101
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Liu Y, Wang C, Chen Y, Yuan Z, Yu T, Zhang W, Tang F, Gu J, Xu Q, Chi X, Ding L, Xue F, Zhang C. A variant in KCNQ1 gene predicts metabolic syndrome among northern urban Han Chinese women. BMC MEDICAL GENETICS 2018; 19:153. [PMID: 30157802 PMCID: PMC6114251 DOI: 10.1186/s12881-018-0652-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Accepted: 07/23/2018] [Indexed: 12/30/2022]
Abstract
BACKGROUND Previous studies have reported that the potassium voltage-gated channel subfamily Q member 1 (KCNQ1) gene is associated with diabetes in both European and Asian population. This study aims to find a predictable single nucleotide polymorphism (SNP) to predict the risk of metabolic syndrome (MetS) through investigating the association of SNP in KCNQ1 gene with MetS in Han Chinese women of northern urban area. METHODS Six SNPs were selected and genotyped in 1381 unrelated women aged 21 and above, who have had physical check-up in Shandong Provincial Qianfoshan Hospital. Cox proportional model was conducted to access the association between SNPs and MetS. RESULTS Sixty one women developed MetS between 2010 and 2015 during the 3055 person-year of follow-up. The cumulative incidence density was 19.964/1000 person-year. The SNP rs163182 was associated with MetS both in the additive genetic model (RR = 1.658, 95% CI: 1.144-2.402) and in the recessive genetic model (RR = 2.461, 95% CI: 1.347-4.496). It remained significant after adjustment. This relationship was also observed in MetS components (BMI and SBP). CONCLUSION A novel association between rs163182 and MetS was found in this study, which can predict the occurrence of MetS among northern urban Han Chinese women. More investigations are needed to be done to assess the possible pathway in which KCNQ1 gene affects MetS.
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Affiliation(s)
- Yafei Liu
- Division of Biostatistics, School of Public Health, Shandong University, 44 Wenhua Xilu, Jinan, 250010, Shandong, China.,Shandong Provincial Qianfoshan Hospital, Shandong University, 16766 Jingshi Rd, Jinan, 250014, China
| | - Chunxia Wang
- Jinan Kingmed Center for Clinical Laboratory Co, Ltd., 554 Zhengfeng Rd, Jinan, 250010, Shandong, China
| | - Yafei Chen
- Linyi Centre for Adverse Drug Reaction Monitoring, Linyi, 276000, Shandong, China
| | - Zhongshang Yuan
- Division of Biostatistics, School of Public Health, Shandong University, 44 Wenhua Xilu, Jinan, 250010, Shandong, China
| | - Tao Yu
- Division of Biostatistics, School of Public Health, Shandong University, 44 Wenhua Xilu, Jinan, 250010, Shandong, China
| | - Wenchao Zhang
- Shandong Provincial Qianfoshan Hospital, Shandong University, 16766 Jingshi Rd, Jinan, 250014, China
| | - Fang Tang
- Shandong Provincial Qianfoshan Hospital, Shandong University, 16766 Jingshi Rd, Jinan, 250014, China
| | - Jianhua Gu
- Division of Biostatistics, School of Public Health, Shandong University, 44 Wenhua Xilu, Jinan, 250010, Shandong, China
| | - Qinqin Xu
- Division of Biostatistics, School of Public Health, Shandong University, 44 Wenhua Xilu, Jinan, 250010, Shandong, China
| | - Xiaotong Chi
- Department of Imaging and Nuclear Medicine, Taishan Medical University, 619 Changcheng Rd, Tai'an, 271016, Shandong, China
| | - Lijie Ding
- Division of Biostatistics, School of Public Health, Shandong University, 44 Wenhua Xilu, Jinan, 250010, Shandong, China
| | - Fuzhong Xue
- Division of Biostatistics, School of Public Health, Shandong University, 44 Wenhua Xilu, Jinan, 250010, Shandong, China.
| | - Chengqi Zhang
- Shandong Provincial Qianfoshan Hospital, Shandong University, 16766 Jingshi Rd, Jinan, 250014, China.
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102
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A Large Multiethnic Genome-Wide Association Study of Adult Body Mass Index Identifies Novel Loci. Genetics 2018; 210:499-515. [PMID: 30108127 DOI: 10.1534/genetics.118.301479] [Citation(s) in RCA: 109] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Accepted: 08/08/2018] [Indexed: 12/31/2022] Open
Abstract
Body mass index (BMI), a proxy measure for obesity, is determined by both environmental (including ethnicity, age, and sex) and genetic factors, with > 400 BMI-associated loci identified to date. However, the impact, interplay, and underlying biological mechanisms among BMI, environment, genetics, and ancestry are not completely understood. To further examine these relationships, we utilized 427,509 calendar year-averaged BMI measurements from 100,418 adults from the single large multiethnic Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. We observed substantial independent ancestry and nationality differences, including ancestry principal component interactions and nonlinear effects. To increase the list of BMI-associated variants before assessing other differences, we conducted a genome-wide association study (GWAS) in GERA, with replication in the Genetic Investigation of Anthropomorphic Traits (GIANT) consortium combined with the UK Biobank (UKB), followed by GWAS in GERA combined with GIANT, with replication in the UKB. We discovered 30 novel independent BMI loci (P < 5.0 × 10-8) that replicated. We then assessed the proportion of BMI variance explained by sex in the UKB using previously identified loci compared to previously and newly identified loci and found slight increases: from 3.0 to 3.3% for males and from 2.7 to 3.0% for females. Further, the variance explained by previously and newly identified variants decreased with increasing age in the GERA and UKB cohorts, echoed in the variance explained by the entire genome, which also showed gene-age interaction effects. Finally, we conducted a tissue expression QTL enrichment analysis, which revealed that GWAS BMI-associated variants were enriched in the cerebellum, consistent with prior work in humans and mice.
