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1. Using genetic variation to disentangle the complex relationship between food intake and health outcomes

Author

Nicola Pirastu, Ciara McDonnell, Eryk J. Grzeszkowiak, Ninon Mounier, Fumiaki Imamura, Jordi Merino, Felix R. Day, Jie Zheng, Nele Taba, Maria Pina Concas, Linda Repetto, Katherine A. Kentistou, Antonietta Robino, Tõnu Esko, Peter K. Joshi, Krista Fischer, Ken K. Ong, Tom R. Gaunt, Zoltán Kutalik, John R. B. Perry, and James F. Wilson

Subjects
Genetics, QH426-470
Abstract

Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes. Author summary Food and drink consumption is one of the most important factors influencing human health and wellbeing. The role of diet in human physiology and disease has been widely studied, but challenges in accurately assessing long term diet result in contradicting findings. Mendelian randomization is a statistical technique that uses genetic variants associated with modifiable exposures to estimate the causal effect of an exposure to a health outcome and could be extremely useful in the context of diet-health relationships. In our study, we initially identified genetic variants associated to 29 measures of food and drink consumption. We then show that genetic variants associated with food and drink consumption are subject to reverse causation and confounding. We have thus developed a statistical genetics method to identify genetic variants directly associated with food and drink consumption. By using these genetic variants (and their corresponding direct effects) in Mendelian randomization analyses we provided consistent evidence of causal associations of food and drink consumption with obesity, blood lipid status, and several other risk factors and health outcomes.

Published
2022

2. Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria.

Author

Felix Day, Tugce Karaderi, Michelle R Jones, Cindy Meun, Chunyan He, Alex Drong, Peter Kraft, Nan Lin, Hongyan Huang, Linda Broer, Reedik Magi, Richa Saxena, Triin Laisk, Margrit Urbanek, M Geoffrey Hayes, Gudmar Thorleifsson, Juan Fernandez-Tajes, Anubha Mahajan, Benjamin H Mullin, Bronwyn G A Stuckey, Timothy D Spector, Scott G Wilson, Mark O Goodarzi, Lea Davis, Barbara Obermayer-Pietsch, André G Uitterlinden, Verneri Anttila, Benjamin M Neale, Marjo-Riitta Jarvelin, Bart Fauser, Irina Kowalska, Jenny A Visser, Marianne Andersen, Ken Ong, Elisabet Stener-Victorin, David Ehrmann, Richard S Legro, Andres Salumets, Mark I McCarthy, Laure Morin-Papunen, Unnur Thorsteinsdottir, Kari Stefansson, andMe Research Team, Unnur Styrkarsdottir, John R B Perry, Andrea Dunaif, Joop Laven, Steve Franks, Cecilia M Lindgren, and Corrine K Welt

Subjects
Genetics, QH426-470
Abstract

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health.

Published
2018
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3. Correction: Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria

Author

Benjamin M. Neale, Benjamin H. Mullin, Barbara Obermayer-Pietsch, Richard S. Legro, Joop S.E. Laven, Richa Saxena, Ken K. Ong, Scott Wilson, Jenny A. Visser, Alexander W. Drong, Tim D. Spector, Triin Laisk, Margrit Urbanek, Unnur Styrkarsdottir, Felix R. Day, John R. B. Perry, Juan Fernández-Tajes, Andres Salumets, Bronwyn G. A. Stuckey, Anubha Mahajan, Andrea Dunaif, Linda Broer, Marianne Andersen, Mark O. Goodarzi, Matthew Jones, Mark I. McCarthy, Steve Franks, Elisabet Stener-Victorin, Kari Stefansson, Lea K. Davis, Marjo-Riitta Järvelin, Verneri Anttila, Irina Kowalska, Laure Morin-Papunen, Bart C.J.M. Fauser, Reedik Mägi, Tugce Karaderi, Nan Lin, Geoffrey Hayes, Unnur Thorsteinsdottir, Gudmar Thorleifsson, Cindy Meun, Peter Kraft, Hongyan Huang, André G. Uitterlinden, Cecilia M. Lindgren, Corrine K. Welt, David A. Ehrmann, Chunyan He, Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, University of Iceland, Day, Felix [0000-0003-3789-7651], Ong, Kenneth [0000-0003-4689-7530], Perry, John [0000-0001-6483-3771], Apollo - University of Cambridge Repository, Medical Research Council (MRC), Genesis Research Trust, Department of Obstetrics and Gynecology, HUS Gynecology and Obstetrics, Obstetrics & Gynecology, Internal Medicine, and 'European Union (EU)' and 'Horizon 2020'

Subjects
endocrine system diseases, Genome-wide association study, Body Mass Index, 0302 clinical medicine, Human genetics, Glucose homeostasis, Polycystic ovary syndrome, Body mass index, Genetics & Heredity, 0303 health sciences, 030219 obstetrics & reproductive medicine, Statistics, 1184 Genetics, developmental biology, physiology, WOMEN, Genomics, ASSOCIATION, female genital diseases and pregnancy complications, 3. Good health, Phenotypes, Oncology, Physical Sciences, Medical genetics, Polycystic Ovary Syndrome, medicine.medical_specialty, Genetic loci, SYNDROME PCOS, White People, 03 medical and health sciences, Asian People, Genome-Wide Association Studies, Genetics, Humans, Statistical Methods, Molecular Biology, Ecology, Evolution, Behavior and Systematics, 0604 Genetics, Science & Technology, IDENTIFICATION, Hyperandrogenism, Correction, Biology and Life Sciences, Computational Biology, medicine.disease, 030104 developmental biology, Genetic Loci, Eggjastokkar, Case-Control Studies, Mathematics, Developmental Biology, 0301 basic medicine, Líkamsþyngdarstuðull, Linkage disequilibrium, Cancer Research, Physiology, Type 2 diabetes, QH426-470, Bioinformatics, Genome-wide association studies, Cohort Studies, Mathematical and Statistical Techniques, 3123 Gynaecology and paediatrics, Medicine and Health Sciences, Genetics of disease, Genetics (clinical), 2. Zero hunger, RISK, HYPERANDROGENEMIA, Metaanalysis, Polycystic ovary, Kvensjúkdómar, PREVALENCE, Phenotype, Physiological Parameters, Female, Life Sciences & Biomedicine, Research Article, SUSCEPTIBILITY LOCI, TWIN, Biology, Research and Analysis Methods, 23andMe Research Team, Insulin resistance, Mendelian randomization, medicine, Erfðafræði, Genetic Predisposition to Disease, 030304 developmental biology, business.industry, Body Weight, Cancers and Neoplasms, Human Genetics, Rannsóknir, Genome Analysis, Genetic architecture, Genetics of Disease, business, Gynecological Tumors, Genome-Wide Association Study
Abstract

Publisher's version (útgefin grein), Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health., This work has been supported by MRC grant MC_U106179472 (FD, KO, JRBP), Samuel Oschin Comprehensive Cancer Institute Developmental Funds, Center for Bioinformatics and Functional Genomics and Department of Biomedical Sciences Developmental Funds (MRJ), NCI P30CA177558 (CH), NCI UM1CA186107 (PK), European Regional Development Fund (Project No. 2014-2020.4.01.15-0012) and the European Union’s Horizon 2020 research and innovation program under grant agreements No 692065 (TL, RM, AS) and 692145 (RM), NICHD R01HD065029 (RS), Estonian Ministry of Education and Research (grant IUT34-16 to TL), NICHD R01HD057450 (MU), NICHD P50HD044405 (AD), NICHD R01HD057223 (AD), R01HD085227 (MGH, AD), deCode Genetics (GT, UT, KS, US), Raine Medical Research Foundation Priming Grant (BHM), SCGOPHCG RAC 2015-16/034 (SGW, BGAS), 2016-17/018 (BGAS), NIHR BRC, Wellcome Trust, MRC (TDS), Eris M. Field Chair in Diabetes Research (MOG), NIDDK P30 DK063491 (MOG), NIDDK U01DK094431, U01DK048381 (DE), NICHD U10HD38992 (RL), Estonian Ministry of Education and Research (grant IUT34-16), Enterprise Estonia (grant EU48695); the EU-FP7 Marie Curie Industry-Academia Partnerships and Pathways (IAPP, grant SARM, EU324509 to AS), Wellcome (090532, 098381, 203141); European Commission (ENGAGE: HEALTH-F4-2007-201413 to MIM), MRC G0802782, MR/M012638/1 (SF), Li Ka Shing Foundation, WT-SSI/John Fell Funds, NIHR Biomedical Research Centre, Oxford, Widenlife and NICHD 5P50HD028138-27 (CML), NICHD R01HD065029, ADA 1-10-CT-57, Harvard Clinical and Translational Science Center, from the National Center for Research Resources 1UL1 RR025758 (CKW). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Published
2019

4. A genome-wide association study identifies protein quantitative trait loci (pQTLs).

Author

David Melzer, John R B Perry, Dena Hernandez, Anna-Maria Corsi, Kara Stevens, Ian Rafferty, Fulvio Lauretani, Anna Murray, J Raphael Gibbs, Giuseppe Paolisso, Sajjad Rafiq, Javier Simon-Sanchez, Hana Lango, Sonja Scholz, Michael N Weedon, Sampath Arepalli, Neil Rice, Nicole Washecka, Alison Hurst, Angela Britton, William Henley, Joyce van de Leemput, Rongling Li, Anne B Newman, Greg Tranah, Tamara Harris, Vijay Panicker, Colin Dayan, Amanda Bennett, Mark I McCarthy, Aimo Ruokonen, Marjo-Riitta Jarvelin, Jack Guralnik, Stefania Bandinelli, Timothy M Frayling, Andrew Singleton, and Luigi Ferrucci

Subjects
Genetics, QH426-470
Abstract

There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8x10(-57)), CCL4L1 (p = 3.9x10(-21)), IL18 (p = 6.8x10(-13)), LPA (p = 4.4x10(-10)), GGT1 (p = 1.5x10(-7)), SHBG (p = 3.1x10(-7)), CRP (p = 6.4x10(-6)) and IL1RN (p = 7.3x10(-6)) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8x10(-40)), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways.

Published
2008
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5. A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone-Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation

Author

Massimo Mangino, Magnus Karlsson, Wei Vivian Zhuang, Laure Morin Papunen, Nicole Soranzo, Martin Reincke, Leo-Pekka Lyytikäinen, Andrea D. Coviello, Petra H.M. Peeters, Daniel B. Mirel, Myriam Fornage, Carla H. van Gils, Kurt Lohman, Tamara B. Harris, Martin Bidlingmaier, Leslie J. Raffel, Marc J. Gunter, Liesbeth Vandenput, M. Maggio, Pamela Ouyang, Sarah Keildson, Iva Miljkovic, Annemarie Koster, Simin Liu, Steven R. Cummings, John-Olov Jansson, Mattias Lorentzon, Mika Kähönen, Stephen J. Chanock, Yuhui Chen, Luigi Ferrucci, David G. Cox, Johannes Kettunen, Henri Wallaschofski, Anneli Pouta, Marcello Ricardo Paulista Markus, Steve Franks, Jorma Viikari, Frank De Jong, Melissa Wellons, Susan E. Hankinson, Georg Homuth, Hannu Martikainen, Albert Hofman, Alexander P. Reiner, Andrew D. Johnson, Douglas P. Kiel, Marjo-Riitta Järvelin, Reiner Biffar, Fernando Rivadeneira, Joel Eriksson, Inga Prokopenko, Ann-Kristin Petersen, Kathryn M. Rexrode, H.-Erich Wichmann, Stephen M. Schwartz, Chunyan He, John R. B. Perry, Shelley S. Tworoger, N. Charlotte Onland-Moret, Yongmei Liu, David S. Siscovick, Terho Lehtimäki, Peter Kraft, Georg Brabant, André G. Uitterlinden, Alexander Teumer, Östen Ljunggren, Dan Mellström, Stefania Bandinelli, Dhananjay Vaidya, Claes Ohlsson, David Karasik, Lisette Stolk, Anna-Liisa Hartikainen, Andrew R. Wood, Shalender Bhasin, Mark I. McCarthy, Jennifer Prescott, Anna Murray, Tim D. Spector, Guangju Zhai, Olli T. Raitakari, Joanne M. Murabito, Kathryn L. Lunetta, Thomas Illig, Jingmin Liu, Melissa Garcia, Brian H. Chen, Ramachandran S. Vasan, David J. Hunter, Robin Haring, Sarah C. Nelson, Vasiliki Lagou, Aimo Ruokonen, Immaculata De Vivo, Doris Stöckl, Timothy M. Frayling, Yvonne T. van der Schouw, Interne Geneeskunde, RS: CARIM School for Cardiovascular Diseases, Public Health, Internal Medicine, Epidemiology, Urology, Medical Research Council (MRC), and Institute for Molecular Medicine Finland

Subjects
MEDICAL PROGRESS, Male, Cancer Research, Medicin och hälsovetenskap, Epidemiology, HAN CHINESE POPULATION, Genome-wide association study, RECEPTOR TYROSINE KINASE, QH426-470, HAN CHINESE, Medical and Health Sciences, 0302 clinical medicine, Sex hormone-binding globulin, Endocrinology, Sex Hormone-Binding Globulin, GENETICS & HEREDITY, Gonadal Steroid Hormones, POPULATION, Genetics (clinical), GENE-EXPRESSION, RISK, 0303 health sciences, education.field_of_study, Sex Characteristics, POLYCYSTIC-OVARY-SYNDROME, INSULIN-RECEPTOR, 3. Good health, 030220 oncology & carcinogenesis, Genetic Epidemiology, MEDICAL, Medicine, Allelic heterogeneity, Female, Life Sciences & Biomedicine, Metabolic Networks and Pathways, Research Article, medicine.medical_specialty, medicine.drug_class, Population, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, 03 medical and health sciences, Genetic Heterogeneity, SDG 3 - Good Health and Well-being, Internal medicine, medicine, Genetics, Humans, Reproductive Endocrinology, education, PROGRESS, Molecular Biology, Ecology, Evolution, Behavior and Systematics, Alleles, 030304 developmental biology, 0604 Genetics, Science & Technology, GCKR RS780094, Endocrine Physiology, Genetic heterogeneity, ta3121, Androgen, SHBG GENE, POLYMORPHISM, Orthopedics, Sex steroid, biology.protein, 3111 Biomedicine, Developmental Biology, Genome-Wide Association Study
Abstract

Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8×10−106), PRMT6 (rs17496332, 1p13.3, p = 1.4×10−11), GCKR (rs780093, 2p23.3, p = 2.2×10−16), ZBTB10 (rs440837, 8q21.13, p = 3.4×10−09), JMJD1C (rs7910927, 10q21.3, p = 6.1×10−35), SLCO1B1 (rs4149056, 12p12.1, p = 1.9×10−08), NR2F2 (rs8023580, 15q26.2, p = 8.3×10−12), ZNF652 (rs2411984, 17q21.32, p = 3.5×10−14), TDGF3 (rs1573036, Xq22.3, p = 4.1×10−14), LHCGR (rs10454142, 2p16.3, p = 1.3×10−07), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7×10−08), and UGT2B15 (rs293428, 4q13.2, p = 5.5×10−06). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5×10−08, women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ∼15.6% and ∼8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance., Author Summary Sex hormone-binding globulin (SHBG) is the key protein responsible for binding and transporting the sex steroid hormones, testosterone and estradiol, in the circulatory system. SHBG regulates their bioavailability and therefore their effects in the body. SHBG has been linked to chronic diseases including type 2 diabetes and to hormone-sensitive cancers such as breast and prostate cancer. SHBG concentrations are approximately 50% heritable in family studies, suggesting SHBG concentrations are under significant genetic control; yet, little is known about the specific genes that influence SHBG. We conducted a large study of the association of SHBG concentrations with markers in the human genome in ∼22,000 white men and women to determine which loci influence SHBG concentrations. Genes near the identified genomic markers in addition to the SHBG protein coding gene included PRMT6, GCKR, ZBTB10, JMJD1C, SLCO1B1, NR2F2, ZNF652, TDGF3, LHCGR, BAIAP2L1, and UGT2B15. These genes represent a wide range of biologic pathways that may relate to SHBG function and sex steroid hormone biology, including liver function, lipid metabolism, carbohydrate metabolism and type 2 diabetes, and the development and progression of sex steroid hormone-responsive cancers.

Published
2012

6. Stratifying type 2 diabetes cases by BMI identifies genetic risk variants in LAMA1 and enrichment for risk variants in lean compared to obese cases

Author

David Altschuler, Cornelia M. van Duijn, Igor Rudan, Denis Rybin, Yann Labrune, Francis S. Collins, Martha Ganser, Lu Qi, Michael Roden, Unnur Thorsteinsdottir, Inga Prokopenko, Albert Hofman, Guillaume Charpentier, Mark I. McCarthy, Robert Sladek, James F. Wilson, Stéphane Cauchi, Yurii S. Aulchenko, Christian Herder, Robert A. Scott, Man Li, Peter P. Pramstaller, Rafn Benediktsson, Frank B. Hu, Samy Hadjadj, Peter Almgren, Andrew D. Johnson, Beverley Balkau, Pau Navarro, Michael Boehnke, Michael N. Weedon, Leif Groop, John R. B. Perry, Lori L. Bonnycastle, Noël P. Burtt, Alisa K. Manning, Claudia Langenberg, W Rayner, Benjamin F. Voight, Wolfgang Rathmann, Timothy M. Frayling, Gunnar Sigurdsson, Eric Boerwinkle, James S. Pankow, Ben A. Oostra, Andrew D. Morris, Philippe Froguel, Linda Kao, Dan E. Arking, Kari Stefansson, Harry Campbell, Loic Yengo, Colin N. A. Palmer, Nicholas J. Wareham, James B. Meigs, Karen L. Mohlke, Gudmar Thorleifsson, Andrew T. Hattersley, Alan F. Wright, Laura J. Scott, Harald Grallert, Jaakko Tuomilehto, Najaf Amin, Christian Gieger, Thomas Illig, Anna Köttgen, Todd Green, Josée Dupuis, Sidonie Vivequin, Richard N. Bergman, Peter Kraft, André G. Uitterlinden, Valgerdur Steinthorsdottir, Andrew P. Morris, Ann-Kristin Petersen, Epidemiology, Dermatology, Clinical Genetics, and Internal Medicine

Subjects
Male, Cancer Research, Heredity, Epidemiology, PROTEIN, Type 2 diabetes, QH426-470, Overweight, MOUSE, Bioinformatics, DISEASE, GLUCOSE, Body Mass Index, Endocrinology, 0302 clinical medicine, Risk Factors, GENETICS & HEREDITY, Genetics (clinical), 2. Zero hunger, Molecular Epidemiology, 0303 health sciences, High Mobility Group Proteins, Middle Aged, INSULIN, 3. Good health, Phenotypes, DIFFERENTIATION, Genetic Epidemiology, Medicine, Female, medicine.symptom, Life Sciences & Biomedicine, Research Article, EXPRESSION, Asian Continental Ancestry Group, medicine.medical_specialty, SUSCEPTIBILITY LOCI, European Continental Ancestry Group, 030209 endocrinology & metabolism, DIAGRAM Consortium, Biology, Endocrinology and Diabetes, Polymorphism, Single Nucleotide, White People, 03 medical and health sciences, Asian People, SDG 3 - Good Health and Well-being, Internal medicine, GIANT Consortium, Genome-Wide Association Studies, Genetics, medicine, Genetic predisposition, Humans, Genetic Predisposition to Disease, Obesity, GENOME-WIDE ASSOCIATION, Risk factor, Molecular Biology, Alleles, Ecology, Evolution, Behavior and Systematics, Aged, 030304 developmental biology, Diabetic Endocrinology, 0604 Genetics, Science & Technology, Complex Traits, Case-control study, Human Genetics, Odds ratio, Diabetes Mellitus Type 2, medicine.disease, MAGIC, Diabetes Mellitus, Type 2, Case-Control Studies, CELLS, Laminin, Body mass index, Developmental Biology, Genome-Wide Association Study
Abstract

Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI, Author Summary Individuals with Type 2 diabetes (T2D) can present with variable clinical characteristics. It is well known that obesity is a major risk factor for type 2 diabetes, yet patients can vary considerably—there are many lean diabetes patients and many overweight people without diabetes. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI

Published
2012

7. Eight common genetic variants associated with serum DHEAS levels suggest a key role in ageing mechanisms

Author

Timothy M. Frayling, Anna Murray, Massimo Mangino, David Melzer, Florian Ernst, Marcello Maggio, Åsa K. Hedman, Frank H. de Jong, Robin Haring, Alexander Teumer, Jordana T. Bell, Fernando Rivadeneira, Li Xi, Albert Hofman, Claes Ohlsson, Joel Eriksson, Lisette Stolk, Mattias Lorentzon, Iva Miljkovic, Wei Vivian Zhuang, Luigi Ferrucci, Elin Grundberg, Nicole Soranzo, Yongmei Liu, Liesbeth Vandenput, Shalender Bhasin, Joanne M. Murabito, Annemarie Koster, Brenda W.J.H. Penninx, Henri Wallaschofski, Tim D. Spector, Guangju Zhai, Anna Eriksson, Daniel Glass, Henry Völzke, John R. B. Perry, Douglas P. Kiel, Alexandra C. Nica, Ramachandran S. Vasan, Kathryn L. Lunetta, Heyo K. Kroemer, Tamara B. Harris, Andrea D. Coviello, Scott Wilson, André G. Uitterlinden, Kerrin S. Small, Internal Medicine, Public Health, Epidemiology, Psychiatry, EMGO - Mental health, and EMGO+ - Mental Health

Subjects
Male, Cancer Research, Linkage disequilibrium, Aging, Epidemiology, Gene Expression, Genome-wide association study, Type 2 diabetes, QH426-470, Linkage Disequilibrium, chemistry.chemical_compound, 0302 clinical medicine, Endocrinology, Gene expression, Genetics (clinical), 0303 health sciences, Bcl-2-Like Protein 11, Dehydroepiandrosterone Sulfate, Genomics, Middle Aged, 3. Good health, DNA-Binding Proteins, Liver, 030220 oncology & carcinogenesis, Medicine, Female, Aryl Hydrocarbon Hydroxylases, Sulfotransferases, Research Article, Adult, medicine.medical_specialty, Kruppel-Like Transcription Factors, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Actin-Related Protein 2-3 Complex, White People, Biological pathway, 03 medical and health sciences, Young Adult, Dehydroepiandrosterone sulfate, SDG 3 - Good Health and Well-being, Internal medicine, Proto-Oncogene Proteins, medicine, Genetics, Humans, Molecular Biology, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, Adaptor Proteins, Signal Transducing, Aged, Cytochrome P-450 CYP2C9, Homeodomain Proteins, Membrane Proteins, medicine.disease, chemistry, Ageing, Geriatrics, Apoptosis Regulatory Proteins, Genome-Wide Association Study, Transcription Factors
Abstract

Dehydroepiandrosterone sulphate (DHEAS) is the most abundant circulating steroid secreted by adrenal glands—yet its function is unknown. Its serum concentration declines significantly with increasing age, which has led to speculation that a relative DHEAS deficiency may contribute to the development of common age-related diseases or diminished longevity. We conducted a meta-analysis of genome-wide association data with 14,846 individuals and identified eight independent common SNPs associated with serum DHEAS concentrations. Genes at or near the identified loci include ZKSCAN5 (rs11761528; p = 3.15×10−36), SULT2A1 (rs2637125; p = 2.61×10−19), ARPC1A (rs740160; p = 1.56×10−16), TRIM4 (rs17277546; p = 4.50×10−11), BMF (rs7181230; p = 5.44×10−11), HHEX (rs2497306; p = 4.64×10−9), BCL2L11 (rs6738028; p = 1.72×10−8), and CYP2C9 (rs2185570; p = 2.29×10−8). These genes are associated with type 2 diabetes, lymphoma, actin filament assembly, drug and xenobiotic metabolism, and zinc finger proteins. Several SNPs were associated with changes in gene expression levels, and the related genes are connected to biological pathways linking DHEAS with ageing. This study provides much needed insight into the function of DHEAS., Author Summary Dehydroepiandrosterone sulphate (DHEAS), mainly secreted by the adrenal gland, is the most abundant circulating steroid in humans. It shows a significant physiological decline after the age of 25 and diminishes about 95% by the age of 85 years, which has led to speculation that a relative DHEAS deficiency may contribute to the development of common age-related diseases or diminished longevity. Twin- and family-based studies have shown that there is a substantial genetic effect with heritability estimate of 60%, but no specific genes regulating serum DHEAS concentration have been identified to date. Here we take advantage of recent technical and methodological advances to examine the effects of common genetic variants on serum DHEAS concentrations. By examining 14,846 Caucasian individuals, we show that eight common genetic variants are associated with serum DHEAS concentrations. Genes at or near these genetic variants include BCL2L11, ARPC1A, ZKSCAN5, TRIM4, HHEX, CYP2C9, BMF, and SULT2A1. These genes have various associations with steroid hormone metabolism—co-morbidities of ageing including type 2 diabetes, lymphoma, actin filament assembly, drug and xenobiotic metabolism, and zinc finger proteins—suggesting a wider functional role for DHEAS than previously thought.

Published
2011

8. A genome-wide association study identifies protein quantitative trait loci (pQTLs)

Author

Luigi Ferrucci, J. Raphael Gibbs, Michael N. Weedon, Tamara B. Harris, Alison J. Hurst, William Henley, Annamaria Corsi, Vijay Panicker, Colin M. Dayan, Amanda J. Bennett, Nicole Washecka, Kara Stevens, Stefania Bandinelli, Jack M. Guralnik, Giuseppe Paolisso, Sampath Arepalli, Marjo-Riitta Järvelin, Ian Rafferty, Joyce van de Leemput, John R. B. Perry, Sonja W. Scholz, Mark I. McCarthy, Gregory J. Tranah, Hana Lango, Javier Simón-Sánchez, Rongling Li, Aimo Ruokonen, Andrew B. Singleton, Anne B. Newman, Timothy M. Frayling, Fulvio Lauretani, Dena G. Hernandez, Neil Rice, Anna Murray, David Melzer, Sajjad Rafiq, Angela Britton, Melzer, D., Perry, J., Hernandez, D., Corsi, A., Stevens, K., Rafferty, I., Murray, A., Gibbs, J., Paolisso, Giuseppe, Rafiq, S., SIMON SANCHEZ, J., Lango, H., Sholz, S., Weedon, M., Arepalli, S., Rice, N., Washecka, N., Hurst, A., Britton, A., Henley, W., VAN DE LEEMPUT, J., Li, R., Newman, A., Tranah, G., Harris, T., Panicker, V., Dayan, C., Bennet, A., Mccarthy, M., Ruokonen, A., Jarvelin, M., Guralnik, J., Bandinelli, S., Frayling, T., Singleton, A., and Ferrucci, L.

Subjects
Male, Cancer Research, Transcription, Genetic, Genetic Linkage, Gene Dosage, Genome-wide association study, DISEASE, 0302 clinical medicine, Biochemistry/Protein Chemistry, Copy-number variation, Genetics and Genomics/Genetics of Disease, Genetics (clinical), Genetics & Heredity, RISK, Aged, 80 and over, Genetics, 0303 health sciences, BIRTH COHORT, interleukin, Genetics and Genomics/Functional Genomics, Genetics and Genomics/Gene Expression, Blood Proteins, Genetics and Genomics/Physiogenomics, Middle Aged, CANCER, Diabetes and Endocrinology, InCHIANTI study, 030220 oncology & carcinogenesis, MENDELIAN RANDOMIZATION, Female, Life Sciences & Biomedicine, Biochemistry/Transcription and Translation, Research Article, Adult, liver function markers, lcsh:QH426-470, Genotype, Cardiovascular Disorders, Quantitative Trait Loci, Single-nucleotide polymorphism, Genetics and Genomics/Complex Traits, Biology, Quantitative trait locus, Polymorphism, Single Nucleotide, 03 medical and health sciences, Genetic variation, Humans, YEAST, Allele, Molecular Biology, QH426, POLYMORPHISMS, Ecology, Evolution, Behavior and Systematics, Aged, 030304 developmental biology, 0604 Genetics, Science & Technology, HUMAN GENE-EXPRESSION, RECEPTOR, Genome, Human, Genetic Variation, Molecular biology, R1, COMMON VARIANT, lcsh:Genetics, Genetics and Genomics/Genome Projects, Expression quantitative trait loci, Liver function, Developmental Biology, Genome-Wide Association Study
Abstract

There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts – cis effects, and elsewhere in the genome – trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8×10−57), CCL4L1 (p = 3.9×10−21), IL18 (p = 6.8×10−13), LPA (p = 4.4×10−10), GGT1 (p = 1.5×10−7), SHBG (p = 3.1×10−7), CRP (p = 6.4×10−6) and IL1RN (p = 7.3×10−6) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8×10−40), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways., Author Summary One of the central dogmas of molecular genetics is that DNA is transcribed to RNA which is translated to protein and alterations to proteins can influence human diseases. Genome-wide association studies have recently revealed many new DNA variants that influence human diseases. To complement these efforts, several genome-wide studies have established that DNA variation influences mRNA expression levels. Loci influencing mRNA levels have been termed “eQTLs”. In this study we have performed the first genome-wide association study of the third piece in this jigsaw – the role of DNA variation in relation to protein levels, or “pQTLs”. We analysed 42 proteins measured in blood fractions from the InCHIANTI study. We identified eight cis effects including common variants in or near the IL6R, CCL4, IL18, LPA, GGT1, SHBG, CRP and IL1RN genes, all associated with blood levels of their respective protein products. Mechanisms implicated included altered transcription (GGT1) but also rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA) and variation in gene copy number (CCL4). Blood levels of many of these proteins are correlated with human diseases and the identification of “pQTLs” may in turn help our understanding of disease.

Published
2008

9. Correction: Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria.

Author

Felix Day, Tugce Karaderi, Michelle R Jones, Cindy Meun, Chunyan He, Alex Drong, Peter Kraft, Nan Lin, Hongyan Huang, Linda Broer, Reedik Magi, Richa Saxena, Triin Laisk, Margrit Urbanek, M Geoffrey Hayes, Gudmar Thorleifsson, Juan Fernandez-Tajes, Anubha Mahajan, Benjamin H Mullin, Bronwyn G A Stuckey, Timothy D Spector, Scott G Wilson, Mark O Goodarzi, Lea Davis, Barbara Obermayer-Pietsch, André G Uitterlinden, Verneri Anttila, Benjamin M Neale, Marjo-Riitta Jarvelin, Bart Fauser, Irina Kowalska, Jenny A Visser, Marianne Andersen, Ken Ong, Elisabet Stener-Victorin, David Ehrmann, Richard S Legro, Andres Salumets, Mark I McCarthy, Laure Morin-Papunen, Unnur Thorsteinsdottir, Kari Stefansson, andMe Research Team, Unnur Styrkarsdottir, John R B Perry, Andrea Dunaif, Joop Laven, Steve Franks, Cecilia M Lindgren, and Corrine K Welt

Subjects
Genetics, QH426-470
Abstract

[This corrects the article DOI: 10.1371/journal.pgen.1007813.].

Published
2019
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10. Stratifying type 2 diabetes cases by BMI identifies genetic risk variants in LAMA1 and enrichment for risk variants in lean compared to obese cases.

Author

John R B Perry, Benjamin F Voight, Loïc Yengo, Najaf Amin, Josée Dupuis, Martha Ganser, Harald Grallert, Pau Navarro, Man Li, Lu Qi, Valgerdur Steinthorsdottir, Robert A Scott, Peter Almgren, Dan E Arking, Yurii Aulchenko, Beverley Balkau, Rafn Benediktsson, Richard N Bergman, Eric Boerwinkle, Lori Bonnycastle, Noël P Burtt, Harry Campbell, Guillaume Charpentier, Francis S Collins, Christian Gieger, Todd Green, Samy Hadjadj, Andrew T Hattersley, Christian Herder, Albert Hofman, Andrew D Johnson, Anna Kottgen, Peter Kraft, Yann Labrune, Claudia Langenberg, Alisa K Manning, Karen L Mohlke, Andrew P Morris, Ben Oostra, James Pankow, Ann-Kristin Petersen, Peter P Pramstaller, Inga Prokopenko, Wolfgang Rathmann, William Rayner, Michael Roden, Igor Rudan, Denis Rybin, Laura J Scott, Gunnar Sigurdsson, Rob Sladek, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Jaakko Tuomilehto, Andre G Uitterlinden, Sidonie Vivequin, Michael N Weedon, Alan F Wright, MAGIC, DIAGRAM Consortium, GIANT Consortium, Frank B Hu, Thomas Illig, Linda Kao, James B Meigs, James F Wilson, Kari Stefansson, Cornelia van Duijn, David Altschuler, Andrew D Morris, Michael Boehnke, Mark I McCarthy, Philippe Froguel, Colin N A Palmer, Nicholas J Wareham, Leif Groop, Timothy M Frayling, and Stéphane Cauchi

Subjects
Genetics, QH426-470
Abstract

Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI

Published
2012
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11. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Author

Zari Dastani, Marie-France Hivert, Nicholas Timpson, John R B Perry, Xin Yuan, Robert A Scott, Peter Henneman, Iris M Heid, Jorge R Kizer, Leo-Pekka Lyytikäinen, Christian Fuchsberger, Toshiko Tanaka, Andrew P Morris, Kerrin Small, Aaron Isaacs, Marian Beekman, Stefan Coassin, Kurt Lohman, Lu Qi, Stavroula Kanoni, James S Pankow, Hae-Won Uh, Ying Wu, Aurelian Bidulescu, Laura J Rasmussen-Torvik, Celia M T Greenwood, Martin Ladouceur, Jonna Grimsby, Alisa K Manning, Ching-Ti Liu, Jaspal Kooner, Vincent E Mooser, Peter Vollenweider, Karen A Kapur, John Chambers, Nicholas J Wareham, Claudia Langenberg, Rune Frants, Ko Willems-Vandijk, Ben A Oostra, Sara M Willems, Claudia Lamina, Thomas W Winkler, Bruce M Psaty, Russell P Tracy, Jennifer Brody, Ida Chen, Jorma Viikari, Mika Kähönen, Peter P Pramstaller, David M Evans, Beate St Pourcain, Naveed Sattar, Andrew R Wood, Stefania Bandinelli, Olga D Carlson, Josephine M Egan, Stefan Böhringer, Diana van Heemst, Lyudmyla Kedenko, Kati Kristiansson, Marja-Liisa Nuotio, Britt-Marie Loo, Tamara Harris, Melissa Garcia, Alka Kanaya, Margot Haun, Norman Klopp, H-Erich Wichmann, Panos Deloukas, Efi Katsareli, David J Couper, Bruce B Duncan, Margreet Kloppenburg, Linda S Adair, Judith B Borja, DIAGRAM+ Consortium, MAGIC Consortium, GLGC Investigators, MuTHER Consortium, James G Wilson, Solomon Musani, Xiuqing Guo, Toby Johnson, Robert Semple, Tanya M Teslovich, Matthew A Allison, Susan Redline, Sarah G Buxbaum, Karen L Mohlke, Ingrid Meulenbelt, Christie M Ballantyne, George V Dedoussis, Frank B Hu, Yongmei Liu, Bernhard Paulweber, Timothy D Spector, P Eline Slagboom, Luigi Ferrucci, Antti Jula, Markus Perola, Olli Raitakari, Jose C Florez, Veikko Salomaa, Johan G Eriksson, Timothy M Frayling, Andrew A Hicks, Terho Lehtimäki, George Davey Smith, David S Siscovick, Florian Kronenberg, Cornelia van Duijn, Ruth J F Loos, Dawn M Waterworth, James B Meigs, Josee Dupuis, J Brent Richards, Benjamin F Voight, Laura J Scott, Valgerdur Steinthorsdottir, Christian Dina, Ryan P Welch, Eleftheria Zeggini, Cornelia Huth, Yurii S Aulchenko, Gudmar Thorleifsson, Laura J McCulloch, Teresa Ferreira, Harald Grallert, Najaf Amin, Guanming Wu, Cristen J Willer, Soumya Raychaudhuri, Steve A McCarroll, Oliver M Hofmann, Ayellet V Segrè, Mandy van Hoek, Pau Navarro, Kristin Ardlie, Beverley Balkau, Rafn Benediktsson, Amanda J Bennett, Roza Blagieva, Eric Boerwinkle, Lori L Bonnycastle, Kristina Bengtsson Boström, Bert Bravenboer, Suzannah Bumpstead, Noël P Burtt, Guillaume Charpentier, Peter S Chines, Marilyn Cornelis, Gabe Crawford, Alex S F Doney, Katherine S Elliott, Amanda L Elliott, Michael R Erdos, Caroline S Fox, Christopher S Franklin, Martha Ganser, Christian Gieger, Niels Grarup, Todd Green, Simon Griffin, Christopher J Groves, Candace Guiducci, Samy Hadjadj, Neelam Hassanali, Christian Herder, Bo Isomaa, Anne U Jackson, Paul R V Johnson, Torben Jørgensen, Wen H L Kao, Augustine Kong, Peter Kraft, Johanna Kuusisto, Torsten Lauritzen, Man Li, Aloysius Lieverse, Cecilia M Lindgren, Valeriya Lyssenko, Michel Marre, Thomas Meitinger, Kristian Midthjell, Mario A Morken, Narisu Narisu, Peter Nilsson, Katharine R Owen, Felicity Payne, Ann-Kristin Petersen, Carl Platou, Christine Proença, Inga Prokopenko, Wolfgang Rathmann, N William Rayner, Neil R Robertson, Ghislain Rocheleau, Michael Roden, Michael J Sampson, Richa Saxena, Beverley M Shields, Peter Shrader, Gunnar Sigurdsson, Thomas Sparsø, Klaus Strassburger, Heather M Stringham, Qi Sun, Amy J Swift, Barbara Thorand, Jean Tichet, Tiinamaija Tuomi, Rob M van Dam, Timon W van Haeften, Thijs van Herpt, Jana V van Vliet-Ostaptchouk, G Bragi Walters, Michael N Weedon, Cisca Wijmenga, Jacqueline Witteman, Richard N Bergman, Stephane Cauchi, Francis S Collins, Anna L Gloyn, Ulf Gyllensten, Torben Hansen, Winston A Hide, Graham A Hitman, Albert Hofman, David J Hunter, Kristian Hveem, Markku Laakso, Andrew D Morris, Colin N A Palmer, Igor Rudan, Eric Sijbrands, Lincoln D Stein, Jaakko Tuomilehto, Andre Uitterlinden, Mark Walker, Richard M Watanabe, Goncalo R Abecasis, Bernhard O Boehm, Harry Campbell, Mark J Daly, Andrew T Hattersley, Oluf Pedersen, Inês Barroso, Leif Groop, Rob Sladek, Unnur Thorsteinsdottir, James F Wilson, Thomas Illig, Philippe Froguel, Cornelia M van Duijn, Kari Stefansson, David Altshuler, Michael Boehnke, Mark I McCarthy, Nicole Soranzo, Eleanor Wheeler, Nicole L Glazer, Nabila Bouatia-Naji, Reedik Mägi, Joshua Randall, Paul Elliott, Denis Rybin, Abbas Dehghan, Jouke Jan Hottenga, Kijoung Song, Anuj Goel, Taina Lajunen, Alex Doney, Christine Cavalcanti-Proença, Meena Kumari, Nicholas J Timpson, Carina Zabena, Erik Ingelsson, Ping An, Jeffrey O'Connell, Jian'an Luan, Amanda Elliott, Steven A McCarroll, Rosa Maria Roccasecca, François Pattou, Praveen Sethupathy, Yavuz Ariyurek, Philip Barter, John P Beilby, Yoav Ben-Shlomo, Sven Bergmann, Murielle Bochud, Amélie Bonnefond, Knut Borch-Johnsen, Yvonne Böttcher, Eric Brunner, Suzannah J Bumpstead, Yii-Der Ida Chen, Peter Chines, Robert Clarke, Lachlan J M Coin, Matthew N Cooper, Laura Crisponi, Ian N M Day, Eco J C de Geus, Jerome Delplanque, Annette C Fedson, Antje Fischer-Rosinsky, Nita G Forouhi, Maria Grazia Franzosi, Pilar Galan, Mark O Goodarzi, Jürgen Graessler, Scott Grundy, Rhian Gwilliam, Göran Hallmans, Naomi Hammond, Xijing Han, Anna-Liisa Hartikainen, Caroline Hayward, Simon C Heath, Serge Hercberg, David R Hillman, Aroon D Hingorani, Jennie Hui, Joe Hung, Marika Kaakinen, Jaakko Kaprio, Y Antero Kesaniemi, Mika Kivimaki, Beatrice Knight, Seppo Koskinen, Peter Kovacs, Kirsten Ohm Kyvik, G Mark Lathrop, Debbie A Lawlor, Olivier Le Bacquer, Cécile Lecoeur, Yun Li, Robert Mahley, Massimo Mangino, María Teresa Martínez-Larrad, Jarred B McAteer, Ruth McPherson, Christa Meisinger, David Melzer, David Meyre, Braxton D Mitchell, Sutapa Mukherjee, Silvia Naitza, Matthew J Neville, Marco Orrù, Ruth Pakyz, Giuseppe Paolisso, Cristian Pattaro, Daniel Pearson, John F Peden, Nancy L Pedersen, Andreas F H Pfeiffer, Irene Pichler, Ozren Polasek, Danielle Posthuma, Simon C Potter, Anneli Pouta, Michael A Province, Nigel W Rayner, Kenneth Rice, Samuli Ripatti, Fernando Rivadeneira, Olov Rolandsson, Annelli Sandbaek, Manjinder Sandhu, Serena Sanna, Avan Aihie Sayer, Paul Scheet, Udo Seedorf, Stephen J Sharp, Beverley Shields, Gunnar Sigurðsson, Eric J G Sijbrands, Angela Silveira, Laila Simpson, Andrew Singleton, Nicholas L Smith, Ulla Sovio, Amy Swift, Holly Syddall, Ann-Christine Syvänen, Anke Tönjes, André G Uitterlinden, Ko Willems van Dijk, Dhiraj Varma, Sophie Visvikis-Siest, Veronique Vitart, Nicole Vogelzangs, Gérard Waeber, Peter J Wagner, Andrew Walley, Kim L Ward, Hugh Watkins, Sarah H Wild, Gonneke Willemsen, Jaqueline C M Witteman, John W G Yarnell, Diana Zelenika, Björn Zethelius, Guangju Zhai, Jing Hua Zhao, M Carola Zillikens, DIAGRAM Consortium, GIANT Consortium, Global B Pgen Consortium, Ingrid B Borecki, Pierre Meneton, Patrik K E Magnusson, David M Nathan, Gordon H Williams, Kaisa Silander, Stefan R Bornstein, Peter Schwarz, Joachim Spranger, Fredrik Karpe, Alan R Shuldiner, Cyrus Cooper, Manuel Serrano-Ríos, Lars Lind, Lyle J Palmer, Paul W Franks, Shah Ebrahim, Michael Marmot, W H Linda Kao, Peter Paul Pramstaller, Alan F Wright, Michael Stumvoll, Anders Hamsten, Procardis Consortium, Thomas A Buchanan, Timo T Valle, Jerome I Rotter, Brenda W J H Penninx, Dorret I Boomsma, Antonio Cao, Angelo Scuteri, David Schlessinger, Manuela Uda, Aimo Ruokonen, Marjo-Riitta Jarvelin, Leena Peltonen, Vincent Mooser, Robert Sladek, MAGIC investigators, GLGC Consortium, Kiran Musunuru, Albert V Smith, Andrew C Edmondson, Ioannis M Stylianou, Masahiro Koseki, James P Pirruccello, Daniel I Chasman, Christopher T Johansen, Sigrid W Fouchier, Gina M Peloso, Maja Barbalic, Sally L Ricketts, Joshua C Bis, Mary F Feitosa, Marju Orho-Melander, Olle Melander, Xiaohui Li, Mingyao Li, Yoon Shin Cho, Min Jin Go, Young Jin Kim, Jong-Young Lee, Taesung Park, Kyunga Kim, Xueling Sim, Rick Twee-Hee Ong, Damien C Croteau-Chonka, Leslie A Lange, Joshua D Smith, Andreas Ziegler, Weihua Zhang, Robert Y L Zee, John B Whitfield, John R Thompson, Ida Surakka, Tim D Spector, Johannes H Smit, Juha Sinisalo, James Scott, Juha Saharinen, Chiara Sabatti, Lynda M Rose, Robert Roberts, Mark Rieder, Alex N Parker, Guillaume Pare, Christopher J O'Donnell, Markku S Nieminen, Deborah A Nickerson, Grant W Montgomery, Wendy McArdle, David Masson, Nicholas G Martin, Fabio Marroni, Gavin Lucas, Robert Luben, Marja-Liisa Lokki, Guillaume Lettre, Lenore J Launer, Edward G Lakatta, Reijo Laaksonen, Kirsten O Kyvik, Inke R König, Kay-Tee Khaw, Lee M Kaplan, Åsa Johansson, A Cecile J W Janssens, Wilmar Igl, G Kees Hovingh, Christian Hengstenberg, Aki S Havulinna, Nicholas D Hastie, Tamara B Harris, Talin Haritunians, Alistair S Hall, Leif C Groop, Elena Gonzalez, Nelson B Freimer, Jeanette Erdmann, Kenechi G Ejebe, Angela Döring, Anna F Dominiczak, Serkalem Demissie, Panagiotis Deloukas, Ulf de Faire, Gabriel Crawford, Yii-der I Chen, Mark J Caulfield, S Matthijs Boekholdt, Themistocles L Assimes, Thomas Quertermous, Mark Seielstad, Tien Y Wong, E-Shyong Tai, Alan B Feranil, Christopher W Kuzawa, Herman A Taylor, Stacey B Gabriel, Hilma Holm, Vilmundur Gudnason, Ronald M Krauss, Jose M Ordovas, Patricia B Munroe, Jaspal S Kooner, Alan R Tall, Robert A Hegele, John J P Kastelein, Eric E Schadt, David P Strachan, Muredach P Reilly, Nilesh J Samani, Heribert Schunkert, L Adrienne Cupples, Manjinder S Sandhu, Paul M Ridker, Daniel J Rader, and Sekar Kathiresan

Subjects
Genetics, QH426-470
Abstract

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p

Published
2012
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12. A genome-wide association meta-analysis of circulating sex hormone-binding globulin reveals multiple Loci implicated in sex steroid hormone regulation.

Author

Andrea D Coviello, Robin Haring, Melissa Wellons, Dhananjay Vaidya, Terho Lehtimäki, Sarah Keildson, Kathryn L Lunetta, Chunyan He, Myriam Fornage, Vasiliki Lagou, Massimo Mangino, N Charlotte Onland-Moret, Brian Chen, Joel Eriksson, Melissa Garcia, Yong Mei Liu, Annemarie Koster, Kurt Lohman, Leo-Pekka Lyytikäinen, Ann-Kristin Petersen, Jennifer Prescott, Lisette Stolk, Liesbeth Vandenput, Andrew R Wood, Wei Vivian Zhuang, Aimo Ruokonen, Anna-Liisa Hartikainen, Anneli Pouta, Stefania Bandinelli, Reiner Biffar, Georg Brabant, David G Cox, Yuhui Chen, Steven Cummings, Luigi Ferrucci, Marc J Gunter, Susan E Hankinson, Hannu Martikainen, Albert Hofman, Georg Homuth, Thomas Illig, John-Olov Jansson, Andrew D Johnson, David Karasik, Magnus Karlsson, Johannes Kettunen, Douglas P Kiel, Peter Kraft, Jingmin Liu, Östen Ljunggren, Mattias Lorentzon, Marcello Maggio, Marcello R P Markus, Dan Mellström, Iva Miljkovic, Daniel Mirel, Sarah Nelson, Laure Morin Papunen, Petra H M Peeters, Inga Prokopenko, Leslie Raffel, Martin Reincke, Alex P Reiner, Kathryn Rexrode, Fernando Rivadeneira, Stephen M Schwartz, David Siscovick, Nicole Soranzo, Doris Stöckl, Shelley Tworoger, André G Uitterlinden, Carla H van Gils, Ramachandran S Vasan, H-Erich Wichmann, Guangju Zhai, Shalender Bhasin, Martin Bidlingmaier, Stephen J Chanock, Immaculata De Vivo, Tamara B Harris, David J Hunter, Mika Kähönen, Simin Liu, Pamela Ouyang, Tim D Spector, Yvonne T van der Schouw, Jorma Viikari, Henri Wallaschofski, Mark I McCarthy, Timothy M Frayling, Anna Murray, Steve Franks, Marjo-Riitta Järvelin, Frank H de Jong, Olli Raitakari, Alexander Teumer, Claes Ohlsson, Joanne M Murabito, and John R B Perry

Subjects
Genetics, QH426-470
Abstract

Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8 × 10(-106)), PRMT6 (rs17496332, 1p13.3, p = 1.4 × 10(-11)), GCKR (rs780093, 2p23.3, p = 2.2 × 10(-16)), ZBTB10 (rs440837, 8q21.13, p = 3.4 × 10(-09)), JMJD1C (rs7910927, 10q21.3, p = 6.1 × 10(-35)), SLCO1B1 (rs4149056, 12p12.1, p = 1.9 × 10(-08)), NR2F2 (rs8023580, 15q26.2, p = 8.3 × 10(-12)), ZNF652 (rs2411984, 17q21.32, p = 3.5 × 10(-14)), TDGF3 (rs1573036, Xq22.3, p = 4.1 × 10(-14)), LHCGR (rs10454142, 2p16.3, p = 1.3 × 10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7 × 10(-08)), and UGT2B15 (rs293428, 4q13.2, p = 5.5 × 10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5 × 10(-08), women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ~15.6% and ~8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.

Published
2012
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13. Genetic determinants of serum testosterone concentrations in men.

Author

Claes Ohlsson, Henri Wallaschofski, Kathryn L Lunetta, Lisette Stolk, John R B Perry, Annemarie Koster, Ann-Kristin Petersen, Joel Eriksson, Terho Lehtimäki, Ilpo T Huhtaniemi, Geoffrey L Hammond, Marcello Maggio, Andrea D Coviello, EMAS Study Group, Luigi Ferrucci, Margit Heier, Albert Hofman, Kate L Holliday, John-Olov Jansson, Mika Kähönen, David Karasik, Magnus K Karlsson, Douglas P Kiel, Yongmei Liu, Osten Ljunggren, Mattias Lorentzon, Leo-Pekka Lyytikäinen, Thomas Meitinger, Dan Mellström, David Melzer, Iva Miljkovic, Matthias Nauck, Maria Nilsson, Brenda Penninx, Stephen R Pye, Ramachandran S Vasan, Martin Reincke, Fernando Rivadeneira, Abdelouahid Tajar, Alexander Teumer, André G Uitterlinden, Jagadish Ulloor, Jorma Viikari, Uwe Völker, Henry Völzke, H Erich Wichmann, Tsung-Sheng Wu, Wei Vivian Zhuang, Elad Ziv, Frederick C W Wu, Olli Raitakari, Anna Eriksson, Martin Bidlingmaier, Tamara B Harris, Anna Murray, Frank H de Jong, Joanne M Murabito, Shalender Bhasin, Liesbeth Vandenput, and Robin Haring

Subjects
Genetics, QH426-470
Abstract

Testosterone concentrations in men are associated with cardiovascular morbidity, osteoporosis, and mortality and are affected by age, smoking, and obesity. Because of serum testosterone's high heritability, we performed a meta-analysis of genome-wide association data in 8,938 men from seven cohorts and followed up the genome-wide significant findings in one in silico (n = 871) and two de novo replication cohorts (n = 4,620) to identify genetic loci significantly associated with serum testosterone concentration in men. All these loci were also associated with low serum testosterone concentration defined as

Published
2011
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14. Eight common genetic variants associated with serum DHEAS levels suggest a key role in ageing mechanisms.

Author

Guangju Zhai, Alexander Teumer, Lisette Stolk, John R B Perry, Liesbeth Vandenput, Andrea D Coviello, Annemarie Koster, Jordana T Bell, Shalender Bhasin, Joel Eriksson, Anna Eriksson, Florian Ernst, Luigi Ferrucci, Timothy M Frayling, Daniel Glass, Elin Grundberg, Robin Haring, Asa K Hedman, Albert Hofman, Douglas P Kiel, Heyo K Kroemer, Yongmei Liu, Kathryn L Lunetta, Marcello Maggio, Mattias Lorentzon, Massimo Mangino, David Melzer, Iva Miljkovic, MuTHER Consortium, Alexandra Nica, Brenda W J H Penninx, Ramachandran S Vasan, Fernando Rivadeneira, Kerrin S Small, Nicole Soranzo, André G Uitterlinden, Henry Völzke, Scott G Wilson, Li Xi, Wei Vivian Zhuang, Tamara B Harris, Joanne M Murabito, Claes Ohlsson, Anna Murray, Frank H de Jong, Tim D Spector, and Henri Wallaschofski

Subjects
Genetics, QH426-470
Abstract

Dehydroepiandrosterone sulphate (DHEAS) is the most abundant circulating steroid secreted by adrenal glands--yet its function is unknown. Its serum concentration declines significantly with increasing age, which has led to speculation that a relative DHEAS deficiency may contribute to the development of common age-related diseases or diminished longevity. We conducted a meta-analysis of genome-wide association data with 14,846 individuals and identified eight independent common SNPs associated with serum DHEAS concentrations. Genes at or near the identified loci include ZKSCAN5 (rs11761528; p = 3.15 × 10(-36)), SULT2A1 (rs2637125; p = 2.61 × 10(-19)), ARPC1A (rs740160; p = 1.56 × 10(-16)), TRIM4 (rs17277546; p = 4.50 × 10(-11)), BMF (rs7181230; p = 5.44 × 10(-11)), HHEX (rs2497306; p = 4.64 × 10(-9)), BCL2L11 (rs6738028; p = 1.72 × 10(-8)), and CYP2C9 (rs2185570; p = 2.29 × 10(-8)). These genes are associated with type 2 diabetes, lymphoma, actin filament assembly, drug and xenobiotic metabolism, and zinc finger proteins. Several SNPs were associated with changes in gene expression levels, and the related genes are connected to biological pathways linking DHEAS with ageing. This study provides much needed insight into the function of DHEAS.

Published
2011
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15. A genome-wide association study reveals variants in ARL15 that influence adiponectin levels.

Author

J Brent Richards, Dawn Waterworth, Stephen O'Rahilly, Marie-France Hivert, Ruth J F Loos, John R B Perry, Toshiko Tanaka, Nicholas John Timpson, Robert K Semple, Nicole Soranzo, Kijoung Song, Nuno Rocha, Elin Grundberg, Josée Dupuis, Jose C Florez, Claudia Langenberg, Inga Prokopenko, Richa Saxena, Robert Sladek, Yurii Aulchenko, David Evans, Gerard Waeber, Jeanette Erdmann, Mary-Susan Burnett, Naveed Sattar, Joseph Devaney, Christina Willenborg, Aroon Hingorani, Jaquelin C M Witteman, Peter Vollenweider, Beate Glaser, Christian Hengstenberg, Luigi Ferrucci, David Melzer, Klaus Stark, John Deanfield, Janina Winogradow, Martina Grassl, Alistair S Hall, Josephine M Egan, John R Thompson, Sally L Ricketts, Inke R König, Wibke Reinhard, Scott Grundy, H-Erich Wichmann, Phil Barter, Robert Mahley, Y Antero Kesaniemi, Daniel J Rader, Muredach P Reilly, Stephen E Epstein, Alexandre F R Stewart, Cornelia M Van Duijn, Heribert Schunkert, Keith Burling, Panos Deloukas, Tomi Pastinen, Nilesh J Samani, Ruth McPherson, George Davey Smith, Timothy M Frayling, Nicholas J Wareham, James B Meigs, Vincent Mooser, Tim D Spector, and GIANT Consortium

Subjects
Genetics, QH426-470
Abstract

The adipocyte-derived protein adiponectin is highly heritable and inversely associated with risk of type 2 diabetes mellitus (T2D) and coronary heart disease (CHD). We meta-analyzed 3 genome-wide association studies for circulating adiponectin levels (n = 8,531) and sought validation of the lead single nucleotide polymorphisms (SNPs) in 5 additional cohorts (n = 6,202). Five SNPs were genome-wide significant in their relationship with adiponectin (P< or =5x10(-8)). We then tested whether these 5 SNPs were associated with risk of T2D and CHD using a Bonferroni-corrected threshold of P< or =0.011 to declare statistical significance for these disease associations. SNPs at the adiponectin-encoding ADIPOQ locus demonstrated the strongest associations with adiponectin levels (P-combined = 9.2x10(-19) for lead SNP, rs266717, n = 14,733). A novel variant in the ARL15 (ADP-ribosylation factor-like 15) gene was associated with lower circulating levels of adiponectin (rs4311394-G, P-combined = 2.9x10(-8), n = 14,733). This same risk allele at ARL15 was also associated with a higher risk of CHD (odds ratio [OR] = 1.12, P = 8.5x10(-6), n = 22,421) more nominally, an increased risk of T2D (OR = 1.11, P = 3.2x10(-3), n = 10,128), and several metabolic traits. Expression studies in humans indicated that ARL15 is well-expressed in skeletal muscle. These findings identify a novel protein, ARL15, which influences circulating adiponectin levels and may impact upon CHD risk.

Published
2009
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