Cohorts for Heart and Ageing Research in Genomic Epidemiology consortium, Insulin resistance, SDG 3 - Good Health and Well-being, Internal medicine, insulin resistance, NLR Family, Pyrin Domain-Containing 3 Protein, medicine, Humans, Allele, saturated fats, 030109 nutrition & dietetics, Insulin, Genetic Variation, food and beverages, Inflammasome, medicine.disease, Dietary Fats, Genome-wide interaction studies, 030104 developmental biology, Endocrinology, Saturated fats, Diabetes Mellitus, Type 2, meta-analyses, Meta-analyses, NLRP3 inflammasomes, genome-wide interaction studies, Food Science, Biotechnology, medicine.drug
Abstract: Scope Insulin resistance (IR) and inflammation are hallmarks of type 2 diabetes (T2D). The nod-like receptor pyrin domain containing-3 (NLRP3) inflammasome is a metabolic sensor activated by saturated fatty acids (SFA) initiating IL-1 beta inflammation and IR. Interactions between SFA intake and NLRP3-related genetic variants may alter T2D risk factors. Methods Meta-analyses of six Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 19 005) tested interactions between SFA and NLRP3-related single-nucleotide polymorphisms (SNPs) and modulation of fasting insulin, fasting glucose, and homeostasis model assessment of insulin resistance. Results SFA interacted with rs12143966, wherein each 1% increase in SFA intake increased insulin by 0.0063 IU mL(-1) (SE +/- 0.002, p = 0.001) per each major (G) allele copy. rs4925663, interacted with SFA (beta +/- SE = -0.0058 +/- 0.002, p = 0.004) to increase insulin by 0.0058 IU mL(-1), per additional copy of the major (C) allele. Both associations are close to the significance threshold (p < 0.0001). rs4925663 causes a missense mutation affecting NLRP3 expression. Conclusion Two NLRP3-related SNPs showed potential interaction with SFA to modulate fasting insulin. Greater dietary SFA intake accentuates T2D risk, which, subject to functional validation, may be further elaborated depending on NLRP3-related genetic variants.
Published: 2019

42. Multi-ancestry GWAS of the electrocardiographic PR interval identifies 210 loci underlying cardiac conduction

Author: Lorenz Risch, Igor Rudan, Hilma Holm, Christopher P. Nelson, Jan A. Kors, Stefanie Aeschbacher, Stefan Kääb, Peter W. Macfarlane, Lars Lind, Amanda A. Seyerle, Ozren Polasek, Daniel F. Gudbjartsson, Xiuqing Guo, Nilesh J. Samani, Bruce M. Psaty, Rosa B. Thorolfsdottir, Elsayed Z. Soliman, Yong Qian, Mary L. Biggs, Antti Jula, Vilmundur Gudnason, Paul L. Huang, Tamara B. Harris, Gianfranco Sinagra, Luisa Foco, Anubha Mahajan, Mika Kähönen, Lu-Chen Weng, Borbala Mifsud, Stefan van Duijvenboden, Terho Lehtimäki, Jennifer A. Brody, Paolo Gasparini, Kathleen A. Ryan, Marten E. van den Berg, James J. Cranley, Eric Boerwinkle, Cathy C. Laurie, Annette Peters, Joshua C. Bis, Raymond Noordam, Andrew P. Morris, Johan Sundström, Lenore J. Launer, Stefan Weiss, Rebecca D. Jackson, Alison D. Murray, Jeffrey R. O'Connell, Aki S. Havulinna, Dennis O. Mook-Kanamori, Sheila Ulivi, Renée de Mutsert, Eric A. Whitsel, Adrienne M. Stilp, James P. Cook, Nona Sotoodehnia, Antonio Luiz Pinho Ribeiro, Seung Hoan Choi, Mark J. Caulfield, Sébastien Thériault, Henry J. Lin, Dan M. Roden, J. Wouter Jukema, James F. Wilson, Veikko Salomaa, Honghuang Lin, Andrew A. Hicks, Christy L. Avery, Nina Mononen, Dan E. Arking, Ruth J. F. Loos, Yalda Jamshidi, André G. Uitterlinden, Nina Hutri-Kähönen, Andrew Tinker, Gudmar Thorleifsson, Daniel Levy, Martina Müller-Nurasyid, Alexander P. Reiner, Bruno H. Stricker, Caroline Hayward, Yordi J. van de Vegte, Ioanna Ntalla, Tim D. Spector, Niek Verweij, Michael R. Barnes, Martin Gögele, Nathan R. Tucker, Arie C. Maan, Eduardo Tarazona-Santos, Katri Sääksjärvi, Maria Pina Concas, Pim van der Harst, Georg Ehret, Cecilia M. Lindgren, David Conen, Cornelia M. van Duijn, Muhammad B. Riaz, Leo-Pekka Lyytikäinen, Amelia W. Hall, Peter P. Pramstaller, Maria Fernanda Lima-Costa, Vilmantas Giedraitis, Emelia J. Benjamin, M. Fabiola Del Greco, Thomas Meitinger, Erwin P. Bottinger, Francesco Cucca, Aaron Isaacs, Carolina Roselli, James H. Cartwright, Massimo Mangino, Adolfo Correa, Patrick Sulem, Thibaud Boutin, Michiel Rienstra, Stephan B. Felix, Julia Ramirez, Kathleen F. Kerr, Jonathan Marten, David J. Porteous, Kent D. Taylor, Patrick T. Ellinor, Michele Orini, Susan R. Heckbert, Olli T. Raitakari, Girish N. Nadkarni, Edward G. Lakatta, Anna F. Dominiczak, Jie Yao, Erik Ingelsson, Christopher Newton-Cheh, Katharina Schramm, Jerome I. Rotter, Michael J. Cutler, Pashupati P. Mishra, Diane Fatkin, Marcus Dörr, Ulrike Peters, Solmaz Assa, Christian Fuchsberger, M. Abdullah Said, Catriona L. K. Barnes, Peter K. Joshi, M. Yldau van der Ende, Alvaro Alonso, James G. Wilson, Jun Ding, Kathryn L. Lunetta, Kjell Nikus, Helen R. Warren, Charles Kooperberg, Moritz F. Sinner, Sandosh Padmanabhan, Patricia B. Munroe, Jeffrey Haessler, Albert V. Smith, Alan R. Shuldiner, Morten S. Olesen, Konstantin Strauch, Steven A. Lubitz, J. Gustav Smith, Renan P. Souza, Michael Preuss, Kirill V. Tarasov, M. Benjamin Shoemaker, Barry London, Melanie Waldenberger, Cristian Pattaro, David O. Arnar, Gardar Sveinbjornsson, Alessandro De Grandi, Ian Ford, Kenneth Rice, Mark Chaffin, Kari Stefansson, Hao Mei, Uwe Völker, Blair H. Smith, Nathalia M. Araujo, Harry Campbell, Pier D. Lambiase, Stephanie M. Gogarten, May E. Montasser, Unnur Thorsteinsdottir, Ivana Kolcic, and Stella Trompet
Subjects: 0303 health sciences, medicine.medical_specialty, education.field_of_study, business.industry, Population, Cardiomyopathy, Atrial fibrillation, Genome-wide association study, Disease, 030204 cardiovascular system & hematology, medicine.disease, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Endophenotype, Cardiac conduction, medicine, Cardiology, PR interval, business, education, 030304 developmental biology
Abstract: The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality1,2. We performed multi-ancestry (N=293,051) and European only (N=271,570) genome-wide association (GWAS) meta-analyses for the PR interval, discovering 210 loci of which 149 are novel. Variants at all loci nearly doubled the percentage of heritability explained, from 33.5% to 62.6%. We observed enrichment for genes involved in cardiac muscle development/contraction and the cytoskeleton highlighting key regulation processes for atrioventricular conduction. Additionally, 19 novel loci harbour genes underlying inherited monogenic heart diseases suggesting the role of these genes in cardiovascular pathology in the general population. We showed that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease risk, including distal conduction disease, AF, atrioventricular pre-excitation, non-ischemic cardiomyopathy, and coronary heart disease. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.
Published: 2019

43. The Association between Habitual Sleep Duration and Sleep Quality with Glycemic Traits: Assessment by Cross-Sectional and Mendelian Randomization Analyses

Author: Diana van Heemst, Esther Donga, Frits R. Rosendaal, Nienke R. Biermasz, Gerard J. Blauw, Maxime M Bos, Patrick C.N. Rensen, Raymond Noordam, and Renée de Mutsert
Subjects: medicine.medical_specialty, lcsh:Medicine, 030209 endocrinology & metabolism, Article, 03 medical and health sciences, 0302 clinical medicine, Insulin resistance, Diabetes mellitus, Internal medicine, insulin resistance, Mendelian randomization, medicine, sleep, Glycemic, diabetes, business.industry, Confounding, lcsh:R, Sleep apnea, General Medicine, medicine.disease, Sleep in non-human animals, Confidence interval, 3. Good health, mendelian randomization, epidemiology, business, 030217 neurology & neurosurgery
Abstract: Evidence on whether habitual sleep duration and sleep quality are associated with increased insulin resistance is inconsistent. Here, we investigated the associations between different measures of habitual sleep with glycemic traits through cross-sectional and Mendelian randomization (MR) analyses. We assessed the associations of sleep duration and sleep quality with glycemic traits using multivariable linear regression models adjusted for potential confounders in 4672 middle-aged (45&ndash, 65 years, 48% men) nondiabetic participants of the Netherlands Epidemiology of Obesity (NEO) study. Genetic variants for total, short, and long sleep duration were used as instrumental variables in MR analyses using summary-level data of glycemic traits in nondiabetic individuals (MAGIC, n = 58,074). In cross-sectional analyses, shortest sleepers (median 5.0 h of sleep per night) had 14.5% (95% confidence interval (CI): 2.0, 28.6%) higher fasting insulin level and 16.3% (95% CI: 2.7, 31.7%) higher HOMA-&beta, Bad sleep quality was associated with higher insulin resistance (e.g., 14.3% (95% CI: 4.7, 24.9%) higher HOMA-IR). All these associations disappeared after adjustment for BMI and the risk of sleep apnea. MR analyses did not indicate a causal association between total, short or long sleep duration and glycemic traits. Therefore, our used measures of habitual sleep duration and sleep quality are unlikely to directly associate with insulin resistance.
Published: 2019
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44. A multi-ancestry genome-wide study incorporating gene–smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure

Author: Bamidele O. Tayo, RJ Waken, Mario Sims, Diane M. Becker, Tõnu Esko, Yingchang Lu, Pamela J. Schreiner, Antonietta Robino, Anne U. Jackson, H. Janaka de Silva, Peter J. van der Most, Archie Campbell, Ozren Polasek, Salman M. Tajuddin, Jing Hua Zhao, Barbara V. Howard, Saima Afaq, Vilmundur Gudnason, Lynda M. Rose, Francis S. Collins, Massimiliano Cocca, Ruth J. F. Loos, Yii-Der Ida Chen, W. James Gauderman, Jaspal S. Kooner, Lawrence F. Bielak, Ulrich Broeckel, Anuradhani Kasturiratne, Melissa A. Richard, Tomohiro Katsuya, Nicola D. Kerrison, Tin Aung, Lisa de las Fuentes, Lynne E. Wagenknecht, Oscar H. Franco, Yongmei Liu, Eric Boerwinkle, Nana Matoba, Saskia P. Hagenaars, Rob M. van Dam, Tibor V. Varga, Nilesh J. Samani, Tangchun Wu, Thomas H. Mosley, Caroline Hayward, Joseph H. Lee, Frida Renström, Tamara B. Harris, Alena Stančáková, Adesola Ogunniyi, Wen Bin Wei, Lenore J. Launer, Marcus Dörr, Xiuqing Guo, Jennifer A. Smith, Terho Lehtimäki, Dan E. Arking, Fang-Chi Hsu, Karin Leander, Martin Farrall, Konstantin Strauch, Albert V. Smith, Richard S. Cooper, Chiea Chuen Khor, Changwei Li, James E. Hixson, Sami Heikkinen, David R. Weir, Pirjo Komulainen, Renée de Mutsert, Raymond Noordam, Ubaydah Nasri, Paul M. Ridker, C. Charles Gu, Tamuno Alfred, Jerome I. Rotter, Nora Franceschini, Nita G. Forouhi, Lihua Wang, Alanna C. Morrison, Jian-Min Yuan, Ching-Yu Cheng, Peter S. Braund, Paul Elliott, Gregory P. Wilson, Jianjun Liu, Xiaofeng Zhu, Markku Laakso, Christian Gieger, Yukihide Momozawa, Rainer Rettig, Carsten Oliver Schmidt, Amy R. Bentley, Wei Zhao, Ioanna Ntalla, Kenneth Rice, Yoichiro Kamatani, Andres Metspalu, Helen R. Warren, Yechiel Friedlander, Susan Redline, Kurt Lohman, Cornelia M. van Duijn, Aravinda Chakravarti, Traci M. Bartz, Sarah E. Harris, Yih Chung Tham, He Gao, Mike A. Nalls, Mathilde Boissel, Donna K. Arnett, Harold Snieder, James S. Pankow, Babatunde L. Salako, Laura J. Bierut, Tin Louie, Albertine J. Oldehinkel, Xueling Sim, Thomas Meitinger, Maris Alver, Claudia Langenberg, Stephen B. Kritchevsky, Norihiro Kato, Evangelos Evangelou, Philippe Froguel, Alexandre C. Pereira, Michael R. Brown, Karen Schwander, Charles Kooperberg, Blair H. Smith, Annette Peters, Fernando Pires Hartwig, Yanhua Zhou, Jie Yao, Alisa K. Manning, Keng-Hung Lin, Dennis O. Mook-Kanamori, Ervin R. Fox, Tuomo Rankinen, Timo A. Lakka, Charles N. Rotimi, Nicholette D. Palmer, Jiang He, Nicholas J. Wareham, Jingmin Liu, Yun Ju Sung, Cathy C. Laurie, Donald W. Bowden, Yong-Bing Xiang, Lisa R. Yanek, B. Kuhnel, Nancy L. Pedersen, Yajuan Wang, Ananda R. Wickremasinghe, Jonathan Marten, Yi-Jen Hung, Dabeeru C. Rao, Bernardo L. Horta, Joel D. Kaufman, Barry I. Freedman, Chuan Gao, Olli T. Raitakari, Reedik Mägi, Solomon K. Musani, Albert Hofman, Wanqing Wen, Heming Wang, Xiao-Ou Shu, Y Liu, Mark J. Caulfield, Meian He, Daniel I. Chasman, Carl D. Langefeld, Charumathi Sabanayagam, Bruce M. Psaty, Jasmin Divers, R. Graham Barr, Chew-Kiat Heng, Stella Aslibekyan, John M. Starr, Stefan Weiss, Anuj Goel, Tuomas O. Kilpeläinen, Terrence Forrester, Mary F. Feitosa, Jost B. Jonas, Kae-Woei Liang, Colleen M. Sitlani, Daniel Levy, Marie Loh, Qing Duan, Aldi T. Kraja, Tien Yin Wong, Myriam Fornage, Andrea R. V. R. Horimoto, Michele K. Evans, David J. Porteous, Dina Vojinovic, Hua Tang, Michael A. Province, Ching-Ti Liu, Rainer Rauramaa, William R. Scott, Cora E. Lewis, Charles B. Eaton, Sharon L.R. Kardia, Michael Boehnke, James Scott, Colin A McKenzie, Jin-Fang Chai, Woon-Puay Koh, Yucheng Jia, Claude Bouchard, Peter S. Sever, Koichi Matsuda, Najaf Amin, Ulf de Faire, Walter Palmas, André G. Uitterlinden, Thomas T. Perls, Erin B. Ware, Wayne Huey-Herng Sheu, Michiaki Kubo, Ya Xing Wang, Hugh Watkins, Steven C. Hunt, Weihua Zhang, Johanna Kuusisto, Lili Milani, Rajkumar Dorajoo, Georg Ehret, L. Adrienne Cupples, Franco Giulianini, Zoltán Kutalik, Jose E Krieger, Kevin Sandow, Bruna Gigante, Alexander P. Reiner, Preeti Gupta, Heikki A. Koistinen, Treva Rice, Patricia B. Munroe, Wen-Jane Lee, Jennifer A. Brody, Paolo Gasparini, Paul W. Franks, Yik Ying Teo, Leo-Pekka Lyytikäinen, Thomas W. Winkler, Patricia A. Peyser, Ian J. Deary, Jessica D. Faul, Sing Hui Lim, Fumihiko Takeuchi, Xu Chen, Brian E. Cade, Patrik K. E. Magnusson, John C. Chambers, Tamar Sofer, E. Shyong Tai, Candace M Kammerer, Mary K. Wojczynski, Pim van der Harst, Marzyeh Amini, Jennifer G. Robinson, Erwin P. Bottinger, Alan B. Zonderman, Benjamin Lehne, M. Waldenberger, Jeffrey R. O'Connell, Hugues Aschard, Ilaria Gandin, Kent D. Taylor, Igor Rudan, Christopher P. Nelson, John M. C. Connell, Jian'an Luan, Mickaël Canouil, Robert A. Scott, Yize Li, Marguerite R. Irvin, Sung, Yun Ju, de Las Fuentes, Lisa, Winkler, Thomas W, Chasman, Daniel I, Bentley, Amy R, Kraja, Aldi T, Ntalla, Ioanna, Warren, Helen R, Guo, Xiuqing, Schwander, Karen, Manning, Alisa K, Brown, Michael R, Aschard, Hugue, Feitosa, Mary F, Franceschini, Nora, Lu, Yingchang, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Marten, Jonathan, Musani, Solomon K, Kilpeläinen, Tuomas O, Richard, Melissa A, Aslibekyan, Stella, Bartz, Traci M, Dorajoo, Rajkumar, Li, Changwei, Liu, Yongmei, Rankinen, Tuomo, Smith, Albert Vernon, Tajuddin, Salman M, Tayo, Bamidele O, Zhao, Wei, Zhou, Yanhua, Matoba, Nana, Sofer, Tamar, Alver, Mari, Amini, Marzyeh, Boissel, Mathilde, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Gandin, Ilaria, Gao, Chuan, Giulianini, Franco, Goel, Anuj, Harris, Sarah E, Hartwig, Fernando P, He, Meian, Horimoto, Andrea R V R, Hsu, Fang-Chi, Jackson, Anne U, Kammerer, Candace M, Kasturiratne, Anuradhani, Komulainen, Pirjo, Kühnel, Brigitte, Leander, Karin, Lee, Wen-Jane, Lin, Keng-Hung, Luan, Jian'An, Lyytikäinen, Leo-Pekka, Mckenzie, Colin A, Nelson, Christopher P, Noordam, Raymond, Scott, Robert A, Sheu, Wayne H H, Stančáková, Alena, Takeuchi, Fumihiko, van der Most, Peter J, Varga, Tibor V, Waken, Robert J, Wang, Heming, Wang, Yajuan, Ware, Erin B, Weiss, Stefan, Wen, Wanqing, Yanek, Lisa R, Zhang, Weihua, Zhao, Jing Hua, Afaq, Saima, Alfred, Tamuno, Amin, Najaf, Arking, Dan E, Aung, Tin, Barr, R Graham, Bielak, Lawrence F, Boerwinkle, Eric, Bottinger, Erwin P, Braund, Peter S, Brody, Jennifer A, Broeckel, Ulrich, Cade, Brian, Campbell, Archie, Canouil, Mickaël, Chakravarti, Aravinda, Cocca, Massimiliano, Collins, Francis S, Connell, John M, de Mutsert, Renée, de Silva, H Janaka, Dörr, Marcu, Duan, Qing, Eaton, Charles B, Ehret, Georg, Evangelou, Evangelo, Faul, Jessica D, Forouhi, Nita G, Franco, Oscar H, Friedlander, Yechiel, Gao, He, Gigante, Bruna, Gu, C Charle, Gupta, Preeti, Hagenaars, Saskia P, Harris, Tamara B, He, Jiang, Heikkinen, Sami, Heng, Chew-Kiat, Hofman, Albert, Howard, Barbara V, Hunt, Steven C, Irvin, Marguerite R, Jia, Yucheng, Katsuya, Tomohiro, Kaufman, Joel, Kerrison, Nicola D, Khor, Chiea Chuen, Koh, Woon-Puay, Koistinen, Heikki A, Kooperberg, Charles B, Krieger, Jose E, Kubo, Michiaki, Kutalik, Zoltan, Kuusisto, Johanna, Lakka, Timo A, Langefeld, Carl D, Langenberg, Claudia, Launer, Lenore J, Lee, Joseph H, Lehne, Benjamin, Levy, Daniel, Lewis, Cora E, Li, Yize, Lim, Sing Hui, Liu, Ching-Ti, Liu, Jianjun, Liu, Jingmin, Liu, Yeheng, Loh, Marie, Lohman, Kurt K, Louie, Tin, Mägi, Reedik, Matsuda, Koichi, Meitinger, Thoma, Metspalu, Andre, Milani, Lili, Momozawa, Yukihide, Mosley, Thomas H, Nalls, Mike A, Nasri, Ubaydah, O'Connell, Jeff R, Ogunniyi, Adesola, Palmas, Walter R, Palmer, Nicholette D, Pankow, James S, Pedersen, Nancy L, Peters, Annette, Peyser, Patricia A, Polasek, Ozren, Porteous, David, Raitakari, Olli T, Renström, Frida, Rice, Treva K, Ridker, Paul M, Robino, Antonietta, Robinson, Jennifer G, Rose, Lynda M, Rudan, Igor, Sabanayagam, Charumathi, Salako, Babatunde L, Sandow, Kevin, Schmidt, Carsten O, Schreiner, Pamela J, Scott, William R, Sever, Peter, Sims, Mario, Sitlani, Colleen M, Smith, Blair H, Smith, Jennifer A, Snieder, Harold, Starr, John M, Strauch, Konstantin, Tang, Hua, Taylor, Kent D, Teo, Yik Ying, Tham, Yih Chung, Uitterlinden, André G, Waldenberger, Melanie, Wang, Lihua, Wang, Ya Xing, Wei, Wen Bin, Wilson, Gregory, Wojczynski, Mary K, Xiang, Yong-Bing, Yao, Jie, Yuan, Jian-Min, Zonderman, Alan B, Becker, Diane M, Boehnke, Michael, Bowden, Donald W, Chambers, John C, Chen, Yii-Der Ida, Weir, David R, de Faire, Ulf, Deary, Ian J, Esko, Tõnu, Farrall, Martin, Forrester, Terrence, Freedman, Barry I, Froguel, Philippe, Gasparini, Paolo, Gieger, Christian, Horta, Bernardo Lessa, Hung, Yi-Jen, Jonas, Jost Bruno, Kato, Norihiro, Kooner, Jaspal S, Laakso, Markku, Lehtimäki, Terho, Liang, Kae-Woei, Magnusson, Patrik K E, Oldehinkel, Albertine J, Pereira, Alexandre C, Perls, Thoma, Rauramaa, Rainer, Redline, Susan, Rettig, Rainer, Samani, Nilesh J, Scott, Jame, Shu, Xiao-Ou, van der Harst, Pim, Wagenknecht, Lynne E, Wareham, Nicholas J, Watkins, Hugh, Wickremasinghe, Ananda R, Wu, Tangchun, Kamatani, Yoichiro, Laurie, Cathy C, Bouchard, Claude, Cooper, Richard S, Evans, Michele K, Gudnason, Vilmundur, Hixson, Jame, Kardia, Sharon L R, Kritchevsky, Stephen B, Psaty, Bruce M, van Dam, Rob M, Arnett, Donna K, Mook-Kanamori, Dennis O, Fornage, Myriam, Fox, Ervin R, Hayward, Caroline, van Duijn, Cornelia M, Tai, E Shyong, Wong, Tien Yin, Loos, Ruth J F, Reiner, Alex P, Rotimi, Charles N, Bierut, Laura J, Zhu, Xiaofeng, Cupples, L Adrienne, Province, Michael A, Rotter, Jerome I, Franks, Paul W, Rice, Kenneth, Elliott, Paul, Caulfield, Mark J, Gauderman, W Jame, Munroe, Patricia B, Rao, Dabeeru C, Morrison, Alanna C, Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), Brigham and Women's Hospital [Boston], Queen Mary University of London (QMUL), Harbor UCLA Medical Center [Torrance, Ca.], Département de Biologie Computationnelle - Department of Computational Biology, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Harvard School of Public Health, European Genomic Institute for Diabetes - FR 3508 (EGID), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), The University of Texas Health Science Center at Houston (UTHealth), U.S. National Heart, Lung, and Blood Institute (NHLBI) (K25HL121091 to Y.J.S.), National Institutes of Health (R01HL118305), We thank anonymous reviewers for critical reading and providing constructive and insightful comments, which substantially improved the article. This project, like several other projects, was carried out as part of the CHARGE Gene–Lifestyle Interactions Working Group., Conflict of Interest statement. The authors declare no competing financial interests except for the following: B.M.P. serves on the Data and Safety Monitoring Board of a clinical trial funded by the manufacturer (Zoll LifeCor) and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson, O.H.F. received grants from Metagenics (on women’s health and epigenetics) and from Nestle (on child health), L.J.B. is listed as an inventor on Issued U.S. Patent 8,080,371,‘Markers for Addiction’ covering the use of certain SNPs in determining the diagnosis, prognosis and treatment of addiction, P.S. has received research awards from Pfizer Inc, J.B.J. is a consultant for Mundipharma Co. (Cambridge, UK), Patent holder with Biocompatibles UK Ltd (Franham, Surrey, UK) (title: treatment of eye diseases using encapsulated cells encoding and secreting neuroprotective factor and/or anti-angiogenic factor, Patent number: 20120263794) and Patent application with University of Heidelberg (Heidelberg, Germany) (title: agents for use in the therapeutic or prophylactic treatment of myopia or hyperopia, Europäische Patentanmeldung 15000771.4), P.W.F. has been a paid consultant for Eli Lilly and Sanofi Aventis and has received research support from several pharmaceutical companies as part of a European Union Innovative Medicines Initiative project, M.A.N.'s participation is supported by a consulting contract between Data Tecnica International and the National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, M.A.N. also consults for Illumina Inc, the Michael J. Fox Foundation and University of California Healthcare among others, and M.J. C. is chief scientist for Genomics England, a UK government company., Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Institut Européen de Génomique du Diabète - European Genomic Institute for Diabetes - FR 3508 (EGID), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Epidemiology, Internal Medicine, Life Course Epidemiology (LCE), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Cardiovascular Centre (CVC), University Management, Department of Medicine, University of Helsinki, HUS Abdominal Center, Endokrinologian yksikkö, Marten, Jonathan [0000-0001-6916-2014], Luan, Jian'an [0000-0003-3137-6337], Zhao, Jing Hua [0000-0003-4930-3582], Forouhi, Nita [0000-0002-5041-248X], Langenberg, Claudia [0000-0002-5017-7344], Wareham, Nicholas [0000-0003-1422-2993], Apollo - University of Cambridge Repository, and Medical Research Council (MRC)
Subjects: Male, Receptors, Vasopressin, multi-ancestry, Genome-wide association study, Blood Pressure, HYDROCARBON RECEPTOR AHR, 030204 cardiovascular system & hematology, Antiporters, gene-smoking interaction, 0302 clinical medicine, Polymorphism (computer science), genome-wide study, Ethnicity, OXIDATIVE STRESS, Association Studies Article, 11 Medical and Health Sciences, Genetics (clinical), Genetics & Heredity, Genetics, ddc:616, Aged, 80 and over, 0303 health sciences, [STAT.AP]Statistics [stat]/Applications [stat.AP], DEPENDENT HYPERTENSION, CARDIOVASCULAR RISK, Smoking, 1184 Genetics, developmental biology, physiology, General Medicine, ASSOCIATION, Middle Aged, Caspase 9, 3. Good health, Pulse pressure, ENVIRONMENT INTERACTION, Sulfate Transporters, T-CADHERIN, Hypertension, Female, Life Sciences & Biomedicine, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Adult, Biochemistry & Molecular Biology, Mean arterial pressure, Adolescent, Diastole, Biology, elevated blood pressure, gene-smoking interactions, 03 medical and health sciences, Young Adult, Insulin resistance, Lifelines Cohort Study, medicine, Humans, Arterial Pressure, Molecular Biology, METAANALYSIS, 030304 developmental biology, Aged, Science & Technology, Polymorphism, Genetic, Tumor Suppressor Proteins, Racial Groups, Membrane Proteins, 06 Biological Sciences, SYSTOLIC BLOOD-PRESSURE, BODY-MASS INDEX, medicine.disease, Blood pressure, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Heart failure, 1182 Biochemistry, cell and molecular biology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Gene-Environment Interaction, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Genome-Wide Association Study
Abstract: Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene–smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene–smoking interaction analysis and 38 were newly identified (P
Published: 2019

45. Metabolomics Profiling of Visceral Adipose Tissue: Results From MESA and the NEO Study

Author: Matthew A. Allison, David M. Herrington, Ibrahim Karaman, Ioanna Tzoulaki, Philip Greenland, Claire L. Boulangé, Roelof A.J. Smit, Ian J. Neeland, Dennis O. Mook-Kanamori, Renée de Mutsert, Naresh M. Punjabi, Hildo J. Lamb, J. Wouter Jukema, Ko Willems van Dijk, Sebastiaan C. Boone, Frits R. Rosendaal, Colby Ayers, Dhananjay Vaidya, Imperial College Healthcare NHS Trust- BRC Funding, and National Institutes of Health
Subjects: Male, obesity, Epidemiology, Metabolite, Glutamine, Proton Magnetic Resonance Spectroscopy, Adipose tissue, Cardiorespiratory Medicine and Haematology, 030204 cardiovascular system & hematology, chemistry.chemical_compound, 0302 clinical medicine, 80 and over, visceral adipose tissue, Amino Acids, Tomography, Original Research, 2. Zero hunger, Aged, 80 and over, 0303 health sciences, cohort, Organ Size, Middle Aged, Magnetic Resonance Imaging, X-Ray Computed, 3. Good health, adipose tissue, Cholesterol, Female, Cardiology and Cardiovascular Medicine, Glycolysis, Metabolic Networks and Pathways, medicine.medical_specialty, HDL, metabolite, Intra-Abdominal Fat, LDL, 03 medical and health sciences, Metabolomics, Internal medicine, medicine, Humans, Lactic Acid, Metabolic and endocrine, Triglycerides, Nutrition, 030304 developmental biology, Aged, business.industry, Prevention, Cholesterol, HDL, Gluconeogenesis, Metabolism, Cholesterol, LDL, Branched-Chain, Endocrinology, chemistry, Linear Models, Digestive Diseases, business, Tomography, X-Ray Computed, Biomarkers, Amino Acids, Branched-Chain, Lipoprotein
Abstract: Background Identifying associations between serum metabolites and visceral adipose tissue ( VAT ) could provide novel biomarkers of VAT and insights into the pathogenesis of obesity‐related diseases. We aimed to discover and replicate metabolites reflecting pathways related to VAT . Methods and Results Associations between fasting serum metabolites and VAT area (by computed tomography or magnetic resonance imaging) were assessed with cross‐sectional linear regression of individual‐level data from participants in MESA (Multi‐Ethnic Study of Atherosclerosis; discovery, N=1103) and the NEO (Netherlands Epidemiology of Obesity) study (replication, N=2537). Untargeted 1 H nuclear magnetic resonance metabolomics profiling of serum was performed in MESA, and metabolites were replicated in the NEO study using targeted 1 H nuclear magnetic resonance spectroscopy. A total of 30 590 metabolomic spectral variables were evaluated. After adjustment for age, sex, race/ethnicity, socioeconomic status, smoking, physical activity, glucose/lipid‐lowering medication, and body mass index, 2104 variables representing 24 nonlipid and 49 lipid/lipoprotein subclass metabolites remained significantly associated with VAT ( P =4.88×10 −20 –1.16×10 −3 ). These included conventional metabolites, amino acids, acetylglycoproteins, intermediates of glucose and hepatic metabolism, organic acids, and subclasses of apolipoproteins, cholesterol, phospholipids, and triglycerides. Metabolites mapped to 31 biochemical pathways, including amino acid substrate use/metabolism and glycolysis/gluconeogenesis. In the replication cohort, acetylglycoproteins, branched‐chain amino acids, lactate, glutamine (inversely), and atherogenic lipids remained associated with VAT ( P =1.90×10 −35 –8.46×10 −7 ), with most associations remaining after additional adjustment for surrogates of VAT (glucose level, waist circumference, and serum triglycerides), reflecting novel independent associations. Conclusions We identified and replicated a metabolite panel associated with VAT in 2 community‐based cohorts. These findings persisted after adjustment for body mass index and appear to define a metabolic signature of visceral adiposity.
Published: 2019

46. Mendelian randomization reveals unexpected effects of CETP on the lipoprotein profile

Author: C Alexander Blauw, Jimmy F.P. Berbée, Lisanne L. Blauw, Patrick C.N. Rensen, Ko Willems van Dijk, Raymond Noordam, Diana van Heemst, Sebastian Soidinsalo, Dennis O. Mook-Kanamori, Frits R. Rosendaal, Yanan Wang, J. Wouter Jukema, Renée de Mutsert, Peter Würtz, Ruifang Li-Gao, Diabetes and Obesity Research Program, and Research Programs Unit
Subjects: Male, medicine.medical_specialty, Very low-density lipoprotein, LIPID TRANSFER PROTEIN, Lipoproteins, Biology, Article, ESTER TRANSFER PROTEIN, 03 medical and health sciences, chemistry.chemical_compound, High-density lipoprotein, Anacetrapib, Internal medicine, Mendelian randomization, Cholesterylester transfer protein, Genetics, medicine, Humans, GENOME-WIDE ASSOCIATION, CETP inhibitor, Genetics (clinical), 0303 health sciences, PLASMA, Models, Genetic, 030305 genetics & heredity, 1184 Genetics, developmental biology, physiology, Middle Aged, HEPATIC LIPASE, REMNANT CHOLESTEROL, Cholesterol Ester Transfer Proteins, 3. Good health, carbohydrates (lipids), HIGH-RISK, Endocrinology, chemistry, Cholesteryl ester, biology.protein, HEART, 1182 Biochemistry, cell and molecular biology, Female, lipids (amino acids, peptides, and proteins), CHOLESTERYL ESTER, 3111 Biomedicine, HIGH-DENSITY-LIPOPROTEIN, Lipoprotein
Abstract: According to the current dogma, cholesteryl ester transfer protein (CETP) decreases high-density lipoprotein (HDL)-cholesterol (C) and increases low-density lipoprotein (LDL)-C. However, detailed insight into the effects of CETP on lipoprotein subclasses is lacking. Therefore, we used a Mendelian randomization approach based on a genetic score for serum CETP concentration (rs247616, rs12720922 and rs1968905) to estimate causal effects per unit (mu g/mL) increase in CETP on 159 standardized metabolic biomarkers, primarily lipoprotein subclasses. Metabolic biomarkers were measured by nuclear magnetic resonance (NMR) in 5672 participants of the Netherlands Epidemiology of Obesity (NEO) study. Higher CETP concentrations were associated with less large HDL (largest effect XL-HDL-C, P = 6 x 10(-22)) and more small VLDL components (largest effect S-VLDL cholesteryl esters, P = 6 x 10(-6)). No causal effects were observed with LDL subclasses. All these effects were replicated in an independent cohort from European ancestry (MAGNETIC NMR GWAS; n similar to 20,000). Additionally, we assessed observational associations between ELISA-measured CETP concentration and metabolic measures. In contrast to results from Mendelian randomization, observationally, CETP concentration predominantly associated with more VLDL, IDL and LDL components. Our results show that CETP is an important causal determinant of HDL and VLDL concentration and composition, which may imply that the CETP inhibitor anacetrapib decreased cardiovascular disease risk through specific reduction of small VLDL rather than LDL. The contrast between genetic and observational associations might be explained by a high capacity of VLDL, IDL and LDL subclasses to carry CETP, thereby concealing causal effects on HDL.
Published: 2019

47. Genome-wide meta-analysis of SNP-by9-ACEI/ARB and SNP-by-thiazide diuretic and effect on serum potassium in cohorts of European and African ancestry

Author: Bruce M. Psaty, Donna K. Arnett, Degui Zhi, Renée de Mutsert, Traci M. Bartz, Albert V. Smith, Raymond Noordam, Leonard Lipovich, Vinodh Srinivasasainagendra, Dennis O. Mook-Kanamori, Nita A. Limdi, André G. Uitterlinden, Colleen M. Sitlani, Eric A. Whitsel, Marguerite R. Irvin, James G. Wilson, Leslie A. Lange, Christie L. Avery, Jin Li, Jerome I. Rotter, Bruno H. Stricker, James S. Floyd, Joshua C. Bis, James A. Stewart, Erica L. Kleinbrink, Kerri L. Wiggins, Epidemiology, and Internal Medicine
Subjects: 0301 basic medicine, Pharmacology, Oncology, medicine.medical_specialty, Hyperkalemia, business.industry, Chromosome, Single-nucleotide polymorphism, 030226 pharmacology & pharmacy, Genome, 3. Good health, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Serum potassium, Internal medicine, Meta-analysis, Genotype, Genetics, medicine, Molecular Medicine, SNP, cardiovascular diseases, medicine.symptom, business
Abstract: We evaluated interactions of SNP-by-ACE-I/ARB and SNP-by-TD on serum potassium (K+) among users of antihypertensive treatments (anti-HTN). Our study included seven European-ancestry (EA) (N = 4835) and four African-ancestry (AA) cohorts (N = 2016). We performed race-stratified, fixed-effect, inverse-variance-weighted meta-analyses of 2.5 million SNP-by-drug interaction estimates; race-combined meta-analysis; and trans-ethnic fine-mapping. Among EAs, we identified 11 significant SNPs (P < 5 × 10 −8 ) for SNP-ACE-I/ARB interactions on serum K+ that were located between NR2F1-AS1 and ARRDC3-AS1 on chromosome 5 (top SNP rs6878413 P = 1.7 × 10 −8 ; ratio of serum K+ in ACE-I/ARB exposed compared to unexposed is 1.0476, 1.0280, 1.0088 for the TT, AT, and AA genotypes, respectively). Trans-ethnic fine mapping identified the same group of SNPs on chromosome 5 as genome-wide significant for the ACE-I/ARB analysis. In conclusion, SNP-by-ACE-I /ARB interaction analyses uncovered loci that, if replicated, could have future implications for the prevention of arrhythmias due to anti-HTN treatment-related hyperkalemia. Before these loci can be identified as clinically relevant, future validation studies of equal or greater size in comparison to our discovery effort are needed.
Published: 2019

48. Glucose metabolism affects coagulation factors: The NEO study

Author: Astrid van Hylckama Vlieg, Willem M. Lijfering, Fréderique A. van der Toorn, Renée de Mutsert, and Frits R. Rosendaal
Subjects: Blood Glucose, Male, medicine.medical_specialty, Population, 030204 cardiovascular system & hematology, Carbohydrate metabolism, Fibrinogen, Factor IX, 03 medical and health sciences, 0302 clinical medicine, Diabetes mellitus, Internal medicine, Glucose Intolerance, medicine, Diabetes Mellitus, Humans, Prospective Studies, glucose, education, Blood Coagulation, Factor XI, Aged, Netherlands, Glycated Hemoglobin, education.field_of_study, Factor VIII, business.industry, Confounding, Hematology, Fasting, Middle Aged, medicine.disease, Impaired fasting glucose, Postprandial Period, Blood Coagulation Factors, Postprandial, Endocrinology, Cross-Sectional Studies, Female, hyperglycemia, business, Biomarkers, medicine.drug, Cohort study
Abstract: Background It is insufficiently understood if there is an association between diabetes and VT, and what the underlying mechanism would be. Objectives We aimed to study the association between glucose concentrations with several coagulation factors in the general population. Methods This is a cross-sectional analysis of baseline measurements within 5778 participants of the Netherlands Epidemiology of Obesity (NEO) study, a population-based cohort study of individuals 45 to 65 years. Associations between fasting glucose and HbA1c concentrations, and postprandial glucose response and factor (F) VIII, FIX, FXI, and fibrinogen levels were examined using linear regression analyses and by calculating mean levels per category of glucose concentrations while adjusting for confounding factors. Results Per each mmol/L higher fasting glucose concentration we observed higher levels of fasting FVIII (5.33%, 95% CI: 4.00-6.65), FIX (6.19%, 95% CI: 5.15-7.23), and FXI (2.11%, 95% CI: 1.20-3.02). Results for fasting HbA1c and postprandial glucose response were similar. Participants with an impaired fasting glucose, high fasting glucose, and diabetes mellitus had higher mean levels of FVIII, FIX, and FXI than those with a normal glucose metabolism, with the highest differences in the levels of FVIII, FIX, and FXI between a high fasting glucose and a normal glucose metabolism. All associations attenuated after adjustment for total body fat, yet all of the above associations remained after adjustment for the confounding factors, except for fibrinogen when contrasted to glucose. Conclusion Concentrations of fasting glucose and HbA1c and postprandial glucose response were positively associated with FVIII, FIX, and FXI, and to some extent also with fibrinogen.
Published: 2019

49. Exome-derived adiponectin-associated variants implicate obesity and lipid biology

Author: Peter Kovacs, Judith B. Borja, Karen L. Mohlke, Jennifer Kriebel, Kent D. Taylor, Stuart MacGregor, Ruth J. F. Loos, Carol A. Wang, Cornelia M. van Duijn, Samuli Ripatti, Ko Willems van Dijk, Jaeyoung Hong, Yingchang Lu, Leslie A. Lange, Terho Lehtimäki, Matthias Blüher, Cassandra N. Spracklen, Michael A. Province, Craig E. Pennell, Laura B. L. Wittemans, Yii-Der Ida Chen, Alex P. Reiner, Nicholas J. Wareham, Massimo Mangino, Kristin L. Young, Tuomas O. Kilpeläinen, David A. Mackey, Michael Preuss, Mika Kähönen, Sara M. Willems, Paraskevi Chirstofidou, Tamara B. Harris, Matthew A. Allison, Michael Boehnke, Jian'an Luan, Cristina Venturini, Kari E. North, Chelsea K. Raulerson, Linda Broer, Paul M. Ridker, Colleen M. Sitlani, Xiuqing Guo, Leo-Pekka Lyytikäinen, Neil Roberston, Pekka Jousilahti, Barbara McKnight, M. Arfan Ikram, Heather M. Highland, Torben Hansen, Niels Grarup, Satu Männistö, James G. Wilson, Konstantin Strauch, Mariaelisa Graff, Ayse Demirkan, Rebecca S. Fine, Tugce Karaderi, Linda S. Adair, Jie Yao, Olli T. Raitakari, Zoltán Kutalik, Jeffrey Haesser, Veikko Salomaa, Sophie Molnos, Rebecca D. Jackson, Renée de Mutsert, Markku Laakso, Mark I. McCarthy, Carolina Medina-Gomez, America A. Sandoval-Zárate, Anke Tönjes, Daniel I. Chasman, Shuai Wang, Michael Stumvoll, Jette Bork-Jensen, Claudia Langenberg, Paul L. Auer, Anubha Mahajan, Claudia Schurmann, Mary F. Feitosa, Melissa E. Garcia, Tim D. Spector, Aruna D. Pradhan, Jorge R. Kizer, Timothy M. Frayling, Ying Wu, James B. Meigs, Andrew P. Morris, Harald Grallert, André G. Uitterlinden, Cecilia M. Lindgren, Traci M. Bartz, Mike A. Nalls, Erik Ingelsson, Jerome I. Rotter, Mark Walker, Ruifang Li-Gao, Ivana Nedeljkovic, Najaf Amin, Hanieh Yaghootkar, Dennis O. Mook-Kanamori, Betina H. Thuesen, Lars Lind, Jin Li, Epidemiology, Internal Medicine, Centre of Excellence in Complex Disease Genetics, Department of Public Health, Samuli Olli Ripatti / Principal Investigator, University Management, Biostatistics Helsinki, University of Helsinki, Institute for Molecular Medicine Finland, Complex Disease Genetics, and Medical and Clinical Psychology
Subjects: Male, 0301 basic medicine, Candidate gene, Adipose tissue, Genome-wide association study, DISEASE, CANDIDATE GENES, 0302 clinical medicine, Cqardio metabolic traits, RARE, Exome, Genetics (clinical), Aged, 80 and over, Genetics, 0303 health sciences, 1184 Genetics, developmental biology, physiology, Hispanic or Latino, Middle Aged, Lipids, Phenotype, ADIPOSE-TISSUE, Adipose Tissue, 030220 oncology & carcinogenesis, Medical genetics, Female, CIRCULATING ADIPONECTIN, Adiponectin, Adult, EXPRESSION, medicine.medical_specialty, Adolescent, Quantitative Trait Loci, 030209 endocrinology & metabolism, Biology, Polymorphism, Single Nucleotide, Article, White People, Young Adult, 03 medical and health sciences, Cardio Metabolic Traits, Genome-wide Association Study, Obesity, SDG 3 - Good Health and Well-being, medicine, GLYCEMIC TRAITS, Humans, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, Gene, METAANALYSIS, 030304 developmental biology, Aged, PLASMA ADIPONECTIN, Correction, medicine.disease, Human genetics, Black or African American, 030104 developmental biology, Expression quantitative trait loci, 3111 Biomedicine
Abstract: Circulating levels of adiponectin, an adipocyte-secreted protein associated with cardiovascular and metabolic risk, are highly heritable. To gain insights into the biology that regulates adiponectin levels, we performed an exome array meta-analysis of 265,780 genetic variants in 67,739 individuals of European, Hispanic, African American, and East Asian ancestry. We identified 20 loci associated with adiponectin, including 11 that had been reported previously (p -7). Comparison of exome array variants to regional linkage disequilibrium (LD) patterns and prior genome-wide association study (GWAS) results detected candidate variants (r2 > .60) spanning as much as 900 kb. To identify potential genes and mechanisms through which the previously unreported association signals act to affect adiponectin levels, we assessed cross-trait associations, expression quantitative trait loci in subcutaneous adipose, and biological pathways of nearby genes. Eight of the nine loci were also associated (p -4) with at least one obesity or lipid trait. Candidate genes include PRKAR2A, PTH1R, and HDAC9, which have been suggested to play roles in adipocyte differentiation or bone marrow adipose tissue. Taken together, these findings provide further insights into the processes that influence circulating adiponectin levels.
Published: 2019

50. Tissue-Specific Alteration of Metabolic Pathways Influences Glycemic Regulation

Author: Wieland Kiess, Josée Dupuis, Yingchang Lu, Yii-Der Ida Chen, Sara M. Willems, George Dedoussis, Frida Renström, Carolina Medina-Gomez, Tamara B. Harris, Cramer Christensen, Audrey Y. Chu, Nicola L. Beer, Emil V. R. Appel, Niels Grarup, Fredrik Karpe, Mark I. McCarthy, Yuning Chen, Veikko Salomaa, Sylvain Sebert, Richard A. Jensen, Joel N. Hirschhorn, Lars Lind, Jocelyn E. Manning Fox, Caroline Hayward, Patrick E. MacDonald, Matti Uusitupa, Stavroula Kanoni, Carola Marzi, Kenneth Rice, Leslie A. Lange, Ken Sin Lo, Jennifer L. Asimit, Nisa M. Maruthur, Leonard Lipovich, James S. Floyd, Rona J. Strawbridge, Magdalena Zoledziewska, Anne Raimondo, Robert Sladek, Alexandra I. F. Blakemore, Hugoline G. de Haan, Danish Saleheen, Ji Chen, Neil Robertson, Ching-Yu Cheng, Heiner Boeing, Min A. Jhun, Marjo-Riitta Järvelin, Anubha Mahajan, Rainer Rauramaa, Satu Männistö, Paul M. Ridker, Ivan Brandslund, Hester M. den Ruijter, Tien Yin Wong, Alison D. Murray, Jaakko Tuomilehto, Xueling Sim, Igor Rudan, Martijn van de Bunt, Jin Li, Marit E. Jørgensen, Marie-France Hivert, Archie Campbell, Salman M. Tajuddin, Pekka Jousilahti, Lawrence F. Bielak, Juan P. Fernandez, Eleanor Wheeler, Alan B. Zonderman, Anne Clark, Lori L. Bonnycastle, Kurt Lohman, Peter Kovacs, Jung-Jin Lee, Jennifer Wessel, Wesam A Alhejily, Gerard Pasterkamp, John M. Starr, Ping An, Matthias Blüher, Jian'an Luan, Hanieh Yeghootkar, Jakob Stokholm, Michael Roden, Blair H. Smith, Johanna Jakobsdottir, Franco Giulianini, Andrianos M. Yiorkas, Hidetoshi Kitajima, Michael A. Province, Aliki-Eleni Farmaki, Kerrin S. Small, Juha Saltevo, Robert A. Scott, Alena Stančáková, Gaëlle Marenne, Asif Rasheed, Ruth J. F. Loos, David J. Porteous, Cecilia M. Lindgren, Inês Barroso, Gail Davies, Anna L. Gloyn, Shuai Wang, Paul Redmond, Xiuqing Guo, Ele Ferrannini, Mariaelisa Graff, Cornelia M. van Duijn, Juha Auvinen, David R. Weir, Kay-Tee Kaw, Tarunveer S. Ahluwalia, Olov Rolandsson, Wei Zhao, Paul Elliott, Torben Hansen, Abbas Dehghan, Bram P. Prins, Michiel L. Bots, Alison Pattie, Jun Liu, Gonçalo R. Abecasis, Maria Karaleftheri, Claudia Langenberg, Jan-Håkan Jansson, Marja Vääräsmäki, James S. Pankow, Rebecca S. Fine, Jaana Lindström, Ozren Polasek, Vinicius Tragante, Soren K. Thomsen, Jana K. Rundle, Najaf Amin, Saima Afaq, Jennifer A. Smith, Anne U. Jackson, Eirini Marouli, Weihua Zhang, Tim D. Spector, Paul W. Franks, Serena Sanna, Mark J. Caulfield, Heikki A. Koistinen, Jaspal S. Kooner, Tea Skaaby, Francis S. Collins, Eva Rabing Brix Petersen, Arfan Ikram, Sander W. van der Laan, Johanna Kuusisto, Jette Bork-Jensen, Daniel I. Chasman, Michele K. Evans, Emmanouil Tsafantakis, A. I. Tarasov, Ian J. Deary, Hans Bisgaard, Dennis O. Mook-Kanamori, Helen R. Warren, Kent D. Taylor, Andrew D. Morris, Eleftheria Zeggini, Sharon L.R. Kardia, Emma Ahlqvist, Gert J. de Borst, Torben Jørgensen, Antonella Mulas, Man Li, Betina H. Thuesen, Yuan Shi, Timo A. Lakka, Jie Yao, Tapani Ebeling, Natasha H. J. Ng, Sai Chen, Leena Kinnunen, Antje Körner, Klaus Bønnelykke, Lorraine Southam, Anette P. Gjesing, Ilonca Vaartjes, Heather M. Highland, Göran Hallmans, Anke Tönjes, Markku Laakso, Lenore J. Launer, Josef Coresh, Oscar H. Franco, Yongmei Liu, Beverley Balkau, Leena Moilanen, Karl-Heinz Herzig, James G. Wilson, Jennifer A. Brody, Renée de Mutsert, Alisa K. Manning, Anne E. Justice, Matthias B. Schulze, Sandosh Padmanabhan, Jose C. Florez, Shuang Feng, Heather M. Stringham, Bruce M. Psaty, Erwin P. Bottinger, Hannu Puolijoki, Vilmundur Gudnason, Leif Groop, Nicholas J. Wareham, Karina Meidtner, Andrew P. Morris, Taulant Muka, Benoit Hastoy, Panos Deloukas, Pirjo Komulainen, Ayse Demirkan, Francesco Cucca, Stefan Gustafsson, Eric Boerwinkle, Patrik Rorsman, Mike A. Nalls, Erik Ingelsson, Colin N. A. Palmer, Allan Linneberg, Tiinamaija Tuomi, Dan E. Arking, Steve Franks, Jonathan Marten, Mark Walker, Ruifang Li-Gao, Kai Savonen, Michael Stumvoll, Andreas Fritsche, E-Shyong Tai, Mark O. Goodarzi, Matt J. Neville, Oluf Pedersen, Eero Kajantie, Ching-Ti Liu, Michael Boehnke, Aaron Leong, Patricia B. Munroe, Patricia A. Peyser, Jessica D. Faul, John C. Chambers, John Danesh, Sirkka Keinänen-Kiukaanniemi, Giorgio Pistis, Karen L. Mohlke, Folkert W. Asselbergs, James B. Meigs, Tibor V. Varga, Erica L. Kleinbrink, Andrew T. Hattersley, Nathan A. Bihlmeyer, Harald Grallert, Albert V. Smith, Konstantin Strauch, Jerome I. Rotter, and Frits R. Rosendaal
Subjects: medicine.medical_specialty, G6PC2, pathways, Adipose tissue, Type 2 diabetes, Biology, effector transcript, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Diabetes mellitus, Internal medicine, 0502 economics and business, medicine, Glucose homeostasis, genetics, 050207 economics, 030304 developmental biology, Glycemic, 0303 health sciences, 050208 finance, Pancreatic islets, 05 social sciences, tissue, Genomics, medicine.disease, Endocrinology, medicine.anatomical_structure, chemistry, glycemic traits, Glycated hemoglobin, type 2 diabetes, 030217 neurology & neurosurgery
Abstract: SummaryMetabolic dysregulation in multiple tissues alters glucose homeostasis and influences risk for type 2 diabetes (T2D). To identify pathways and tissues influencing T2D-relevant glycemic traits (fasting glucose [FG], fasting insulin [FI], two-hour glucose [2hGlu] and glycated hemoglobin [HbA1c]), we investigated associations of exome-array variants in up to 144,060 individuals without diabetes of multiple ancestries. Single-variant analyses identified novel associations at 21 coding variants in 18 novel loci, whilst gene-based tests revealed signals at two genes, TF (HbA1c) and G6PC (FG, FI). Pathway and tissue enrichment analyses of trait-associated transcripts confirmed the importance of liver and kidney for FI and pancreatic islets for FG regulation, implicated adipose tissue in FI and the gut in 2hGlu, and suggested a role for the non-endocrine pancreas in glucose homeostasis. Functional studies demonstrated that a novel FG/FI association at the liver-enriched G6PC transcript was driven by multiple rare loss-of-function variants. The FG/HbA1c-associated, islet-specific G6PC2 transcript also contained multiple rare functional variants, including two alleles within the same codon with divergent effects on glucose levels. Our findings highlight the value of integrating genomic and functional data to maximize biological inference.Highlights23 novel coding variant associations (single-point and gene-based) for glycemic traits51 effector transcripts highlighted different pathway/tissue signatures for each traitThe exocrine pancreas and gut influence fasting and 2h glucose, respectivelyMultiple variants in liver-enriched G6PC and islet-specific G6PC2 influence glycemia
Published: 2019

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