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103
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Fan HY, Huang YT, Hsieh RH, Chao JCJ, Tung YC, Lee YL, Chen YC. Birthweight, time-varying adiposity growth and early menarche in girls: A Mendelian randomisation and mediation analysis. Obes Res Clin Pract 2018; 12:445-451. [PMID: 30082248 DOI: 10.1016/j.orcp.2018.07.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2018] [Revised: 06/21/2018] [Accepted: 07/13/2018] [Indexed: 10/28/2022]
Abstract
OBJECTIVE To explore the causal effect of time-varying z-BMI growth on early menarche using Mendelian randomisation (MR); to identify critical adiposity predictors of early menarche; to compare the effects of birthweight and time-varying z-BMI growth as mediators of the path from genes to early menarche using mediation analysis. METHODS We used data from the Taiwan Children Health Study with 21 obesity-related single-nucleotide polymorphisms (SNPs) to yield genetic (instrumental variable)IVs for adiposity. Children with available data on genotyping, birthweight, adiposity, and menarcheal age were included. RESULTS In MR analyses, results based on the time-varying z-BMI growth show more statistical power and capture more information of adiposity growth (p=0.01) than those based on single point z-BMI (p=0.02). Among adiposity measures, critical predictors of early menarche are fat free mass (RR=1.33, 95% CI 1.07-1.65) and waist/height ratio (RR=1.27, 95% CI 1.03-1.56). Other potential predictors of early menarche are sum of skinfold (RR=1.24, 95% CI 1.03-1.48) and total body fat (RR=1.20, 95% CI 1.05-1.38). In both one-mediation and multi-mediation analyses, time-varying z-BMI growth in the prepubertal years plays a crucial mediator in the pathway from the genes to early menarche. CONCLUSIONS This study discovered that greater prepubertal adiposity growth is a crucial mediator in the path from genes to early menarche. For girls with genes positively associated with obesity; and/or of lower birthweight, a strategy to prevent childhood adiposity should be implemented in order to avoid early menarche development.
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Affiliation(s)
- Hsien-Yu Fan
- Department of Family Medicine, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | | | - Rong-Hong Hsieh
- School of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, Taipei, Taiwan
| | - Jane C-J Chao
- School of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, Taipei, Taiwan; Master Program in Global Health and Development, Taipei Medical University, Taipei, Taiwan; Nutrition Research Center, Taipei Medical University Hospital, Taipei, Taiwan
| | - Yi-Ching Tung
- Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan
| | - Yungling L Lee
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan; Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.
| | - Yang-Ching Chen
- Department of Family Medicine, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan; School of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, Taipei, Taiwan; Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Graduate Institute of Metabolism and Obesity Sciences, Taipei Medical University, Taipei, Taiwan.
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104
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Zhou X, Cheung CL, Karasugi T, Karppinen J, Samartzis D, Hsu YH, Mak TSH, Song YQ, Chiba K, Kawaguchi Y, Li Y, Chan D, Cheung KMC, Ikegawa S, Cheah KSE, Sham PC. Trans-Ethnic Polygenic Analysis Supports Genetic Overlaps of Lumbar Disc Degeneration With Height, Body Mass Index, and Bone Mineral Density. Front Genet 2018; 9:267. [PMID: 30127800 PMCID: PMC6088183 DOI: 10.3389/fgene.2018.00267] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Accepted: 07/02/2018] [Indexed: 01/08/2023] Open
Abstract
Lumbar disc degeneration (LDD) is age-related break-down in the fibrocartilaginous joints between lumbar vertebrae. It is a major cause of low back pain and is conventionally assessed by magnetic resonance imaging (MRI). Like most other complex traits, LDD is likely polygenic and influenced by both genetic and environmental factors. However, genome-wide association studies (GWASs) of LDD have uncovered few susceptibility loci due to the limited sample size. Previous epidemiology studies of LDD also reported multiple heritable risk factors, including height, body mass index (BMI), bone mineral density (BMD), lipid levels, etc. Genetics can help elucidate causality between traits and suggest loci with pleiotropic effects. One such approach is polygenic score (PGS) which summarizes the effect of multiple variants by the summation of alleles weighted by estimated effects from GWAS. To investigate genetic overlaps of LDD and related heritable risk factors, we calculated the PGS of height, BMI, BMD and lipid levels in a Chinese population-based cohort with spine MRI examination and a Japanese case-control cohort of lumbar disc herniation (LDH) requiring surgery. Because most large-scale GWASs were done in European populations, PGS of corresponding traits were created using weights from European GWASs. We calibrated their prediction performance in independent Chinese samples, then tested associations with MRI-derived LDD scores and LDH affection status. The PGS of height, BMI, BMD and lipid levels were strongly associated with respective phenotypes in Chinese, but phenotype variances explained were lower than in Europeans which would reduce the power to detect genetic overlaps. Despite of this, the PGS of BMI and lumbar spine BMD were significantly associated with LDD scores; and the PGS of height was associated with the increased the liability of LDH. Furthermore, linkage disequilibrium score regression suggested that, osteoarthritis, another degenerative disorder that shares common features with LDD, also showed genetic correlations with height, BMI and BMD. The findings suggest a common key contribution of biomechanical stress to the pathogenesis of LDD and will direct the future search for pleiotropic genes.
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Affiliation(s)
- Xueya Zhou
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong.,Department of Systems Biology, Department of Pediatrics, Columbia University Medical Center, New York, NY, United States
| | - Ching-Lung Cheung
- Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong.,Li Ka Shing Faculty of Medicine, Center for Genomic Sciences, The University of Hong Kong, Hong Kong, Hong Kong
| | - Tatsuki Karasugi
- Department of Orthopaedic Surgery, Faculty of Life Sciences, Kumamoto University, Kumamoto City, Japan
| | - Jaro Karppinen
- Medical Research Center Oulu, University of Oulu and Oulu University Hospital, Oulu, Finland
| | - Dino Samartzis
- Department of Orthopaedics and Traumatology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong
| | - Yi-Hsiang Hsu
- Hebrew SeniorLife, Institute for Aging Research, Roslindale, MA, United States.,Harvard Medical School, Boston, MA, United States.,Molecular and Integrative Physiological Sciences Program, Harvard School of Public Health, Boston, MA, United States
| | - Timothy Shin-Heng Mak
- Li Ka Shing Faculty of Medicine, Center for Genomic Sciences, The University of Hong Kong, Hong Kong, Hong Kong
| | - You-Qiang Song
- Li Ka Shing Faculty of Medicine, Center for Genomic Sciences, The University of Hong Kong, Hong Kong, Hong Kong.,Li Ka Shing Faculty of Medicine, School of Biomedical Science, The University of Hong Kong, Hong Kong, Hong Kong
| | - Kazuhiro Chiba
- Department of Orthopedic Surgery, National Defense Medical College, Tokorozawa, Saitama, Japan
| | - Yoshiharu Kawaguchi
- Department of Orthopaedic Surgery, Toyama University, Toyama Prefecture, Japan
| | - Yan Li
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong
| | - Danny Chan
- Li Ka Shing Faculty of Medicine, School of Biomedical Science, The University of Hong Kong, Hong Kong, Hong Kong
| | - Kenneth Man-Chee Cheung
- Department of Orthopaedics and Traumatology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong
| | - Shiro Ikegawa
- Laboratory of Bone and Joint Diseases, Center for Integrative Medical Sciences, RIKEN, Tokyo, Japan
| | - Kathryn Song-Eng Cheah
- Li Ka Shing Faculty of Medicine, School of Biomedical Science, The University of Hong Kong, Hong Kong, Hong Kong
| | - Pak Chung Sham
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong.,Li Ka Shing Faculty of Medicine, Center for Genomic Sciences, The University of Hong Kong, Hong Kong, Hong Kong
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105
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Causal relationships between adiposity and childhood asthma: bi-directional Mendelian Randomization analysis. Int J Obes (Lond) 2018; 43:73-81. [PMID: 30026589 DOI: 10.1038/s41366-018-0160-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Revised: 06/03/2018] [Accepted: 06/15/2018] [Indexed: 01/07/2023]
Abstract
BACKGROUND/OBJECTIVES Obesity and asthma are common chronic diseases and have been reported to be mutually causative. We investigated the causal direction of the relationship between adiposity and asthma using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. SUBJECTS/METHODS We used data from the Taiwan Children Health Study with 24 body mass index (BMI)-single-nucleotide polymorphisms (SNPs, combined into a weighted allelic score) and 16 asthma-SNPs (combined into two weighted allelic scores, separately for asthma inflammatory and antioxidative genes) to yield genetic IVs for adiposity and asthma, respectively. RESULTS The weighted allele score for BMI was strongly associated with adiposity (p = 2 × 10-16) and active asthma (p = 0.03). The two-stage least square regression risk ratio (RR) for the effect of BMI on asthma was 1.04 (95% confidence interval: 1.00-1.07, p = 0.03). Although the weighted asthma genetic scores were significantly associated with asthma (p = 8.4 × 10-3), no association was seen for genetically instrumented asthma with BMI using MR. Central obesity was the most accurate predictor of asthma. Adiposity showed higher causal effects on asthma in boys and children with non-atopic asthma. Sensitivity analysis for MR revealed no directional genetic pleiotropy effects. The causal effect RRs of BMI on asthma were 1.04, 1.08, and 1.03 for inverse-variance weighted, MR-Egger regression (slope), and weighted median methods, respectively, all in accordance with the MR estimates. CONCLUSIONS High adiposity may lead to asthma, whereas the effects of asthma on adiposity accumulation are likely to be small.
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106
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Dong SS, Zhang YJ, Chen YX, Yao S, Hao RH, Rong Y, Niu HM, Chen JB, Guo Y, Yang TL. Comprehensive review and annotation of susceptibility SNPs associated with obesity-related traits. Obes Rev 2018. [PMID: 29527783 DOI: 10.1111/obr.12677] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
We aimed to summarize the results of genetic association studies for obesity and provide a comprehensive annotation of all susceptibility single nucleotide polymorphisms (SNPs). A total of 72 studies were summarized, resulting in 90,361 susceptibility SNPs (738 index SNPs and 89,623 linkage disequilibrium SNPs). Over 90% of the susceptibility SNPs are located in non-coding regions, and it is challenging to understand their functional significance. Therefore, we annotated these SNPs by using various functional databases. We identified 24,623 functional SNPs, including 4 nonsense SNPs, 479 missense SNPs, 399 untranslated region SNPs which might affect microRNA binding, 262 promoter and 5,492 enhancer SNPs which might affect transcription factor binding, 7 splicing sites, 76 SNPs which might affect gene methylation levels, 1,839 SNPs under natural selection and 17,351 SNPs which might modify histone binding. Expression quantitative trait loci analyses for functional SNPs identified 98 target genes, including 69 protein coding genes, 27 long non-coding RNAs and 3 processed transcripts. The percentage of protein coding genes that could be correlated with obesity-related pathways directly or through gene-gene interaction is 75.36 (52/69). Our results may serve as an encyclopaedia of obesity susceptibility SNPs and offer guide for functional experiments.
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Affiliation(s)
- S-S Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Y-J Zhang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Y-X Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - S Yao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - R-H Hao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Y Rong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - H-M Niu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - J-B Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Y Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - T-L Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, and Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
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107
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Identification of rs7350481 at chromosome 11q23.3 as a novel susceptibility locus for metabolic syndrome in Japanese individuals by an exome-wide association study. Oncotarget 2018; 8:39296-39308. [PMID: 28445147 PMCID: PMC5503614 DOI: 10.18632/oncotarget.16945] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2017] [Accepted: 03/14/2017] [Indexed: 12/12/2022] Open
Abstract
We have performed exome-wide association studies to identify genetic variants that influence body mass index or confer susceptibility to obesity or metabolic syndrome in Japanese. The exome-wide association study for body mass index included 12,890 subjects, and those for obesity and metabolic syndrome included 12,968 subjects (3954 individuals with obesity, 9014 controls) and 6817 subjects (3998 individuals with MetS, 2819 controls), respectively. Exome-wide association studies were performed with Illumina HumanExome-12 DNA Analysis BeadChip or Infinium Exome-24 BeadChip arrays. The relation of genotypes of single nucleotide polymorphisms to body mass index was examined by linear regression analysis, and that of allele frequencies of single nucleotide polymorphisms to obesity or metabolic syndrome was evaluated with Fisher's exact test. The exome-wide association studies identified six, 11, and 40 single nucleotide polymorphisms as being significantly associated with body mass index, obesity (P <1.21 × 10−6), or metabolic syndrome (P <1.20 × 10−6), respectively. Subsequent multivariable logistic regression analysis with adjustment for age and sex revealed that three and five single nucleotide polymorphisms were related (P < 0.05) to obesity or metabolic syndrome, respectively, with one of these latter polymorphisms—rs7350481 (C/T) at chromosome 11q23.3—also being significantly (P < 3.13 × 10−4) associated with metabolic syndrome. The polymorphism rs7350481 may thus be a novel susceptibility locus for metabolic syndrome in Japanese. In addition, single nucleotide polymorphisms in three genes (CROT, TSC1, RIN3) and at four loci (ANKK1, ZNF804B, CSRNP3, 17p11.2) were implicated as candidate determinants of obesity and metabolic syndrome, respectively.
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108
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Mora-García G, Gómez-Camargo D, Alario Á, Gómez-Alegría C. A Common Variation in the Caveolin 1 Gene Is Associated with High Serum Triglycerides and Metabolic Syndrome in an Admixed Latin American Population. Metab Syndr Relat Disord 2018; 16:453-463. [PMID: 29762069 PMCID: PMC6211369 DOI: 10.1089/met.2018.0004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Background: The caveolin 1 (CAV1) gene has been associated with metabolic traits in animal models and human cohorts. Recently, a prevalent variant in CAV1 has been found to be related to metabolic syndrome in Hispanics living in North America. Since Hispanics represent an admixed population at high risk for cardiovascular diseases, in this study a Latin American population with a similar genetic background was assessed. Objective: To analyze a genetic association between CAV1 and metabolic traits in an admixed Latin American population. Methods: A cross-sectional study was carried out with adults from the Colombian Caribbean Coast, selected in urban clusters and work places through a stratified sampling to include diverse ages and socioeconomic groups. Blood pressure and waist circumference were registered. Serum concentrations of glucose, triglycerides, and high-density lipoprotein cholesterol were measured from an 8-hr fasting whole-blood sample. Two previously analyzed CAV1 single nucleotide polymorphisms were genotyped (rs926198 and rs11773845). A logistic regression model was applied to estimate the associations. An admixture adjustment was performed through a Bayesian model. Results: A total of 605 subjects were included. rs11773845 was associated with hypertriglyceridemia [odds ratio (OR) = 1.33, p = 0.001] and the metabolic syndrome (OR = 1.53, p = 0.02). When admixture adjustment was performed these genetic associations preserved their statistical significance. There were no significant associations between rs926198 and metabolic traits. Conclusions: The CAV1 variation rs11773845 was found to be consistently associated with high serum triglycerides and the metabolic syndrome. This is the first report of a relationship between CAV1 variants and serum triglycerides in Latin America.
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Affiliation(s)
- Gustavo Mora-García
- 1 Grupo UNIMOL, Facultad de Medicina, Universidad de Cartagena , Cartagena de Indias, Colombia
| | - Doris Gómez-Camargo
- 1 Grupo UNIMOL, Facultad de Medicina, Universidad de Cartagena , Cartagena de Indias, Colombia
| | - Ángelo Alario
- 2 Departamento Médico, Facultad de Medicina, Universidad de Cartagena , Cartagena de Indias, Colombia
| | - Claudio Gómez-Alegría
- 3 Grupo de Investigación UNIMOL, Departamento de Farmacia, Facultad de Ciencias, Universidad Nacional de Colombia , Bogotá, Colombia
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109
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Yamada Y, Sakuma J, Takeuchi I, Yasukochi Y, Kato K, Oguri M, Fujimaki T, Horibe H, Muramatsu M, Sawabe M, Fujiwara Y, Taniguchi Y, Obuchi S, Kawai H, Shinkai S, Mori S, Arai T, Tanaka M. Identification of polymorphisms in 12q24.1, ACAD10, and BRAP as novel genetic determinants of blood pressure in Japanese by exome-wide association studies. Oncotarget 2018; 8:43068-43079. [PMID: 28562329 PMCID: PMC5522128 DOI: 10.18632/oncotarget.17474] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2017] [Accepted: 04/05/2017] [Indexed: 12/29/2022] Open
Abstract
We performed exome-wide association studies to identify genetic variants that influence systolic or diastolic blood pressure or confer susceptibility to hypertension in Japanese. The exome-wide association studies were performed with the use of Illumina HumanExome-12 DNA Analysis BeadChip or Infinium Exome-24 BeadChip arrays and with 14,678 subjects, including 8215 individuals with hypertension and 6463 controls. The relation of genotypes of 41,843 single nucleotide polymorphisms to systolic or diastolic blood pressure was examined by linear regression analysis. After Bonferroni's correction, 44 and eight polymorphisms were significantly (P < 1.19 × 10−6) associated with systolic or diastolic blood pressure, respectively, with six polymorphisms (rs12229654, rs671, rs11066015, rs2074356, rs3782886, rs11066280) being associated with both systolic and diastolic blood pressure. Examination of the relation of allele frequencies to hypertension with Fisher's exact test revealed that 100 of the 41,843 single nucleotide polymorphisms were significantly (P < 1.19 × 10−6) associated with hypertension. Subsequent multivariable logistic regression analysis with adjustment for age and sex showed that five polymorphisms (rs150854849, rs202069030, rs139012426, rs12229654, rs76974938) were significantly (P < 1.25 × 10−4) associated with hypertension. The polymorphism rs12229654 was thus associated with both systolic and diastolic blood pressure and with hypertension. Six polymorphisms (rs12229654 at 12q24.1, rs671 of ALDH2, rs11066015 of ACAD10, rs2074356 and rs11066280 of HECTD4, and rs3782886 of BRAP) were found to be associated with both systolic and diastolic blood pressure, with those at 12q24.1 or in ACAD10 or BRAP being novel determinants of blood pressure in Japanese.
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Affiliation(s)
- Yoshiji Yamada
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Japan.,CREST, Japan Science and Technology Agency, Kawaguchi, Japan
| | - Jun Sakuma
- CREST, Japan Science and Technology Agency, Kawaguchi, Japan.,Computer Science Department, College of Information Science, University of Tsukuba, Tsukuba, Japan.,RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Ichiro Takeuchi
- CREST, Japan Science and Technology Agency, Kawaguchi, Japan.,RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.,Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan
| | - Yoshiki Yasukochi
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Japan.,CREST, Japan Science and Technology Agency, Kawaguchi, Japan
| | - Kimihiko Kato
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Japan.,Department of Internal Medicine, Meitoh Hospital, Nagoya, Japan
| | - Mitsutoshi Oguri
- Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Japan.,Department of Cardiology, Kasugai Municipal Hospital, Kasugai, Japan
| | - Tetsuo Fujimaki
- Department of Cardiovascular Medicine, Inabe General Hospital, Inabe, Japan
| | - Hideki Horibe
- Department of Cardiovascular Medicine, Gifu Prefectural Tajimi Hospital, Tajimi, Japan
| | - Masaaki Muramatsu
- Department of Molecular Epidemiology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
| | - Motoji Sawabe
- Section of Molecular Pathology, Graduate School of Health Care Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yoshinori Fujiwara
- Research Team for Social Participation and Community Health, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Yu Taniguchi
- Research Team for Social Participation and Community Health, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Shuichi Obuchi
- Research Team for Promoting Support System for Home Care, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Hisashi Kawai
- Research Team for Promoting Support System for Home Care, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Shoji Shinkai
- Research Team for Social Participation and Health Promotion, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Seijiro Mori
- Center for Promotion of Clinical Investigation, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan
| | - Tomio Arai
- Department of Pathology, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan
| | - Masashi Tanaka
- Department of Clinical Laboratory, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan
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110
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Fan HY, Lee YL, Yang SH, Chien YW, Chao JCJ, Chen YC. Comprehensive determinants of growth trajectories and body composition in school children: A longitudinal cohort study. Obes Res Clin Pract 2018; 12:270-276. [DOI: 10.1016/j.orcp.2017.11.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Revised: 11/20/2017] [Accepted: 11/27/2017] [Indexed: 12/31/2022]
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111
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Tang R, Liu H, Yuan Y, Xie K, Xu P, Liu X, Wen J. Genetic factors associated with risk of metabolic syndrome and hepatocellular carcinoma. Oncotarget 2018; 8:35403-35411. [PMID: 28515345 PMCID: PMC5471064 DOI: 10.18632/oncotarget.15893] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Accepted: 02/15/2017] [Indexed: 01/01/2023] Open
Abstract
Although the metabolic syndrome is a commonplace topic, its potential threats to public health is a problem that cannot be neglected. As the living conditions improved significantly over the past few years, the morbidity of metabolic syndrome has also steadily risen, and the onset age is becoming younger. The hepatocellular carcinoma (HCC), is one of the most prevalent life-threatening human cancers worldwide, incidence of which is also on the rise, gradually occupied the top of the list associated with metabolic syndrome related complication. Despite the advanced improvement of HCC management, the lifestyle, environmental factors, obesity, hepatitis B virus (HBV) infection have been recognized as risk factors for the development of liver cancer. In recent years, genetic studies, especially the genome-wide association studies (GWASs) were widely performed, a new era of the human genome research was created, which has significantly promoted the study of complex disease genetics. These progresses have contributed to the discovery of abundant number of genomic loci convincingly linked with complex metabolic feature and HCC. In this review, we briefly summarize the association between metabolic syndrome and HCC, focusing on the genetic factors contributed to metabolic syndrome and HCC.
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Affiliation(s)
- Ranran Tang
- Nanjing Maternity and Child Health Care Institute, Nanjing Maternity and Child Health Care Hospital, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Maternity and Child Health Care Hospital, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Heng Liu
- Department of Pediatrics, Nanjing Maternity and Child Health Care Hospital, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Yingdi Yuan
- Nanjing Maternity and Child Health Care Institute, Nanjing Maternity and Child Health Care Hospital, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Kaipeng Xie
- Nanjing Maternity and Child Health Care Institute, Nanjing Maternity and Child Health Care Hospital, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Maternity and Child Health Care Hospital, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Pengfei Xu
- Nanjing Maternity and Child Health Care Institute, Nanjing Maternity and Child Health Care Hospital, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Maternity and Child Health Care Hospital, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Xiaoyun Liu
- Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Juan Wen
- Nanjing Maternity and Child Health Care Institute, Nanjing Maternity and Child Health Care Hospital, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Maternity and Child Health Care Hospital, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, China
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112
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Roy Choudhury A, Cheng T, Phan L, Bryant SH, Wang Y. Supporting precision medicine by data mining across multi-disciplines: an integrative approach for generating comprehensive linkages between single nucleotide variants (SNVs) and drug-binding sites. Bioinformatics 2018; 33:1621-1629. [PMID: 28158543 DOI: 10.1093/bioinformatics/btx031] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Accepted: 01/27/2017] [Indexed: 11/13/2022] Open
Abstract
Motivation Genetic variants in drug targets and metabolizing enzymes often have important functional implications, including altering the efficacy and toxicity of drugs. Identifying single nucleotide variants (SNVs) that contribute to differences in drug response and understanding their underlying mechanisms are fundamental to successful implementation of the precision medicine model. This work reports an effort to collect, classify and analyze SNVs that may affect the optimal response to currently approved drugs. Results An integrated approach was taken involving data mining across multiple information resources including databases containing drugs, drug targets, chemical structures, protein-ligand structure complexes, genetic and clinical variations as well as protein sequence alignment tools. We obtained 2640 SNVs of interest, most of which occur rarely in populations (minor allele frequency < 0.01). Clinical significance of only 9.56% of the SNVs is known in ClinVar, although 79.02% are predicted as deleterious. The examples here demonstrate that even if the mapped SNVs predicted as deleterious may not result in significant structural modifications, they can plausibly modify the protein-drug interactions, affecting selectivity and drug-binding affinity. Our analysis identifies potentially deleterious SNVs present on drug-binding residues that are relevant for further studies in the context of precision medicine. Availability and Implementation Data are available from Supplementary information file. Contact yanli.wang@nih.gov. Supplementary information Supplementary Tables S1-S5 are available at Bioinformatics online.
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Affiliation(s)
- Amrita Roy Choudhury
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA
| | - Tiejun Cheng
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA
| | - Lon Phan
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA
| | - Stephen H Bryant
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA
| | - Yanli Wang
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA
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113
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Pigeyre M, Saqlain M, Turcotte M, Raja GK, Meyre D. Obesity genetics: insights from the Pakistani population. Obes Rev 2018; 19:364-380. [PMID: 29265593 DOI: 10.1111/obr.12644] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Revised: 10/10/2017] [Accepted: 10/15/2017] [Indexed: 01/26/2023]
Abstract
The Pakistani population is extensively diverse, indicating a genetic admixture of European and Central/West Asian migrants with indigenous South Asian gene pools. Pakistanis are organized in different ethnicities/castes based on cultural, linguistic and geographical origin. While Pakistan is facing a rapid nutritional transition, the rising prevalence of obesity is driving a growing burden of health complications and mortality. This represents a unique opportunity for the research community to study the interplay between obesogenic environmental changes and obesity predisposing genes in the time frame of one generation. This review recapitulates the ancestral origins of Pakistani population, the societal determinants of the rise in obesity and its governmental management. We describe the contribution of syndromic, monogenic non-syndromic and polygenic obesity genes identified in the Pakistani population. We then discuss the utility of gene identification approaches based on large consanguineous families and original gene × environment interaction study designs in discovering new obesity genes and causal pathways. Elucidation of the genetic basis of obesity in the Pakistani population may result in improved methods of obesity prevention and treatment globally.
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Affiliation(s)
- M Pigeyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.,Department of Nutrition, CHRU Lille, University of Lille, Lille, France
| | - M Saqlain
- Department of Biochemistry, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan
| | - M Turcotte
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - G K Raja
- Department of Biochemistry, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan
| | - D Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
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114
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Gong J, Nishimura KK, Fernandez-Rhodes L, Haessler J, Bien S, Graff M, Lim U, Lu Y, Gross M, Fornage M, Yoneyama S, Isasi CR, Buzkova P, Daviglus M, Lin DY, Tao R, Goodloe R, Bush WS, Farber-Eger E, Boston J, Dilks HH, Ehret G, Gu CC, Lewis CE, Nguyen KDH, Cooper R, Leppert M, Irvin MR, Bottinger EP, Wilkens LR, Haiman CA, Park L, Monroe KR, Cheng I, Stram DO, Carlson CS, Jackson R, Kuller L, Houston D, Kooperberg C, Buyske S, Hindorff LA, Crawford DC, Loos RJ, Le Marchand L, Matise TC, North KE, Peters U. Trans-ethnic analysis of metabochip data identifies two new loci associated with BMI. Int J Obes (Lond) 2018; 42:384-390. [PMID: 29381148 PMCID: PMC5876082 DOI: 10.1038/ijo.2017.304] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2016] [Revised: 11/03/2017] [Accepted: 11/21/2017] [Indexed: 01/05/2023]
Abstract
OBJECTIVE Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population. SUBJECTS Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models. RESULTS We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10-7). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue. CONCLUSION Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.
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Affiliation(s)
- Jian Gong
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Katherine K. Nishimura
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Lindsay Fernandez-Rhodes
- Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Jeffery Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Stephanie Bien
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Misa Graff
- Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Unhee Lim
- Cancer Research Center, University of Hawaii, Honolulu, Hawaii, United States of America
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - Myron Gross
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Myriam Fornage
- Health Science Center, University of Texas, Austin, Texas, United States of America
| | - Sachiko Yoneyama
- Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Carmen R. Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Petra Buzkova
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Martha Daviglus
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, U United States of America SA
| | - Dan-Yu Lin
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Ran Tao
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Robert Goodloe
- Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - William S. Bush
- Department of Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Eric Farber-Eger
- Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Jonathan Boston
- Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Holli H. Dilks
- Sarah Cannon Research Institute, Nashville, Tennessee, United States of America
| | - Georg Ehret
- Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Division of Cardiology, Geneva University Hospital, Geneva, Switzerland
| | - C. Charles Gu
- Department of Biostatistics, Washington University, St. Louis, Missouri, United States of America
| | - Cora E. Lewis
- Department of Medicine, University of Alabama, Birmingham, Alabama, United States of America
| | - Khanh-Dung H. Nguyen
- Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Richard Cooper
- Preventive Medicine and Epidemiology, Loyola University, Chicago, Illinois, United States of America
| | - Mark Leppert
- Department of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama, Birmingham, Alabama, United States of America
| | - Erwin P. Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Lynne R. Wilkens
- Cancer Research Center, University of Hawaii, Honolulu, Hawaii, United States of America
| | - Christopher A. Haiman
- Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Lani Park
- Cancer Research Center, University of Hawaii, Honolulu, Hawaii, United States of America
| | - Kristine R. Monroe
- Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Iona Cheng
- Cancer Prevention Institute of California, Fremont, California, United States of America
| | - Daniel O. Stram
- Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Christopher S. Carlson
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Rebecca Jackson
- Department of Internal Medicine, Ohio State Medical Center, Columbus, Ohio, United States of America
| | - Lew Kuller
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Denise Houston
- Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Steven Buyske
- Department of Genetics, Rutgers University, Piscataway, New Jersey, United States of America
- Department of Statistics and Biostatistics, Rutgers University, Piscataway, New Jersey, United States of America
| | - Lucia A. Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Dana C. Crawford
- Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Ruth J.F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Loic Le Marchand
- Cancer Research Center, University of Hawaii, Honolulu, Hawaii, United States of America
| | - Tara C. Matise
- Department of Genetics, Rutgers University, Piscataway, New Jersey, United States of America
| | - Kari E. North
- Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
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115
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Goodarzi MO. Genetics of obesity: what genetic association studies have taught us about the biology of obesity and its complications. Lancet Diabetes Endocrinol 2018; 6:223-236. [PMID: 28919064 DOI: 10.1016/s2213-8587(17)30200-0] [Citation(s) in RCA: 259] [Impact Index Per Article: 43.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 05/24/2017] [Accepted: 05/24/2017] [Indexed: 01/01/2023]
Abstract
Genome-wide association studies (GWAS) for BMI, waist-to-hip ratio, and other adiposity traits have identified more than 300 single-nucleotide polymorphisms (SNPs). Although there is reason to hope that these discoveries will eventually lead to new preventive and therapeutic agents for obesity, this will take time because such developments require detailed mechanistic understanding of how an SNP influences phenotype (and this information is largely unavailable). Fortunately, absence of functional information has not prevented GWAS findings from providing insights into the biology of obesity. Genes near loci regulating total body mass are enriched for expression in the CNS, whereas genes for fat distribution are enriched in adipose tissue itself. Gene by environment and lifestyle interaction analyses have revealed that our increasingly obesogenic environment might be amplifying genetic risk for obesity, yet those at highest risk could mitigate this risk by increasing physical activity and possibly by avoiding specific dietary components. GWAS findings have also been used in mendelian randomisation analyses probing the causal association between obesity and its many putative complications. In supporting a causal association of obesity with diabetes, coronary heart disease, specific cancers, and other conditions, these analyses have clinical relevance in identifying which outcomes could be preventable through weight loss interventions.
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Affiliation(s)
- Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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116
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Tan KHX, Tan LWL, Sim X, Tai ES, Lee JJM, Chia KS, van Dam RM. Cohort Profile: The Singapore Multi-Ethnic Cohort (MEC) study. Int J Epidemiol 2018; 47:699-699j. [PMID: 29452397 DOI: 10.1093/ije/dyy014] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 01/15/2018] [Accepted: 01/25/2018] [Indexed: 12/11/2022] Open
Affiliation(s)
| | | | | | - E Shyong Tai
- Saw Swee Hock School of Public Health and.,Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
| | | | | | - Rob M van Dam
- Saw Swee Hock School of Public Health and.,Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
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117
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Nakagawa-Senda H, Hachiya T, Shimizu A, Hosono S, Oze I, Watanabe M, Matsuo K, Ito H, Hara M, Nishida Y, Endoh K, Kuriki K, Katsuura-Kamano S, Arisawa K, Nindita Y, Ibusuki R, Suzuki S, Hosono A, Mikami H, Nakamura Y, Takashima N, Nakamura Y, Kuriyama N, Ozaki E, Furusyo N, Ikezaki H, Nakatochi M, Sasakabe T, Kawai S, Okada R, Hishida A, Naito M, Wakai K, Momozawa Y, Kubo M, Tanaka H. A genome-wide association study in the Japanese population identifies the 12q24 locus for habitual coffee consumption: The J-MICC Study. Sci Rep 2018; 8:1493. [PMID: 29367735 PMCID: PMC5784172 DOI: 10.1038/s41598-018-19914-w] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Accepted: 01/08/2018] [Indexed: 12/01/2022] Open
Abstract
Coffee is one of the most widely consumed beverages worldwide, and its role in human health has received much attention. Although genome-wide association studies (GWASs) have investigated genetic variants associated with coffee consumption in European populations, no such study has yet been conducted in an Asian population. Here, we conducted a GWAS to identify common genetic variations that affected coffee consumption in a Japanese population of 11,261 participants recruited as a part of the Japan Multi-Institutional Collaborative Cohort (J-MICC) study. Coffee consumption was collected using a self-administered questionnaire, and converted from categories to cups/day. In the discovery stage (n = 6,312), we found 2 independent loci (12q24.12–13 and 5q33.3) that met suggestive significance (P < 1 × 10−6). In the replication stage (n = 4,949), the lead variant for the 12q24.12–13 locus (rs2074356) was significantly associated with habitual coffee consumption (P = 2.2 × 10−6), whereas the lead variant for the 5q33.3 locus (rs1957553) was not (P = 0.53). A meta-analysis of the discovery and replication populations, and the combined analysis using all subjects, revealed that rs2074356 achieved genome-wide significance (P = 2.2 × 10−16 for a meta-analysis). These findings indicate that the 12q24.12-13 locus is associated with coffee consumption among a Japanese population.
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Affiliation(s)
- Hiroko Nakagawa-Senda
- Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan. .,Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan. .,Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
| | - Tsuyoshi Hachiya
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Morioka, Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Morioka, Japan
| | - Satoyo Hosono
- Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Isao Oze
- Division of Molecular and Clinical Epidemiology, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Miki Watanabe
- Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Keitaro Matsuo
- Division of Molecular and Clinical Epidemiology, Aichi Cancer Center Research Institute, Nagoya, Japan.,Department of Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Hidemi Ito
- Division of Molecular and Clinical Epidemiology, Aichi Cancer Center Research Institute, Nagoya, Japan.,Department of Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Megumi Hara
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan
| | - Yuichiro Nishida
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan
| | - Kaori Endoh
- Laboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan
| | - Kiyonori Kuriki
- Laboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan
| | - Sakurako Katsuura-Kamano
- Department of Preventive Medicine, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan
| | - Kokichi Arisawa
- Department of Preventive Medicine, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan
| | - Yora Nindita
- Department of International Island and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Rie Ibusuki
- Department of International Island and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Sadao Suzuki
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Akihiro Hosono
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Haruo Mikami
- Division of Cancer Prevention and Epidemiology, Chiba Cancer Center, Chiba, Japan
| | - Yohko Nakamura
- Division of Cancer Prevention and Epidemiology, Chiba Cancer Center, Chiba, Japan
| | - Naoyuki Takashima
- Department of Public Health, Shiga University of Medical Science, Shiga, Japan
| | - Yasuyuki Nakamura
- Department of Food Science and Human Nutrition, Faculty of Agriculture, Ryukoku University, Kyoto, Japan
| | - Nagato Kuriyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Etsuko Ozaki
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Norihiro Furusyo
- Department of Environmental Medicine and Infectious Disease, Kyushu University, Fukuoka, Japan
| | - Hiroaki Ikezaki
- Department of Environmental Medicine and Infectious Disease, Kyushu University, Fukuoka, Japan
| | - Masahiro Nakatochi
- Center for Advanced Medicine and Clinical Research, Nagoya University Hospital, Nagoya, Japan
| | - Tae Sasakabe
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Sayo Kawai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Rieko Okada
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Mariko Naito
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Kanagawa, Japan
| | - Michiaki Kubo
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Kanagawa, Japan
| | - Hideo Tanaka
- Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan
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118
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Johnson SC. Nutrient Sensing, Signaling and Ageing: The Role of IGF-1 and mTOR in Ageing and Age-Related Disease. Subcell Biochem 2018; 90:49-97. [PMID: 30779006 DOI: 10.1007/978-981-13-2835-0_3] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Nutrient signaling through insulin/IGF-1 was the first pathway demonstrated to regulate ageing and age-related disease in model organisms. Pharmacological or dietary interventions targeting nutrient signaling pathways have been shown to robustly attenuate ageing in many organisms. Caloric restriction, the most widely studied longevity promoting intervention, works through multiple nutrient signaling pathways, while inhibition of mTOR through treatment with rapamycin reproducibly delays ageing and disease through specific inhibition of the mTOR complexes. Although the benefits of reduced insulin/IGF-1 in lifespan and health are well documented in model organisms, defining the precise role of the IGF-1 in human ageing and age-related disease has proven more difficult. Association studies provide some insight but also reveal paradoxes. Low serum IGF-1 predicts longevity, but IGF-1 decreases with age and IGF-1 therapy benefits some of age-related pathologies. Circulating IGF-1 has been associated both positively and negatively with risk of age-related diseases in humans, and in some cases both activation and inhibition of IGF-1 signaling have provided benefit in animal models of the same diseases. Interventions designed modulate the nutrient sensing signaling pathways positively or negatively are already available for clinical use, highlighting the need for a clear understanding of the role of nutrient signaling in ageing and age-related disease. This chapter examines data from model organisms and human genetic association studies, with a special emphasis on IGF-1 and mTOR, and discusses potential models for resolving the paradoxes surrounding IGF-1 data.
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Affiliation(s)
- Simon C Johnson
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, WA, USA.
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119
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Effect of dietary energy and polymorphisms in BRAP and GHRL on obesity and metabolic traits. Obes Res Clin Pract 2018; 12:39-48. [DOI: 10.1016/j.orcp.2016.05.004] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2016] [Revised: 05/02/2016] [Accepted: 05/09/2016] [Indexed: 12/29/2022]
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120
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Stryjecki C, Alyass A, Meyre D. Ethnic and population differences in the genetic predisposition to human obesity. Obes Rev 2018; 19:62-80. [PMID: 29024387 DOI: 10.1111/obr.12604] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Revised: 06/17/2017] [Accepted: 08/02/2017] [Indexed: 12/22/2022]
Abstract
Obesity rates have escalated to the point of a global pandemic with varying prevalence across ethnic groups. These differences are partially explained by lifestyle factors in addition to genetic predisposition to obesity. This review provides a comprehensive examination of the ethnic differences in the genetic architecture of obesity. Using examples from evolution, heritability, admixture, monogenic and polygenic studies of obesity, we provide explanations for ethnic differences in the prevalence of obesity. The debate over definitions of race and ethnicity, the advantages and limitations of multi-ethnic studies and future directions of research are also discussed. Multi-ethnic studies have great potential to provide a better understanding of ethnic differences in the prevalence of obesity that may result in more targeted and personalized obesity treatments.
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Affiliation(s)
- C Stryjecki
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - A Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - D Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
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Turcot V, Lu Y, Highland HM, Schurmann C, Justice AE, Fine RS, Bradfield JP, Esko T, Giri A, Graff M, Guo X, Hendricks AE, Karaderi T, Lempradl A, Locke AE, Mahajan A, Marouli E, Sivapalaratnam S, Young KL, Alfred T, Feitosa MF, Masca NGD, Manning AK, Medina-Gomez C, Mudgal P, Ng MCY, Reiner AP, Vedantam S, Willems SM, Winkler TW, Abecasis G, Aben KK, Alam DS, Alharthi SE, Allison M, Amouyel P, Asselbergs FW, Auer PL, Balkau B, Bang LE, Barroso I, