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1. The impact of sociodemographic status on the association of classical cardiovascular risk factors with coronary artery disease: a stratified Mendelian randomization study.

Author

Martens LG, van Hamersveld D, le Cessie S, Willems van Dijk K, van Heemst D, and Noordam R

Subjects
Humans, Risk Factors, Mendelian Randomization Analysis, Heart Disease Risk Factors, Triglycerides, Lipoproteins, LDL genetics, Cholesterol, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Coronary Artery Disease epidemiology, Coronary Artery Disease genetics, Cardiovascular Diseases epidemiology
Abstract

Objectives: Low socioeconomic status (SES) is associated with cardiovascular risk factors and increased coronary artery disease (CAD) risk. We tested whether SES is an effect modifier of the association between classical cardiovascular risk factors and CAD using SES-stratified Mendelian Randomization in European-ancestry participants from UK Biobank., Study Design and Setting: We calculated weighted genetic risk scores (GRS) for the risk factors body mass index (BMI), systolic blood pressure, low-density lipoprotein cholesterol, and triglycerides. Participants were stratified by Townsend deprivation index score. Logistic regression models were used to investigate associations between GRSs and CAD occurrence. Additionally, stratification based on GRS-adjusted Townsend deprivation index residuals was conducted to correct for possible collider-stratification bias., Results: In a total sample size of N = 446,485, with 52,946 cases, the risk for CAD per standard deviation increase in genetically influenced BMI was highest in the group with the lowest 25% SES (odds ratio: 1.126, 95% confidence interval: 1.106-1.145; odds ratio: 1.081, 95% confidence interval: 1.059-1.103 in high SES), remaining similar after controlling for possible collider-stratification bias. The effects of genetically influenced systolic blood pressure, low-density lipoprotein cholesterol, and triglyceride on CAD were similar between SES groups., Conclusion: CAD risk attributable to increased BMI is not homogenous and could be modified by SES. This emphasizes the need of tailor-made approaches for BMI-associated CAD risk reduction., Competing Interests: Declaration of competing interest None declared., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Published
2023
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2. Cardiovascular risk factors and major recurrent coronary events: A genetic liability study in patients with coronary artery disease in the UK Biobank.

Author

Noordam R, Brochard TA, Drewes YM, Gussekloo J, Mooijaart SP, Willems van Dijk K, Trompet S, Jukema JW, and van Heemst D

Subjects
Male, Humans, Middle Aged, Female, Risk Factors, Cholesterol, LDL, Biological Specimen Banks, Heart Disease Risk Factors, Triglycerides, United Kingdom epidemiology, Mendelian Randomization Analysis, Coronary Artery Disease epidemiology, Coronary Artery Disease genetics, Cardiovascular Diseases genetics, Myocardial Infarction diagnosis, Myocardial Infarction epidemiology, Myocardial Infarction genetics, Myocardial Ischemia
Abstract

Background and Aims: Mendelian randomization confirmed multiple risk factors for primary events of coronary artery disease (CAD), but no such studies have been performed on recurrent major coronary events despite interesting insights derived from other designs. We examined the associations between genetically-influenced classical cardiovascular risk factors and the risk of recurrent major coronary events in a cohort of CAD patients., Methods: We included all first-time CAD cases (defined as angina pectoris, chronic ischemic heart disease or acute myocardial infarction) of European ancestry from the UK Biobank. Cases were followed till the end of follow-up, death or when they developed a recurrent major coronary event (chronic ischemic heart disease or acute myocardial infarction). Standardized weighted genetic risk scores were calculated for body mass index (BMI), systolic blood pressure, LDL cholesterol and triglycerides., Results: From a total of 22,949 CAD patients (mean age at first diagnosis 59.8 (SD 7.3) years, 71.1% men), 12,539 (54.6%) reported a recurrent major coronary event within a period of maximum 17.8 years. One standard deviation higher genetically-determined LDL cholesterol was associated with a higher risk of a recurrent major coronary event (odds ratio: 1.08 [95% confidence interval: 1.05, 1.11]). No associations were observed for genetically-influenced BMI (1.00 [0.98, 1.03]), systolic blood pressure (1.01 [0.98, 1.03]) and triglycerides (1.02 [0.995, 1.05])., Conclusions: Despite the use risk-reducing medications following a first coronary event, this study provided genetic evidence that, of the classical risk factors, mainly high LDL cholesterol was associated with a higher risk of developing recurrent major coronary events., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2023
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3. Low leukocyte mitochondrial DNA abundance drives atherosclerotic cardiovascular diseases: a cohort and Mendelian randomization study.

Author

Luo J, Noordam R, Jukema JW, van Dijk KW, Hägg S, Grassmann F, le Cessie S, and van Heemst D

Subjects
Humans, DNA, Mitochondrial genetics, Mendelian Randomization Analysis, Cohort Studies, Mitochondria genetics, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Cardiovascular Diseases genetics, Coronary Artery Disease genetics, Atherosclerosis
Abstract

Aim: Mitochondrial DNA dysfunction has been implicated in the pathogenesis of cardiovascular diseases. We aimed to investigate the associations between leukocyte mitochondrial DNA (mtDNA) abundance, as a proxy of mitochondrial function, and coronary artery disease (CAD) and heart failure (HF) in a cohort study and approximate the causal nature of these relationships using Mendelian randomization (MR) in genetic studies., Methods and Results: Multivariable-adjusted Cox regression analyses were conducted in 273 619 unrelated participants of European ancestry from the UK Biobank (UKB). For genetic studies, we first performed MR analyses with individual-level data from the UKB using a weighted genetic risk score (GRS); two-sample MR analyses were subsequently performed using summary-level data from the publicly available three consortia/biobank for CAD and two for HF. MR analyses were performed per database separately and results were subsequently meta-analysed using fixed-effects models. During a median follow-up of 11.8 years, restricted cubic spline Cox regression analyses showed associations between lower mtDNA abundance and higher risk of CAD and HF. Hazard ratios for participants in the lowest quintile of mtDNA abundance compared with those in the highest quintile were 1.08 (95% confidence interval: 1.03, 1.14) and 1.15 (1.05, 1.24) for CAD and HF. Genetically, no evidence was observed for a possible non-linear causal effect using individual-level weighted genetic risk scores calculated in the UKB on the study outcomes; the pooled odds ratios (95% confidence interval) from two-sample MR of genetically predicted per one-SD decrease in mtDNA abundance were 1.09 (1.03, 1.16) for CAD and 0.99 (0.92, 1.08) for HF, respectively., Conclusion: Our findings support a possible causal role of lower leukocyte mtDNA abundance in higher CAD risk, but not in HF., Competing Interests: Conflict of interest: None declared., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Published
2023
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4. Setting your clock: associations between timing of objective physical activity and cardiovascular disease risk in the general population.

Author

Albalak G, Stijntjes M, van Bodegom D, Jukema JW, Atsma DE, van Heemst D, and Noordam R

Subjects
Humans, Female, Middle Aged, Male, Risk Factors, Self Report, Exercise, Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology, Cardiovascular Diseases prevention & control, Stroke epidemiology
Abstract

Aims: Little is known about the impact of daily physical activity timing (here referred to as 'chronoactivity') on cardiovascular disease (CVD) risk. We aimed to examined the associations between chronoactivity and multiple CVD outcomes in the UK Biobank., Methods and Results: physical activity data were collected in the UK-Biobank through triaxial accelerometer over a 7-day measurement period. We used K-means clustering to create clusters of participants with similar chronoactivity irrespective of the mean daily intensity of the physical activity. Multivariable-adjusted Cox-proportional hazard models were used to estimate hazard ratios (HRs) comparing the different clusters adjusted for age and sex (model 1), and baseline cardiovascular risk factors (model 2). Additional stratified analyses were done by sex, mean activity level, and self-reported sleep chronotype. We included 86 657 individuals (58% female, mean age: 61.6 [SD: 7.8] years, mean BMI: 26.6 [4.5] kg/m2). Over a follow-up period of 6 years, 3707 incident CVD events were reported. Overall, participants with a tendency of late morning physical activity had a lower risk of incident coronary artery disease (HR: 0.84, 95%CI: 0.77, 0.92) and stroke (HR: 0.83, 95%CI: 0.70, 0.98) compared to participants with a midday pattern of physical activity. These effects were more pronounced in women (P-value for interaction = 0.001). We did not find evidence favouring effect modification by total activity level and sleep chronotype., Conclusion: Irrespective of total physical activity, morning physical activity was associated with lower risks of incident cardiovascular diseases, highlighting the potential importance of chronoactivity in CVD prevention., Competing Interests: Conflict of interest: None declared., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Published
2023
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5. The association of measures of body shape and adiposity with incidence of cardiometabolic disease from an ageing perspective.

Author

Meulmeester FL, Willems van Dijk K, Mooijaart SP, van Heemst D, and Noordam R

Subjects
Male, Humans, Female, Adiposity, Incidence, Somatotypes, Body Mass Index, Obesity complications, Obesity epidemiology, Aging, Diabetes Mellitus, Type 2 epidemiology, Cardiovascular Diseases
Abstract

While obesity increases the risk of developing cardiometabolic diseases (CMDs), these associations seem to attenuate with increasing age, albeit studied poorly. The present study aimed to investigate the associations between adiposity and CMDs in sex-specific groups of chronological age and leukocyte telomere length (LTL) as a measure of biological age. We investigated the associations between BMI, a body shape index, waist-to-hip ratio (adjusted for BMI) and total body fat, and incident coronary artery disease (CAD), type 2 diabetes (T2D) and ischemic stroke (IS) in 413,017 European-ancestry participants of the UK Biobank without CMD at baseline. We assessed the change in the associations between adiposity and CMD over strata of increasing chronological age or decreasing LTL. Participants (56% women) had a median (IQR) age of 57.0 (50.0-63.0) years. The median follow-up time was 12 years. People with higher BMI had a higher risk of incident CAD (HR 1.14 (95% confidence interval [CI] 1.13, 1.16)), T2D (HR 1.70 (95% CI 1.68, 1.72)) and IS (HR 1.09 (95% CI 1.06, 1.12)). In groups based on chronological age and LTL, adiposity measures were associated with higher risk of CAD and T2D in both men and women, but these associations attenuated with increasing chronological age (P interactions  < 0.001), but not with decreasing LTL (P interaction men = 0.85; P interaction women = 0.27). Increased (abdominal) adiposity was associated with higher risk of incident CMDs, which attenuated with increasing chronological age but not with decreasing LTL. Future research may validate these findings using different measures of biological age., (© 2022. The Author(s).)

Published
2023
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6. Higher thyrotropin leads to unfavorable lipid profile and somewhat higher cardiovascular disease risk: evidence from multi-cohort Mendelian randomization and metabolomic profiling.

Author

van Vliet NA, Bos MM, Thesing CS, Chaker L, Pietzner M, Houtman E, Neville MJ, Li-Gao R, Trompet S, Mustafa R, Ahmadizar F, Beekman M, Bot M, Budde K, Christodoulides C, Dehghan A, Delles C, Elliott P, Evangelou M, Gao H, Ghanbari M, van Herwaarden AE, Ikram MA, Jaeger M, Jukema JW, Karaman I, Karpe F, Kloppenburg M, Meessen JMTA, Meulenbelt I, Milaneschi Y, Mooijaart SP, Mook-Kanamori DO, Netea MG, Netea-Maier RT, Peeters RP, Penninx BWJH, Sattar N, Slagboom PE, Suchiman HED, Völzke H, Willems van Dijk K, Noordam R, and van Heemst D

Subjects
Adult, Aged, Female, Humans, Lipids, Male, Mendelian Randomization Analysis, Middle Aged, Thyroxine, Young Adult, Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology, Cardiovascular Diseases genetics, Thyrotropin
Abstract

Background: Observational studies suggest interconnections between thyroid status, metabolism, and risk of coronary artery disease (CAD), but causality remains to be proven. The present study aimed to investigate the potential causal relationship between thyroid status and cardiovascular disease and to characterize the metabolomic profile associated with thyroid status., Methods: Multi-cohort two-sample Mendelian randomization (MR) was performed utilizing genome-wide significant variants as instruments for standardized thyrotropin (TSH) and free thyroxine (fT4) within the reference range. Associations between TSH and fT4 and metabolic profile were investigated in a two-stage manner: associations between TSH and fT4 and the full panel of 161 metabolomic markers were first assessed hypothesis-free, then directional consistency was assessed through Mendelian randomization, another metabolic profile platform, and in individuals with biochemically defined thyroid dysfunction., Results: Circulating TSH was associated with 52/161 metabolomic markers, and fT4 levels were associated with 21/161 metabolomic markers among 9432 euthyroid individuals (median age varied from 23.0 to 75.4 years, 54.5% women). Positive associations between circulating TSH levels and concentrations of very low-density lipoprotein subclasses and components, triglycerides, and triglyceride content of lipoproteins were directionally consistent across the multivariable regression, MR, metabolomic platforms, and for individuals with hypo- and hyperthyroidism. Associations with fT4 levels inversely reflected those observed with TSH. Among 91,810 CAD cases and 656,091 controls of European ancestry, per 1-SD increase of genetically determined TSH concentration risk of CAD increased slightly, but not significantly, with an OR of 1.03 (95% CI 0.99-1.07; p value 0.16), whereas higher genetically determined fT4 levels were not associated with CAD risk (OR 1.00 per SD increase of fT4; 95% CI 0.96-1.04; p value 0.59)., Conclusions: Lower thyroid status leads to an unfavorable lipid profile and a somewhat increased cardiovascular disease risk., (© 2021. The Author(s).)

Published
2021
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7. Interplay of circulating leptin and obesity in cognition and cerebral volumes in older adults.

Author

Zonneveld MH, Noordam R, van der Grond J, van Heemst D, Mooijaart SP, Sabayan B, Jukema JW, and Trompet S

Subjects
Aged, Aged, 80 and over, Alzheimer Disease diagnostic imaging, Alzheimer Disease physiopathology, Body Mass Index, Cardiovascular Diseases diagnostic imaging, Cardiovascular Diseases physiopathology, Cognition physiology, Female, Hippocampus diagnostic imaging, Hippocampus metabolism, Hippocampus pathology, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Obesity blood, Obesity diagnostic imaging, Obesity physiopathology, Alzheimer Disease blood, Cardiovascular Diseases blood, Leptin blood, Obesity genetics
Abstract

We aimed to investigate whether circulating leptin and body mass index (BMI) associate independently with cognitive function (decline) and brain volumes using magnetic resonance imaging (MRI) in older individuals at risk of cardiovascular disease. We studied the cross-sectional and longitudinal associations in participants enrolled in the PROSPER study (Prospective Study of Pravastatin in the Elderly at Risk). Cognitive function was tested at baseline and repeated during a mean follow-up time of 3.2 years. Analyses were performed with multivariable (repeated) linear regression models and adjusted for demographics, cardiovascular risk-factors, and stratified by sex. We included 5623 dementia-free participants (52 % female, mean age 75 years) with a mean BMI of 26.9 (SD = 4.1). In a sub-study, 527 participants underwent brain MRI. At baseline, individuals with a BMI > 30 had a worse performance on the Stroop test (β 5.0 s, 95 %CI 2.6;7.5) and larger volumes of the amygdala (β 234 mm 3 , 95 %CI 3;464) and hippocampus (β 590 mm 3 , 95 %CI 181;999), independent of intracranial volume and serum leptin levels, compared with individuals with the reference BMI (BMI 18-25 kg/m 2 ). Per log ng/mL higher serum leptin, independent of BMI, a 135 mm 3 (95 %CI 2;268) higher volume of the amygdala was found, but no association was observed with cognitive tests nor with other brain volumes. Stratification for sex did not materially change the results. Whereas higher BMI associated with worse cognitive function independent of leptin levels, our study provided evidence that leptin and BMI independently associate with amygdala volume suggesting potential distinct biological associations., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Published
2021
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8. BMI-associated gene variants in FTO and cardiometabolic and brain disease: obesity or pleiotropy?

Author

Ganeff IMM, Bos MM, van Heemst D, and Noordam R

Subjects
Adiposity genetics, Eating genetics, Energy Metabolism genetics, Humans, Alpha-Ketoglutarate-Dependent Dioxygenase FTO genetics, Body Mass Index, Brain Diseases genetics, Cardiovascular Diseases genetics, Diabetes Mellitus, Type 2 genetics, Genetic Pleiotropy, Obesity genetics, Polymorphism, Single Nucleotide genetics
Abstract

Obesity is a causal risk factor for the development of age-related disease conditions, which includes Type 2 diabetes mellitus, cardiovascular disease, and dementia. In genome-wide association studies, genetic variation in FTO is strongly associated with obesity and has been described across different ethnic backgrounds and life stages. To date, much work has been devoted on determining the biological mechanisms via which FTO affects body weight regulation and ultimately contributes to age-related cardiometabolic and brain disease. The main hypotheses of the involved biological mechanisms include the involvement of FTO in habitual food intake and energy expenditure. In this narrative review, our overall aim is to provide an overview on how FTO gene variants could increase the risk of developing age-related disease conditions. Specifically, we will discuss the state of the literature based on the different hypotheses how FTO regulates body weight and ultimately contributes to cardiometabolic disease and brain disease.

Published
2019
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9. Effects of Calcium, Magnesium, and Potassium Concentrations on Ventricular Repolarization in Unselected Individuals.

Author

Noordam R, Young WJ, Salman R, Kanters JK, van den Berg ME, van Heemst D, Lin HJ, Barreto SM, Biggs ML, Biino G, Catamo E, Concas MP, Ding J, Evans DS, Foco L, Grarup N, Lyytikäinen LP, Mangino M, Mei H, van der Most PJ, Müller-Nurasyid M, Nelson CP, Qian Y, Repetto L, Said MA, Shah N, Schramm K, Vidigal PG, Weiss S, Yao J, Zilhao NR, Brody JA, Braund PS, Brumat M, Campana E, Christofidou P, Caulfield MJ, De Grandi A, Dominiczak AF, Doney ASF, Eiriksdottir G, Ellervik C, Giatti L, Gögele M, Graff C, Guo X, van der Harst P, Joshi PK, Kähönen M, Kestenbaum B, Lima-Costa MF, Linneberg A, Maan AC, Meitinger T, Padmanabhan S, Pattaro C, Peters A, Petersmann A, Sever P, Sinner MF, Shen X, Stanton A, Strauch K, Soliman EZ, Tarasov KV, Taylor KD, Thio CHL, Uitterlinden AG, Vaccargiu S, Waldenberger M, Robino A, Correa A, Cucca F, Cummings SR, Dörr M, Girotto G, Gudnason V, Hansen T, Heckbert SR, Juhl CR, Kääb S, Lehtimäki T, Liu Y, Lotufo PA, Palmer CNA, Pirastu M, Pramstaller PP, Ribeiro ALP, Rotter JI, Samani NJ, Snieder H, Spector TD, Stricker BH, Verweij N, Wilson JF, Wilson JG, Jukema JW, Tinker A, Newton-Cheh CH, Sotoodehnia N, Mook-Kanamori DO, Munroe PB, and Warren HR

Subjects
Asymptomatic Diseases epidemiology, Correlation of Data, Female, Heart Conduction System physiopathology, Humans, Male, Middle Aged, Risk Factors, Calcium blood, Cardiovascular Diseases blood, Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology, Cardiovascular Diseases physiopathology, Electrocardiography methods, Electrophysiologic Techniques, Cardiac methods, Magnesium blood, Potassium blood
Abstract

Background: Subclinical changes on the electrocardiogram are risk factors for cardiovascular mortality. Recognition and knowledge of electrolyte associations in cardiac electrophysiology are based on only in vitro models and observations in patients with severe medical conditions., Objectives: This study sought to investigate associations between serum electrolyte concentrations and changes in cardiac electrophysiology in the general population., Methods: Summary results collected from 153,014 individuals (54.4% women; mean age 55.1 ± 12.1 years) from 33 studies (of 5 ancestries) were meta-analyzed. Linear regression analyses examining associations between electrolyte concentrations (mmol/l of calcium, potassium, sodium, and magnesium), and electrocardiographic intervals (RR, QT, QRS, JT, and PR intervals) were performed. The study adjusted for potential confounders and also stratified by ancestry, sex, and use of antihypertensive drugs., Results: Lower calcium was associated with longer QT intervals (-11.5 ms; 99.75% confidence interval [CI]: -13.7 to -9.3) and JT duration, with sex-specific effects. In contrast, higher magnesium was associated with longer QT intervals (7.2 ms; 99.75% CI: 1.3 to 13.1) and JT. Lower potassium was associated with longer QT intervals (-2.8 ms; 99.75% CI: -3.5 to -2.0), JT, QRS, and PR durations, but all potassium associations were driven by use of antihypertensive drugs. No physiologically relevant associations were observed for sodium or RR intervals., Conclusions: The study identified physiologically relevant associations between electrolytes and electrocardiographic intervals in a large-scale analysis combining cohorts from different settings. The results provide insights for further cardiac electrophysiology research and could potentially influence clinical practice, especially the association between calcium and QT duration, by which calcium levels at the bottom 2% of the population distribution led to clinically relevant QT prolongation by >5 ms., (Copyright © 2019 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Published
2019
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10. Adult weight change in relation to visceral fat and liver fat at middle age: The Netherlands epidemiology of obesity study.

Author

Verkouter I, Noordam R, de Roos A, Lamb HJ, Rosendaal FR, van Heemst D, and de Mutsert R

Subjects
Biomarkers, Body Mass Index, Cardiovascular Diseases etiology, Fatty Liver physiopathology, Female, Health Surveys, Humans, Insulin Resistance physiology, Male, Metabolic Diseases etiology, Middle Aged, Neoplasms etiology, Netherlands epidemiology, Obesity complications, Obesity physiopathology, Population Surveillance, Weight Gain, Adiposity physiology, Cardiovascular Diseases epidemiology, Fatty Liver epidemiology, Intra-Abdominal Fat physiology, Metabolic Diseases epidemiology, Neoplasms epidemiology, Obesity epidemiology
Abstract

Objective: We aimed to investigate the associations between weight change during adulthood and the amount of abdominal subcutaneous fat, visceral fat, and liver fat at middle age., Methods: The Netherlands Epidemiology of Obesity (NEO) study is a population-based cohort of 6671 middle-aged men and women. We calculated the percentage of weight change during adulthood based on body weight at middle age and recalled body weight at age 20. Abdominal subcutaneous and visceral adipose tissue were assessed by magnetic resonance imaging (MRI), in addition to hepatic triglyceride content by 1 H-MR spectroscopy in a random subgroup (maximum of n = 2580). With multivariable linear regression analysis, we examined the associations between categories of adult weight change, body mass index (BMI) at age 20 and measures of abdominal adiposity at middle age, adjusted for age, sex, ethnicity, lifestyle factors, menopausal status, parity, use of medication and total body fat at middle age., Results: In 2399 participants (54% women), individuals who gained more than 50% of body weight during adulthood had 1.96 (95% CI: 1.64; 2.33) times more visceral adipose tissue at middle age and 2.39 (95% CI: 1.70, 3.36) times more hepatic triglyceride content than weight maintainers (weight change between -5% and 5%). Associations with abdominal subcutaneous adipose tissue were weaker: participants who gained more than 50% of their body weight had 1.54 (95% CI: 1.38, 1.72) times more abdominal subcutaneous adipose tissue compared with weight maintainers., Conclusions: In this population-based study, adult weight gain was associated with relatively more visceral adipose tissue and hepatic triglyceride content at middle age than abdominal subcutaneous adipose tissue. Overall, our study suggests that weight maintenance during adulthood plays an important role in limiting excess visceral adipose tissue and hepatic triglyceride content at middle age.

Published
2019
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11. The ApoE ε4 Isoform: Can the Risk of Diseases be Reduced by Environmental Factors?

Author

Bos MM, Noordam R, Blauw GJ, Slagboom PE, Rensen PCN, and van Heemst D

Subjects
Alzheimer Disease metabolism, Apolipoprotein E4 metabolism, Cardiovascular Diseases metabolism, Humans, Risk Factors, Aging genetics, Alzheimer Disease genetics, Apolipoprotein E4 genetics, Cardiovascular Diseases genetics, Environmental Exposure adverse effects, Genome-Wide Association Study methods
Abstract

Candidate gene studies and genome-wide association studies found that genetic variation in APOE is robustly associated with multiple age-related diseases and longevity. Apolipoprotein E (ApoE) is an apolipoprotein that plays an important role in triglyceride and cholesterol metabolism. In literature, especially the ApoE ɛ4 isoform has been associated with an increased risk of mortality and age-related diseases such as Alzheimer's disease (AD), cardiovascular diseases (CVD), as compared to the "neutral" ApoE ɛ3 isoform. There are, however, large differences in the deleterious effects of the ApoE ɛ4 isoform between ancestries and populations, which might be explained by differences in environmental and lifestyle exposures. In this respect, poor nutrition and physical inactivity are two important lifestyle factors that have been associated with increased risks for AD and CVD. Therefore, in this narrative review, we discuss how omega-3 fatty acid intake and physical activity may modify the impact of ApoE ɛ4 on AD and CVD risk.

Published
2019
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12. Facial appearance reflects human familial longevity and cardiovascular disease risk in healthy individuals.

Author

Gunn DA, de Craen AJ, Dick JL, Tomlin CC, van Heemst D, Catt SD, Griffiths T, Ogden S, Maier AB, Murray PG, Griffiths CE, Slagboom PE, and Westendorp RG

Subjects
Aged, Aged, 80 and over, Aging pathology, Aging physiology, Blood Pressure, Cardiovascular Diseases pathology, Cardiovascular Diseases physiopathology, Case-Control Studies, Cross-Sectional Studies, Female, Humans, Longevity physiology, Male, Middle Aged, Risk Factors, Sex Characteristics, Siblings, Skin Aging pathology, Cardiovascular Diseases etiology, Facies, Longevity genetics
Abstract

Background: As facial appearance can be readily quantified and skin tissue easily accessed, they could be valuable tools for determining how biological mechanisms influence tissue degeneration with age and, consequently, human health and lifespan. It is unknown, however, whether appearance reflects disease risk or lifespan independently of factors already known to associate with both health and appearance., Methods: In a cross-sectional study, we compared the amount of skin wrinkling on a sun-protected site (upper inner arm) and the facial appearance of 261 offspring (mean age 63.2 y) of nonagenarian siblings with 253 age-matched controls (mean age 62.7 y), all with no reported disease history. We next examined whether any appearance features that significantly associated with familial longevity also associated with the Framingham cardiovascular disease (CVD) risk score. All analyses were adjusted for chronological age, smoking, photodamage, and body mass index., Results: Female and male offspring had reduced upper inner arm skin wrinkling (p = .03 and p < .001, respectively), and the male offspring looked 1.4 y younger than the controls (p = .002). There were no significant associations between CVD risk and upper inner arm skin wrinkling. Women in the lowest quartile of CVD risk looked more than 2 y younger for their age than those in higher risk quartiles (p = .002). Systolic blood pressure was the most significant (p = .004) CVD risk factor that was associated with perceived age in women., Conclusions: Facial appearance and skin wrinkling at a sun-protected site reflect the propensity to reach an extreme old age, and facial appearance reflects the risk of succumbing to CVD independently of chronological age, smoking, photodamage, and BMI.

Published
2013
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13. Plasma levels of apolipoprotein E and cognitive function in old age.

Author

Mooijaart SP, van Vliet P, van Heemst D, Rensen PC, Berbée JF, Jolles J, de Craen AJ, and Westendorp RG

Subjects
Aged, Aged, 80 and over, Cerebrovascular Disorders genetics, Cerebrovascular Disorders mortality, Cholesterol metabolism, Female, Genotype, Humans, Male, Neuropsychological Tests, Risk Factors, Aging, Apolipoproteins E genetics, Cardiovascular Diseases genetics, Cognition Disorders genetics, Dementia genetics
Abstract

The relationship between structural variants of the apolipoprotein E gene, APOE epsilon2/epsilon3/epsilon4, and dementia is well established, whereas the relationship of plasma apoE levels with dementia is less clear. Plasma apoE levels are under tight genetic control but vary widely within the various genotypes indicating that the APOE epsilon2/epsilon3/epsilon4 locus explains only a small fraction of this variation. Here we studied the association of plasma apolipoprotein E (apoE) levels with cognitive function in the elderly population at large. Within the Leiden 85-plus Study, a prospective population-based study of subjects aged 85 years, we measured plasma apoE level and genotype at base line. During a 5-year follow-up period, cognitive function was annually assessed using the Mini Mental State Examination (MMSE) and a standardized neuropsychological test battery. Among epsilon3epsilon3 carriers (n = 324), high plasma apoE levels associated with impaired global cognitive function (-1.10 points change in MMSE score per one standard deviation increase of plasma apoE level, P = 0.001), as well as lower attention (P = 0.064), speed and memory function (all P < 0.05). Adjustment for cardiovascular risk factors and exclusion of all subjects who suffered a stroke did not materially change the associations. Similar estimates were obtained in epsilon3epsilon4 carriers (n = 100), but not in epsilon2epsilon3 carriers (n = 90). We conclude that in old age, in non-epsilon2-allele carriers, high plasma apoE levels are associated with cognitive impairments, independent of genotype, cardiovascular risk factors, and stroke.

Published
2007
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14. Genetic variants in the glucocorticoid receptor gene (NR3C1) and cardiovascular disease risk. The Leiden 85-plus Study.

Author

Kuningas M, Mooijaart SP, Slagboom PE, Westendorp RG, and van Heemst D

Subjects
Age Distribution, Aged, 80 and over, Female, Genetic Predisposition to Disease epidemiology, Heterozygote, Humans, Incidence, Male, Netherlands epidemiology, Risk Assessment methods, Risk Factors, Survival Analysis, Survival Rate, Apolipoproteins E genetics, Cardiovascular Diseases genetics, Cardiovascular Diseases mortality, Genetic Testing methods, Genetic Variation genetics, Polymorphism, Single Nucleotide genetics, Receptors, Glucocorticoid genetics
Abstract

Recently, the ER22/23EK, N363S and BclI polymorphisms in the glucocorticoid receptor (GR) gene have been linked to altered cortisol sensitivity and to cortisol-associated disorders. The aim of this study was to investigate the effect of these genetic variants in the GR gene on cardiovascular disease and mortality in elderly persons aged 85 years and over. In the population-based Leiden 85-plus Study, 552 participants were genotyped for the ER22/23EK, N363S and BclI polymorphisms, and the effects of the polymorphisms on metabolic profile, body composition, and on the prevalence of cardiovascular pathologies at baseline, were assessed. Allcause and cardiovascular disease mortality risks dependent on the SNPs were calculated after a 4.2-year follow-up. The analyses of metabolic profile revealed that carriers of the ER22/23EK polymorphism have higher HbA1C levels (P<0.001) and carriers of the N363S SNP have higher LDL cholesterol (P<0.001) and triglyceride concentrations (P=0.03), compared to the non-carriers. The only significant association between genotype and body composition analyses was for height and the ER22/23EK polymorphism. Men carrying the ER22/23EK polymorphism were taller (P=0.02) compared to non-carriers. No associations with cardiovascular pathologies, allcause and cardiovascular mortality were observed for any of the polymorphisms. We conclude that, in spite the effect of the ER22/23EK and N363S SNPs on metabolism, these polymorphisms together with the BclI SNP, do not affect the risks of cardiovascular disease and survival at old age.

Published
2006
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15. ApoE plasma levels and risk of cardiovascular mortality in old age.

Author

Mooijaart SP, Berbée JF, van Heemst D, Havekes LM, de Craen AJ, Slagboom PE, Rensen PC, and Westendorp RG

Subjects
Age Factors, Aged, 80 and over, Apolipoproteins E genetics, C-Reactive Protein metabolism, Cardiovascular Diseases etiology, Female, Follow-Up Studies, Genotype, Humans, Lipids blood, Male, Proportional Hazards Models, Protein Isoforms blood, Protein Isoforms genetics, Risk Factors, Survival Rate, Apolipoproteins E blood, Cardiovascular Diseases blood, Cardiovascular Diseases mortality
Abstract

Background: The epsilon2, epsilon3, and epsilon4 alleles of the apolipoprotein E gene (APOE) encode three isoforms, apoE2, E3, and E4, respectively. The apoE isoforms circulate in different plasma concentrations, but plasma concentrations of the same isoform also differ between individuals. Whereas the isoforms have been associated with cardiovascular disease, the relation between plasma apoE levels and cardiovascular disease is unknown., Methods and Findings: We assessed APOE genotypes, plasma levels of apoE, cardiovascular risk factors, and mortality in a population-based sample of 546 individuals aged 85 y who participated in the Leiden 85-plus Study and were prospectively followed for specific causes of death for 5 y. Participants in the highest tertile of apoE levels suffered a twofold-increased risk of cardiovascular mortality (hazard ratio compared to lowest tertile, 2.08; 95% confidence interval [CI], 1.30 to 3.33). Among the 324 participants with the epsilon3epsilon3 genotype, the hazard from cardiovascular disease was threefold increased (highest versus lowest tertile 3.01; 95% CI 1.60 to 5.66), with similar estimates for men and women. Other causes of death were not increased significantly. Plasma levels of apoE in epsilon3epsilon3 participants were positively correlated with total cholesterol (p < 0.001), low-density lipoprotein cholesterol (p < 0.001) and triglycerides (p < 0.001) and negatively with high-density lipoprotein cholesterol levels (p = 0.010). Adjustment for plasma lipids did not change the hazard ratios, whereas interaction was absent. The risk associated with high levels of apoE, however, was strongest in participants from the lowest tertile of C-reactive protein (CRP) levels and absent in those from the highest tertile (p(interaction) < 0.001). Among participants from the lowest tertile of CRP levels, those with a high apoE levels had a significantly steeper increase in CRP than those with low apoE levels (p = 0.020). Similar cardiovascular mortality risks as in epsilon3epsilon3 participants were found in epsilon2 and epsilon4 carriers., Conclusions: In old age, high plasma apoE levels precede an increase of circulating CRP and strongly associates with cardiovascular mortality, independent of APOE genotype and plasma lipids.

Published
2006
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18. Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids

Author

Bentley, Amy R, Sung, Yun J, Brown, Michael R, Winkler, Thomas W, Kraja, Aldi T, Ntalla, Ioanna, Schwander, Karen, Chasman, Daniel I, Lim, Elise, Deng, Xuan, Guo, Xiuqing, Liu, Jingmin, Lu, Yingchang, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Huffman, Jennifer E, Musani, Solomon K, Li, Changwei, Feitosa, Mary F, Richard, Melissa A, Noordam, Raymond, Baker, Jenna, Chen, Guanjie, Aschard, Hugues, Bartz, Traci M, Ding, Jingzhong, Dorajoo, Rajkumar, Manning, Alisa K, Rankinen, Tuomo, Smith, Albert V, Tajuddin, Salman M, Zhao, Wei, Graff, Mariaelisa, Alver, Maris, Boissel, Mathilde, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Evangelou, Evangelos, Gao, Chuan, Goel, Anuj, Hagemeijer, Yanick, Harris, Sarah E, Hartwig, Fernando P, He, Meian, Horimoto, Andrea RVR, Hsu, Fang-Chi, Hung, Yi-Jen, Jackson, Anne U, Kasturiratne, Anuradhani, Komulainen, Pirjo, Kuehnel, Brigitte, Leander, Karin, Lin, Keng-Hung, Luan, Jian'an, Lyytikainen, Leo-Pekka, Matoba, Nana, Nolte, Ilja M, Pietzner, Maik, Prins, Bram, Riaz, Muhammad, Robino, Antonietta, Said, M Abdullah, Schupf, Nicole, Scott, Robert A, Sofer, Tamar, Stancakova, Alena, Takeuchi, Fumihiko, Tayo, Bamidele O, van der Most, Peter J, Varga, Tibor V, Wang, Tzung-Dau, Wang, Yajuan, Ware, Erin B, Wen, Wanqing, Xiang, Yong-Bing, Yanek, Lisa R, Zhang, Weihua, Zhao, Jing Hua, Adeyemo, Adebowale, Afaq, Saima, Amin, Najaf, Amini, Marzyeh, Arking, Dan E, Arzumanyan, Zorayr, Aung, Tin, Ballantyne, Christie, Barr, R Graham, Bielak, Lawrence F, Boerwinkle, Eric, Bottinger, Erwin P, Broeckel, Ulrich, Brown, Morris, Cade, Brian E, Campbell, Archie, Canouil, Mickael, Charumathi, Sabanayagam, Chen, Yii-Der Ida, Christensen, Kaare, Concas, Maria Pina, Connell, John M, de las Fuentes, Lisa, de Silva, H Janaka, de Vries, Paul S, Doumatey, Ayo, Duan, Qing, Eaton, Charles B, Eppinga, Ruben N, Faul, Jessica D, Floyd, James S, Forouhi, Nita G, Forrester, Terrence, Friedlander, Yechiel, Gandin, Ilaria, Gao, He, Ghanbari, Mohsen, Gharib, Sina A, Gigante, Bruna, Giulianini, Franco, Grabe, Hans J, Gu, C Charles, Harris, Tamara B, Heikkinen, Sami, Heng, Chew-Kiat, Hirata, Makoto, Hixson, James E, Ikram, M Arfan, Jia, Yucheng, Joehanes, Roby, Johnson, Craig, Jonas, Jost Bruno, Justice, Anne E, Katsuya, Tomohiro, Khor, Chiea Chuen, Kilpelainen, Tuomas O, Koh, Woon-Puay, Kolcic, Ivana, Kooperberg, Charles, Krieger, Jose E, Kritchevsky, Stephen B, Kubo, Michiaki, Kuusisto, Johanna, Lakka, Timo A, Langefeld, Carl D, Langenberg, Claudia, Launer, Lenore J, Lehne, Benjamin, Lewis, Cora E, Li, Yize, Liang, Jingjing, Lin, Shiow, Liu, Ching-Ti, Liu, Jianjun, Liu, Kiang, Loh, Marie, Lohman, Kurt K, Louie, Tin, Luzzi, Anna, Magi, Reedik, Mahajan, Anubha, Manichaikul, Ani W, McKenzie, Colin A, Meitinger, Thomas, Metspalu, Andres, Milaneschi, Yuri, Milani, Lili, Mohlke, Karen L, Momozawa, Yukihide, Morris, Andrew P, Murray, Alison D, Nalls, Mike A, Nauck, Matthias, Nelson, Christopher P, North, Kari E, O'Connell, Jeffrey R, Palmer, Nicholette D, Papanicolau, George J, Pedersen, Nancy L, Peters, Annette, Peyser, Patricia A, Polasek, Ozren, Poulter, Neil, Raitakari, Olli T, Reiner, Alex P, Renstrom, Frida, Rice, Treva K, Rich, Stephen S, Robinson, Jennifer G, Rose, Lynda M, Rosendaal, Frits R, Rudan, Igor, Schmidt, Carsten O, Schreiner, Pamela J, Scott, William R, Sever, Peter, Shi, Yuan, Sidney, Stephen, Sims, Mario, Smith, Jennifer A, Snieder, Harold, Starr, John M, Strauch, Konstantin, Stringham, Heather M, Tan, Nicholas YQ, Tang, Hua, Taylor, Kent D, Teo, Yik Ying, Tham, Yih Chung, Tiemeier, Henning, Turner, Stephen T, Uitterlinden, Andre G, van Heemst, Diana, Waldenberger, Melanie, Wang, Heming, Wang, Lan, Wang, Lihua, Wei, Wen Bin, Williams, Christine A, Sr, Wilson Gregory, Wojczynski, Mary K, Yao, Jie, Young, Kristin, Yu, Caizheng, Yuan, Jian-Min, Zhou, Jie, Zonderman, Alan B, Becker, Diane M, Boehnke, Michael, Bowden, Donald W, Chambers, John C, Cooper, Richard S, de Faire, Ulf, Deary, Ian J, Elliott, Paul, Esko, Tonu, Farrall, Martin, Franks, Paul W, Freedman, Barry I, Froguel, Philippe, Gasparini, Paolo, Gieger, Christian, Horta, Bernardo L, Juang, Jyh-Ming Jimmy, Kamatani, Yoichiro, Kammerer, Candace M, Kato, Norihiro, Kooner, Jaspal S, Laakso, Markku, Laurie, Cathy C, Lee, I-Te, Lehtimaki, Terho, Magnusson, Patrik KE, Oldehinkel, Albertine J, Penninx, Brenda WJH, Pereira, Alexandre C, Rauramaa, Rainer, Redline, Susan, Samani, Nilesh J, Scott, James, Shu, Xiao-Ou, van der Harst, Pim, Wagenknecht, Lynne E, Wang, Jun-Sing, Wang, Ya Xing, Wareham, Nicholas J, Watkins, Hugh, Weir, David R, Wickremasinghe, Ananda R, Wu, Tangchun, Zeggini, Eleftheria, Zheng, Wei, Bouchard, Claude, Evans, Michele K, Gudnason, Vilmundur, Kardia, Sharon LR, Liu, Yongmei, Psaty, Bruce M, Ridker, Paul M, van Dam, Rob M, Mook-Kanamori, Dennis O, Fornage, Myriam, Province, Michael A, Kelly, Tanika N, Fox, Ervin R, Hayward, Caroline, van Duijn, Cornelia M, Tai, E Shyong, Wong, Tien Yin, Loos, Ruth JF, Franceschini, Nora, Rotter, Jerome I, Zhu, Xiaofeng, Bierut, Laura J, Gauderman, W James, Rice, Kenneth, Munroe, Patricia B, Morrison, Alanna C, Rao, Dabeeru C, Rotimi, Charles N, Cupples, L Adrienne, Consortium, COGENT-Kidney, Consortium, EPIC-InterAct, Grp, Understanding Soc Sci, Cohort, Lifelines, National Institutes of Health [Bethesda] (NIH), Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), The University of Texas Health Science Center at Houston (UTHealth), Universität Regensburg (UR), Queen Mary University of London (QMUL), Brigham and Women's Hospital [Boston], Harvard Medical School [Boston] (HMS), School of Public Health [Boston], Boston University [Boston] (BU), Los Angeles Biomedical Research Institute (LA BioMed), Fred Hutchinson Cancer Research Center [Seattle] (FHCRC), Icahn School of Medicine at Mount Sinai [New York] (MSSM), Singapore Eye Research Institute [Singapore] (SERI), Duke-NUS Medical School [Singapore], National University of Singapore (NUS), Erasmus University Medical Center [Rotterdam] (Erasmus MC), University of Edinburgh, University of Mississippi Medical Center (UMMC), University of Georgia [USA], Leiden University Medical Center (LUMC), Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Harvard T.H. Chan School of Public Health, University of Washington [Seattle], Wake Forest University, Genome Institute of Singapore (GIS), Massachusetts General Hospital [Boston], Pennington Biomedical Research Center, Louisiana State University (LSU), Icelandic Heart Association [Kopavogur, Iceland] (IHA), University of Iceland [Reykjavik], University of Michigan [Ann Arbor], University of Michigan System, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), University of Tartu, Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (GI3M), 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), Karolinska Institutet [Stockholm], Wake Forest School of Medicine [Winston-Salem], Wake Forest Baptist Medical Center, Imperial College London, University of Ioannina, University of Oxford [Oxford], University of Groningen [Groningen], Universidade Federal de Pelotas = Federal University of Pelotas (UFPel), University of Bristol [Bristol], Huazhong University of Science and Technology [Wuhan] (HUST), Universidade de São Paulo Medical School (FMUSP), Case Western Reserve University [Cleveland], University of Southern California (USC), This project was largely supported by a grant from the US National Heart, Lung, and Blood Institute of the National Institutes of Health (R01HL118305) and by the Intramural Research Program of the National Human Genome Research Institute of the National Institutes of Health through the Center for Research on Genomics and Global Health (CRGGH). The CRGGH is supported by the National Human Genome Research Institute, the National Institute of Diabetes and Digestive and Kidney Diseases, the Center for Information Technology, and the Office of the Director at the National Institutes of Health (Z01HG200362)., Bentley, Ar, Sung, Yj, Brown, Mr, Winkler, Tw, Kraja, At, Ntalla, I, Schwander, K, Chasman, Di, Lim, E, Deng, X, Guo, X, Liu, J, Lu, Y, Cheng, Cy, Sim, X, Vojinovic, D, Huffman, Je, Musani, Sk, Li, C, Feitosa, Mf, Richard, Ma, Noordam, R, Baker, J, Chen, G, Aschard, H, Bartz, Tm, Ding, J, Dorajoo, R, Manning, Ak, Rankinen, T, Smith, Av, Tajuddin, Sm, Zhao, W, Graff, M, Alver, M, Boissel, M, Chai, Jf, Chen, X, Divers, J, Evangelou, E, Gao, C, Goel, A, Hagemeijer, Y, Harris, Se, Hartwig, Fp, He, M, Horimoto, Arvr, Hsu, Fc, Hung, Yj, Jackson, Au, Kasturiratne, A, Komulainen, P, Kühnel, B, Leander, K, Lin, Kh, Luan, J, Lyytikäinen, Lp, Matoba, N, Nolte, Im, Pietzner, M, Prins, B, Riaz, M, Robino, A, Said, Ma, Schupf, N, Scott, Ra, Sofer, T, Stancáková, A, Takeuchi, F, Tayo, Bo, van der Most, Pj, Varga, Tv, Wang, Td, Wang, Y, Ware, Eb, Wen, W, Xiang, Yb, Yanek, Lr, Zhang, W, Zhao, Jh, Adeyemo, A, Afaq, S, Amin, N, Amini, M, Arking, De, Arzumanyan, Z, Aung, T, Ballantyne, C, Barr, Rg, Bielak, Lf, Boerwinkle, E, Bottinger, Ep, Broeckel, U, Brown, M, Cade, Be, Campbell, A, Canouil, M, Charumathi, S, Chen, Yi, Christensen, K, COGENT-Kidney, Consortium, Concas, Mp, Connell, Jm, de Las Fuentes, L, de Silva, Hj, de Vries, P, Doumatey, A, Duan, Q, Eaton, Cb, Eppinga, Rn, Faul, Jd, Floyd, J, Forouhi, Ng, Forrester, T, Friedlander, Y, Gandin, I, Gao, H, Ghanbari, M, Gharib, Sa, Gigante, B, Giulianini, F, Grabe, Hj, Gu, Cc, Harris, Tb, Heikkinen, S, Heng, Ck, Hirata, M, Hixson, Je, Ikram, Ma, EPIC-InterAct, Consortium, Jia, Y, Joehanes, R, Johnson, C, Jonas, Jb, Justice, Ae, Katsuya, T, Khor, Cc, Kilpeläinen, To, Koh, Wp, Kolcic, I, Kooperberg, C, Krieger, Je, Kritchevsky, Sb, Kubo, M, Kuusisto, J, Lakka, Ta, Langefeld, Cd, Langenberg, C, Launer, Lj, Lehne, B, Lewis, Ce, Li, Y, Liang, J, Lin, S, Liu, Ct, Liu, K, Loh, M, Lohman, Kk, Louie, T, Luzzi, A, Mägi, R, Mahajan, A, Manichaikul, Aw, Mckenzie, Ca, Meitinger, T, Metspalu, A, Milaneschi, Y, Milani, L, Mohlke, Kl, Momozawa, Y, Morris, Ap, Murray, Ad, Nalls, Ma, Nauck, M, Nelson, Cp, North, Ke, O'Connell, Jr, Palmer, Nd, Papanicolau, Gj, Pedersen, Nl, Peters, A, Peyser, Pa, Polasek, O, Poulter, N, Raitakari, Ot, Reiner, Ap, Renström, F, Rice, Tk, Rich, S, Robinson, Jg, Rose, Lm, Rosendaal, Fr, Rudan, I, Schmidt, Co, Schreiner, Pj, Scott, Wr, Sever, P, Shi, Y, Sidney, S, Sims, M, Smith, Ja, Snieder, H, Starr, Jm, Strauch, K, Stringham, Hm, Tan, Nyq, Tang, H, Taylor, Kd, Teo, Yy, Tham, Yc, Tiemeier, H, Turner, St, Uitterlinden, Ag, Understanding Society Scientific, Group, van Heemst, D, Waldenberger, M, Wang, H, Wang, L, Wei, Wb, Williams, Ca, Wilson, G Sr, Wojczynski, Mk, Yao, J, Young, K, Yu, C, Yuan, Jm, Zhou, J, Zonderman, Ab, Becker, Dm, Boehnke, M, Bowden, Dw, Chambers, Jc, Cooper, R, de Faire, U, Deary, Ij, Elliott, P, Esko, T, Farrall, M, Franks, Pw, Freedman, Bi, Froguel, P, Gasparini, P, Gieger, C, Horta, Bl, Juang, Jj, Kamatani, Y, Kammerer, Cm, Kato, N, Kooner, J, Laakso, M, Laurie, Cc, Lee, It, Lehtimäki, T, Lifelines, Cohort, Magnusson, Pke, Oldehinkel, Aj, Penninx, Bwjh, Pereira, Ac, Rauramaa, R, Redline, S, Samani, Nj, Scott, J, Shu, Xo, van der Harst, P, Wagenknecht, Le, Wang, J, Wang, Yx, Wareham, Nj, Watkins, H, Weir, Dr, Wickremasinghe, Ar, Wu, T, Zeggini, E, Zheng, W, Bouchard, C, Evans, Mk, Gudnason, V, Kardia, Slr, Liu, Y, Psaty, Bm, Ridker, Pm, van Dam, Rm, Mook-Kanamori, Do, Fornage, M, Province, Ma, Kelly, Tn, Fox, Er, Hayward, C, van Duijn, Cm, Tai, E, Wong, Ty, Loos, Rjf, Franceschini, N, Rotter, Ji, Zhu, X, Bierut, Lj, Gauderman, Wj, Rice, K, Munroe, Pb, Morrison, Ac, Rao, Dc, Rotimi, Cn, Cupples, La., Luan, Jian'an [0000-0003-3137-6337], Pietzner, Maik [0000-0003-3437-9963], 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, Epidemiology, Neurology, Radiology & Nuclear Medicine, Internal Medicine, Life Course Epidemiology (LCE), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Cardiovascular Centre (CVC), Home Office, Action on Hearing Loss, Imperial College Healthcare NHS Trust- BRC Funding, Medical Research Council (MRC), Universiteit Leiden, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (EGENODIA (GI3M)), University of Oxford, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, APH - Mental Health, and APH - Digital Health

Subjects
Male, Linkage disequilibrium, Blood lipids, Genome-wide association study, VARIANTS, SUSCEPTIBILITY, Environment interaction, Genome, Linkage Disequilibrium, MESH: Genotype, 0302 clinical medicine, MESH: Aged, 80 and over, Genotype, NICOTINE METABOLISM, 11 Medical and Health Sciences, Genetics & Heredity, Aged, 80 and over, Genetics, MESH: Aged, 0303 health sciences, ARCHITECTURE, [STAT.AP]Statistics [stat]/Applications [stat.AP], Genotype imputation, MESH: Middle Aged, CHOLESTEROL, Smoking, MESH: Life Style, Lifelines Cohort, Middle Aged, Lipids, 3. Good health, ENVIRONMENT INTERACTION, GENOTYPE IMPUTATION, RISK LOCI, METAANALYSIS, CIGARETTES, Cholesterol, MESH: Linkage Disequilibrium, MESH: Young Adult, Meta-analysis, Genome-Wide Association Study/methods, Smoking/blood, Medical genetics, Female, EPIC-InterAct Consortium, Life Sciences & Biomedicine, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Adult, Metaanalysi, Understanding Society Scientific Group, medicine.medical_specialty, MESH: Smoking, Adolescent, Genomics, COGENT-Kidney Consortium, Biology, Nicotine metabolism, Risk loci, Metaanalysis, Cigarettes, Article, Young Adult, 03 medical and health sciences, genomics, medicine, Humans, Linkage Disequilibrium/genetics, Life Style, Aged, 030304 developmental biology, MESH: Adolescent, Science & Technology, MESH: Humans, Lipids/blood, MESH: Adult, 06 Biological Sciences, MESH: Lipids, MESH: Male, cardiovascular diseases, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, genome-wide association studies, MESH: Genome-Wide Association Study, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], MESH: Female, 030217 neurology & neurosurgery, Developmental Biology, Genome-Wide Association Study
Abstract

The concentrations of high- and low-density lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 novel loci, some of which were detected only because the association differed by smoking status. Additionally, we demonstrated the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings., Editorial summary: A multi-ancestry genome-wide gene-smoking interaction study identifies 13 new loci associated with serum lipids.

Published
2019

19. Effects of Calcium, Magnesium, and Potassium concentrations on ventricular repolarization in unselected individuals

Author

Pedro Guatimosim Vidigal, Yongmei Liu, Alice Stanton, Kent D. Taylor, Thomas Meitinger, Vilmundur Gudnason, Massimo Mangino, Mario Pirastu, Nilesh J. Samani, Christopher Newton-Cheh, Xiuqing Guo, Bruno H. Stricker, Mortiz F. Sinner, Steven R. Cummings, Jennifer A. Brody, Antonio Luiz Pinho Ribeiro, Mark J. Caulfield, Bryan Kestenbaum, Dennis O. Mook-Kanamori, Jørgen K. Kanters, Kirill V. Tarasov, Martina Müller-Nurasyid, Luana Giatti, Elsayed Z. Soliman, Christian R. Juhl, Nuno R. Zilhão, Harold Snieder, Eric Campana, Mika Kähönen, Ginevra Biino, Raymond Noordam, Jun Ding, Chris H. L. Thio, Jerome I. Rotter, Torben Hansen, M. Abdullah Said, Francesco Cucca, Allan Linneberg, Nona Sotoodehnia, Niels Grarup, Peter S. Sever, James F. Wilson, André G. Uitterlinden, Xia Shen, Luisa Foco, Yong Qian, Christina Ellervik, Diana van Heemst, Antonietta Robino, Henry J. Lin, Konstantin Strauch, Patricia B. Munroe, Nabi Shah, Claus Graff, Daniel S. Evans, Peter J. van der Most, Stefan Weiss, Maria Pina Concas, Reem Salman, Hao Mei, Linda Repetto, Helen R. Warren, Peter K. Joshi, Susan R. Heckbert, Tim D. Spector, Sandhi Maria Barreto, Jie Yao, Marcus Dörr, Eulalia Catamo, Anna F. Dominiczak, Leo-Pekka Lyytikäinen, Giorgia Girotto, Peter P. Pramstaller, Gudny Eiriksdottir, J. Wouter Jukema, Paulo A. Lotufo, Colin N. A. Palmer, Andrew Tinker, James G. Wilson, Mary L. Biggs, Astrid Petersmann, Arie C. Maan, Peter S. Braund, Maria Fernanda Lima-Costa, Paraskevi Christofidou, Sandosh Padmanabhan, Adolfo Correa, Melanie Waldenberger, Alessandro De Grandi, Stefan Kääb, Cristian Pattaro, Annette Peters, William J Young, Alex S. F. Doney, Katharina Schramm, Terho Lehtimäki, Christopher P. Nelson, Martin Gögele, Marten E. van den Berg, Marco Brumat, Pim van der Harst, Niek Verweij, Simona Vaccargiu, Noordam, R, Young, Wj, Salman, R, Kanters, Jk, van den Berg, Me, van Heemst, D, Lin, Hj, Barreto, Sm, Biggs, Ml, Biino, G, Catamo, E, Concas, Mp, Ding, J, Evans, D, Foco, L, Grarup, N, Lyytikäinen, Lp, Mangino, M, Mei, H, van der Most, Pj, Müller-Nurasyid, M, Nelson, Cp, Qian, Y, Repetto, L, Said, Ma, Shah, N, Schramm, K, Vidigal, Pg, Weiss, S, Yao, J, Zilhao, Nr, Brody, Ja, Braund, P, Brumat, M, Campana, E, Christofidou, P, Caulfield, Mj, De Grandi, A, Dominiczak, Af, Doney, Asf, Eiriksdottir, G, Ellervik, C, Giatti, L, Gögele, M, Graff, C, Guo, X, van der Harst, P, Joshi, Pk, Kähönen, M, Kestenbaum, B, Lima-Costa, Mf, Linneberg, A, Maan, Ac, Meitinger, T, Padmanabhan, S, Pattaro, C, Peters, A, Petersmann, A, Sever, P, Sinner, Mf, Shen, X, Stanton, A, Strauch, K, Soliman, Ez, Tarasov, Kv, Taylor, Kd, Thio, Chl, Uitterlinden, Ag, Vaccargiu, S, Waldenberger, M, Robino, A, Correa, A, Cucca, F, Cummings, Sr, Dörr, M, Girotto, G, Gudnason, V, Hansen, T, Heckbert, Sr, Juhl, Cr, Kääb, S, Lehtimäki, T, Liu, Y, Lotufo, Pa, Palmer, Cna, Pirastu, M, Pramstaller, Pp, Ribeiro, Alp, Rotter, Ji, Samani, Nj, Snieder, H, Spector, Td, Stricker, Bh, Verweij, N, Wilson, Jf, Wilson, Jg, Jukema, Jw, Tinker, A, Newton-Cheh, Ch, Sotoodehnia, N, Mook-Kanamori, Do, Munroe, Pb, Warren, Hr., Cardiovascular Centre (CVC), Life Course Epidemiology (LCE), and Epidemiology

Subjects
Male, Cardiac & Cardiovascular Systems, 030204 cardiovascular system & hematology, ELECTROCARDIOGRAM, Electrocardiography, 0302 clinical medicine, cohort studies, Risk Factors, Medicine, Magnesium, 030212 general & internal medicine, Correlation of Data, 1102 Cardiorespiratory Medicine and Haematology, RISK, education.field_of_study, medicine.diagnostic_test, ACTION-POTENTIAL DURATION, ASSOCIATION, Middle Aged, COUNCIL, electrocardiographic intervals, Cardiovascular Diseases, Cardiology, Female, epidemiology, Electrical conduction system of the heart, Cardiology and Cardiovascular Medicine, Electrophysiologic Techniques, Cardiac, Life Sciences & Biomedicine, medicine.medical_specialty, Population, electrolytes epidemiology, meta-analysis, chemistry.chemical_element, electrolytes, Calcium, QT interval, 1117 Public Health and Health Services, 03 medical and health sciences, QRS complex, DISPERSION, Heart Conduction System, Internal medicine, Humans, PR interval, education, Science & Technology, Cohort Studies, Electrocardiographic Intervals, Electrolytes, Epidemiology, Meta-analysis, business.industry, QT INTERVAL, RESTING HEART-RATE, Confidence interval, REDUCTION, chemistry, Cardiovascular System & Hematology, CONDUCTION, Asymptomatic Diseases, Potassium, Cardiovascular System & Cardiology, electrocardiographic interval, business, cohort studie
Abstract

BACKGROUND Subclinical changes on the electrocardiogram are risk factors for cardiovascular mortality. Recognition and knowledge of electrolyte associations in cardiac electrophysiology are based on only in vitro models and observations in patients with severe medical conditions.OBJECTIVES This study sought to investigate associations between serum electrolyte concentrations and changes in cardiac electrophysiology in the general population.METHODS Summary results collected from 153,014 individuals (54.4% women; mean age 55.1 +/- 12.1 years) from 33 studies (of 5 ancestries) were meta-analyzed. Linear regression analyses examining associations between electrolyte concentrations (mmol/l of calcium, potassium, sodium, and magnesium), and electrocardiographic intervals (RR, QT, QRS, JT, and PR intervals) were performed. The study adjusted for potential confounders and also stratified by ancestry, sex, and use of antihypertensive drugs.RESULTS Lower calcium was associated with longer QT intervals (-11.5 ms; 99.75% confidence interval [CI]: -13.7 to -9.3) and JT duration, with sex-specific effects. In contrast, higher magnesium was associated with longer QT intervals (7.2 ms; 99.75% CI: 1.3 to 13.1) and JT. Lower potassium was associated with longer QT intervals (-2.8 ms; 99.75% CI: -3.5 to -2.0), JT, QRS, and PR durations, but all potassium associations were driven by use of antihypertensive drugs. No physiologically relevant associations were observed for sodium or RR intervals.CONCLUSIONS The study identified physiologically relevant associations between electrolytes and electrocardiographic intervals in a large-scale analysis combining cohorts from different settings. The results provide insights for further cardiac electrophysiology research and could potentially influence clinical practice, especially the association between calcium and QT duration, by which calcium levels at the bottom 2% of the population distribution led to clinically relevant QT prolongation by >5 ms. (C) 2019 by the American College of Cardiology Foundation.

Published
2019

20. Genome-wide association meta-analysis of human longevity identifies a novel locus conferring survival beyond 90 years of age

Author

Doris Lechner, Miriam Capri, Stefan Böhringer, Stefan Schreiber, Gonneke Willemsen, Paolo Garagnani, Irene Maeve Rea, Andres Metspalu, Palmi V. Jonsson, Thomas B. L. Kirkwood, Lene Christiansen, Fernando Rivadeneira, Giuseppina Rose, J. Wouter Jukema, Serena Dato, Owen A. Ross, Almut Nebel, Cornelia M. van Duijn, Gary Saunders, Bernard Jeune, David J. Stott, Jeanine J. Houwing-Duistermaat, A. Murphy, Anton J. M. de Craen, Friederike Flachsbart, Karen Andersen-Ranberg, Albert Hofman, Ian Ford, Ellen A. Nohr, Giuseppe Passarino, Krista Fischer, Elisa Cevenini, Carmen Martin-Ruiz, Jutta Gampe, Iris Postmus, Christopher P. Nelson, Stefano Salvioli, Alberto Montesanto, Mark Lathrop, Marianne Nygaard, Marie E. Breen, Jennifer Harrow, Hae-Won Uh, Erik B. van den Akker, Thorkild I. A. Sørensen, André G. Uitterlinden, Alexander Viktorin, Bastiaan T. Heijmans, Susan E. McNerlan, Quinta Helmer, Naveed Sattar, Claudio Franceschi, Eco J. C. de Geus, E. Mihailov, Jouke-Jan Hottenga, Qihua Tan, Kari Stefansson, Yoichiro Kamatani, Paolina Crocco, Henning Tiemeier, Stella Trompet, Patrik K. E. Magnusson, Marian Beekman, Riin Tamm, Amke Caliebe, Maris Alver, Femke-Anouska Heinsen, Pilar Galan, Daníel F. Guðbjartsson, Joris Deelen, Linda Broer, Ruud van der Breggen, Kristin L. Ayers, Anna M. Bennet, Dorret I. Boomsma, P. Eline Slagboom, Kaare Christensen, Diana van Heemst, Joanna Collerton, Karen Davies, Rudi G. J. Westendorp, Hélène Blanché, Lavinia Paternoster, Nilesh J. Samani, Hreinn Stefansson, Simon P. Mooijaart, Heather J. Cordell, Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Netherlands Consortium for Healthy Aging [Leiden, Netherlands] (NCHA), LeidenUniversity Medical Centre, Department of Epidemiology, The Netherlands Cancer Institute, Institute of Genetic Medicine, Newcastle University [Newcastle], National Institute of Public Health, University of Southern Denmark (SDU), Department of Clinical Genetics, Odense University Hospital, Fondation Jean Dausset - Centre d’Étude du Polymorphisme Humain, Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet [Stockholm], University of Tartu, Institute of Molecular and Cell Biology, Department of Gerontology and Geriatrics, Leiden University Medical Center (LUMC), deCODE genetics [Reykjavik], Christian-Albrechts University of Kiel, University of Calabria, Delft University of Technology (TU Delft), Department of Cardiovascular Sciences, Université Catholique de Louvain = Catholic University of Louvain (UCL), University Hospitals Leicester, Genome Campus, The Wellcome Trust Sanger Institute [Cambridge], School of Medicine, Dentistry and Biomedical Sciences [Belfast], Queen's University [Belfast] (QUB), University of Iowa [Iowa City], DIMES: Department of Experimental, Diagnostic and Specialty Medicine, Bologna University Hospital, Institute for Ageing and Health, University of Glasgow, Max Planck Institute for Demographic Research (MPIDR), Max-Planck-Gesellschaft, Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), EMGO Institute for Health and Care Research, VU University Amsterdam Medical Center, Landspitali National University Hospital of Iceland, University of Iceland, McGill University = Université McGill [Montréal, Canada], Genome Quebec Innovation Centre, Institut de Génomique, Belfast Health and Social Care Trust, Estonian Biocentre, Partenaires INRAE, Aarhus University [Aarhus], School of Social and Community Medicine, Erasmus University Rotterdam, Mayo Clinic, BHF Glasgow Cardiovascular Research Centre, University Medical Center Schleswig-Holstein, Institute of Cardiovascular and Medical Sciences, Sophia Children's Hospital, Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA), Augustinus Foundation, Avera Institute for Human Genetics (AIHG), AXA Research Fund, Belfast City Hospital Trust Fund, Biobanking and Biomolecular Resources Research Infrastructure (BBMRI -NL) [184.021.007], Biotechnology and Biological Sciences Research Council (BBSRC), Bristol-Myers Squibb, Center for Inherited Disease Research (CIDR), Centre for Medical Systems Biology (CMSB), CERA Foundation, Commissariat a L'Energie Atomique (CEA)-Centre National de Genotypage (CNG), Danish Agency for Science, Technology and Innovation (DASTI)/The Danish Council for Independent Research (DCIR) [11-107308], Danish National Research Foundation (DNRF), Department of Health and Social Services (Northern Ireland), DFG-Cluster of Excellence 'Inflammation at Interfaces', Dunhill Medical Trust [R124/0509], Egmont Foundation, Estonian Science Foundation [7859], Estonian Government [SF0180142s08], European Research Council (ERC) [230374], European Science Foundation (ESF) [EU/QLRT-2001-01254], European Union [FP5-QLK6-CY-2001-00128, FP6-LIFESCIHEALTH-36894, FP6-LSH M-CT-2004-503270, FP7-HEALTH-2007-B-223004, FP7-HEALTH-F4-2007-201413, FP7-HEALTH-F4-2008-202047, FP7-HEALTH-2009-single-stage-242244, FP7-HEALTH-2010-two-stage-259679], Fondation Caisse d'Epargne Rhone-Alpes Lyon CERAL, Genetic Association Information Network (GAIN) of the Foundation for the US National Institutes of Health (NIMH) [MH081802], GenomEUtwin [EU/QLRT-2001-01254, QLG2-CT-2002-01254], Guy's & St Thomas' NHS Foundation Trust, Health Foundation, Heart and Lung foundation [20070481], Innovation-Oriented Research Program on Genomics (SenterNovem) [IGE05007], Institut National de la Recherche Agronomique (INRA), Institut National de la Sante et de la Recherche Medicale (INSERM), King's College London, Medical Research Council (MRC) [G0500997, G0601333], Ministere de l'Enseignement superieur et de la Recherche (MESR), National Institutes of Health (NIH)/National Institute of Aging (NIA) [P01AG08761, R01D0042157-01A, U01DK066134], National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre, NBIC BioAssist [NWO-NBIC/BioAssist/RK/2008.024], Netherlands Consortium for Healthy Ageing (NCHA) [050-060-810], Netherlands Genomics Initiative (NGI), Netherlands Heart Foundation (NHF) [2001 D 032], Netherlands Organization for Scientific Research (NWO, MagW/ZonMW) [904-61-090, 904-61-193, 480-04-004, 400-05-717, Spinozapremie 56-464-14192, 175.010.2005.011, 911-03-012, 985-10-002, Addiction-31160008, Middelg-root-911-09-032], Netspar - Living longer for a good health, NHS North of Tyne (Newcastle Primary Care Trust), Pharmacy Foundation, Regione Autonoma della Sardegna, Rutgers University Cell and DNA Repository [NIMH U24 MH068457-06], Swedish Research Council [M-2005-1112], Tampere University Hospital and Academy of Finland, Danish Interdisciplinary Research Council, Health Foundation (Helsefonden), Ministry for Higher Education, National Program for Research Infrastructure [09-063256], March of Dimes Birth Defects Foundation, Swedish Foundation for Strategic Research (SSF), Unilever Discover Colworth, Universite Paris 13, University of Tartu [SP1GVAR-ENG], Velux Foundation, VU University's Institute for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam (NCA), Wellcome Trust [084762, 085475, 087436], IDEAL [FP7-HEALTH-2010-two-stage-259679], Research and Education into Ageing-0153, European Regional Development Fund, Deelen J, Beekman M, Uh HW, Broer L, Ayers KL, Tan Q, Kamatani Y, Bennet AM, Tamm R, Trompet S, Guðbjartsson DF, Flachsbart F, Rose G, Viktorin A, Fischer K, Nygaard M, Cordell HJ, Crocco P, van den Akker EB, Böhringer S, Helmer Q, Nelson CP, Saunders GI, Alver M, Andersen-Ranberg K, Breen ME, van der Breggen R, Caliebe A, Capri M, Cevenini E, Collerton JC, Dato S, Davies K, Ford I, Gampe J, Garagnani P, de Geus EJ, Harrow J, van Heemst D, Heijmans BT, Heinsen FA, Hottenga JJ, Hofman A, Jeune B, Jonsson PV, Lathrop M, Lechner D, Martin-Ruiz C, McNerlan SE, Mihailov E, Montesanto A, Mooijaart SP, Murphy A, Nohr EA, Paternoster L, Postmus I, Rivadeneira F, Ross OA, Salvioli S, Sattar N, Schreiber S, Stefánsson H, Stott DJ, Tiemeier H, Uitterlinden AG, Westendorp RG, Willemsen G, Samani NJ, Galan P, Sørensen TI, Boomsma DI, Jukema JW, Rea IM, Passarino G, de Craen AJ, Christensen K, Nebel A, Stefánsson K, Metspalu A, Magnusson P, Blanché H, Christiansen L, Kirkwood TB, van Duijn CM, Franceschi C, Houwing-Duistermaat JJ, Slagboom PE., Leiden Univ, Dept Mol Epidemiol, NL-2300 RC Leiden, Netherlands [ 2 ] Leiden Univ, Netherlands Consortium Healthy Ageing, NL-2300 RC Leiden, Netherlands [ 3 ] Leiden Univ, Dept Med Stat & Bioinformat, NL-2300 RC Leiden, Netherlands [ 4 ] Leiden Univ, Dept Cardiol, NL-2300 RC Leiden, Netherlands [ 5 ] Leiden Univ, Dept Gerontol & Geriatr, NL-2300 RC Leiden, Netherlands [ 6 ] Erasmus MC, Dept Epidemiol, NL-3000 CA Rotterdam, Netherlands [ 7 ] Erasmus MC, Dept Internal Med, NL-3000 CA Rotterdam, Netherlands [ 8 ] Newcastle Univ, Int Ctr Life, Inst Med Genet, Newcastle Upon Tyne NE1 3BZ, Tyne & Wear, England [ 9 ] Univ So Denmark, Inst Publ Hlth, DK-5000 Odense C, Denmark [ 10 ] Univ So Denmark, Inst Clin Res, Dept Gynecol & Obstet, DK-5000 Odense C, Denmark [ 11 ] Odense Univ Hosp, Dept Clin Genet, DK-5000 Odense C, Denmark [ 12 ] Odense Univ Hosp, Clin Biochem & Pharmacol, DK-5000 Odense C, Denmark [ 13 ] Fdn Jean Dausset CEPH, F-75010 Paris, France [ 14 ] Karolinska Inst, Dept Med Epidemiol & Biostat, SE-17177 Stockholm, Sweden [ 15 ] Univ Tartu, Estonian Genome Ctr, Tartu 51010, Estonia [ 16 ] Univ Tartu, Inst Mol & Cell Biol, EE-51010 Tartu, Estonia [ 17 ] deCODE Genet, Populat Gen, IS-101 Reykjavik, Iceland [ 18 ] Univ Kiel, Inst Clin Mol Biol, D-24105 Kiel, Germany [ 19 ] Univ Kiel, Inst Med Informat & Stat, D-24105 Kiel, Germany [ 20 ] Univ Calabria, Dept Biol Ecol & Earth Sci, I-87036 Arcavacata Di Rende, Italy [ 21 ] Delft Univ Technol, Delft Bioinformat Lab, NL-2600 GA Delft, Netherlands [ 22 ] Univ Leicester, Dept Cardiovasc Sci, Leicester LE3 9QP, Leics, England [ 23 ] Glenfield Hosp, Cardiovasc Biomed Res Unit, Natl Inst Hlth Res, Leicester LE3 9QP, Leics, England [ 24 ] Wellcome Trust Sanger Inst, Wellcome Trust Genome Campus, Cambridge CB10 1SA, England [ 25 ] Queens Univ Belfast, Sch Med Dent & Biomed Sci, Belfast BT9 7BL, Antrim, North Ireland [ 26 ] Univ Iowa, Dept Psychiat, Iowa City, IA 52242 USA [ 27 ] Univ Bologna, Dept Expt Diagnost & Specialty Med, I-40126 Bologna, Italy [ 28 ] Univ Bologna, Interdepartmental Ctr L Galvani, I-40126 Bologna, Italy [ 29 ] Newcastle Univ, Inst Ageing & Hlth, Newcastle Upon Tyne NE4 5PL, Tyne & Wear, England [ 30 ] Univ Glasgow, Robertson Ctr Biostat, Glasgow G12 8QQ, Lanark, Scotland [ 31 ] Univ Glasgow, Inst Cardiovasc & Med Sci, Glasgow G12 8QQ, Lanark, Scotland [ 32 ] Max Planck Inst Demograf Forsch, Lab Stat Demog, D-18057 Rostock, Germany [ 33 ] Vrije Univ Amsterdam, Dept Biol Psychol, NL-1081 BT Amsterdam, Netherlands [ 34 ] Vrije Univ Amsterdam Med Ctr, EMGO Inst Hlth & Care Res, NL-1081 BT Amsterdam, Netherlands [ 35 ] Landspitali Univ Hosp, IS-101 Reykjavik, Iceland [ 36 ] Univ Iceland, Fac Med, IS-101 Reykjavik, Iceland [ 37 ] CEA, Inst Genom, F-91057 Evry, France [ 38 ] McGill Univ, Montreal, PQ H3G 1A4, Canada [ 39 ] Genome Quebec Innovat Ctr, Montreal, PQ H3G 1A4, Canada [ 40 ] Belfast Hlth & Social Care Trust, Cytogenet Lab, Belfast BT8 8BH, Antrim, North Ireland [ 41 ] Estonian Bioctr, EE-51010 Tartu, Estonia [ 42 ] Aarhus Univ, Dept Publ Hlth, Epidemiol Sect, DK-8000 Aarhus C, Denmark [ 43 ] Univ Bristol, Sch Social & Community Med, MRC Ctr Causal Anal Translat Epidemiol, Bristol BS8 2BN, Avon, England [ 44 ] Mayo Clin, Dept Neurosci, Jacksonville, FL 32224 USA [ 45 ] Univ Glasgow, Fac Med, BHF Glasgow Cardiovasc Res Ctr, Glasgow G12 8TA, Lanark, Scotland [ 46 ] Univ Kiel, PopGen Biobank, D-24105 Kiel, Germany [ 47 ] Univ Hosp Schleswig Holstein, D-24105 Kiel, Germany [ 48 ] Sophia Childrens Univ Hosp, Erasmus Med Ctr, Dept Child & Adolescent Psychiat, NL-3000 CA Rotterdam, Netherlands [ 49 ] Univ Paris 04, UREN, U557, INSERM, F-93017 Bobigny, France [ 50 ] U1125 Inra, F-93017 Bobigny, France [ 51 ] Cnam, F-93017 Bobigny, France [ 52 ] Univ Paris 13, CRNH IdF, F-93017 Bobigny, France [ 53 ] Univ Copenhagen, Fac Hlth & Med Sci, Sect Metab Genet, Novo Nordisk Fdn Ctr, DK-2200 Copenhagen N, Denmark [ 54 ] Inst Prevent Med, DK-2000 Copenhagen, Denmark [ 55 ] Frederiksberg Univ Hosp, DK-2000 Copenhagen, Denmark [ 56 ] Interuniv Cardiol Inst Netherlands, NL-3501 DG Utrecht, Netherlands [ 57 ] Bellaria Hosp, IRCCS Inst Neurol Sci, I-40139 Bologna, Italy [ 58 ] CNR, ISOF, I-40129 Bologna, Italy, Epidemiology, Surgery, Internal Medicine, Child and Adolescent Psychiatry / Psychology, ProdInra, Migration, Vrije Universiteit Amsterdam [Amsterdam] (VU), Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), VU University Amsterdam, Biological Psychology, and EMGO+ - Lifestyle, Overweight and Diabetes

Subjects
Male, Netherlands Twin Register (NTR), Disease/genetics, Lífslíkur, Longevity/genetics, [SDV.MHEP.PHY] Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], Genetic Linkage, Genome-wide association study, 0302 clinical medicine, Prospective Studies, Genetics (clinical), Genetics, Aged, 80 and over, 0303 health sciences, education.field_of_study, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Association Studies Articles, Age Factors, Chromosome Mapping, Genetic Loci/physiology, General Medicine, 3. Good health, Europe, Phenotype, Cardiovascular Diseases, Hypertension, Chromosomes, Human, Pair 5, Female, Human Longevity, genetics, meta-analysis, Aging/genetics, Cardiology and Cardiovascular Medicine, HUMAN AGING, Longevity, European Continental Ancestry Group, Population, HUMAN GENETICS, Single-nucleotide polymorphism, Locus (genetics), Biology, FAMILIAL LONGEVITY, White People, 03 medical and health sciences, Gene mapping, SDG 3 - Good Health and Well-being, Cardiovascular Diseases/genetics, [SDV.MHEP.PHY]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], Humans, Allele, education, Molecular Biology, Aged, 030304 developmental biology, Genetic association, Öldrun, Genome, Human, Arfgengi, Minor allele frequency, Ageing, Genetic Loci, Chromosomes, Human, Pair 19, Hypertension/genetics, 030217 neurology & neurosurgery, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Genome-Wide Association Study
Abstract

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access. The genetic contribution to the variation in human lifespan is ∼ 25%. Despite the large number of identified disease-susceptibility loci, it is not known which loci influence population mortality. We performed a genome-wide association meta-analysis of 7729 long-lived individuals of European descent (≥ 85 years) and 16 121 younger controls (

Published
2014

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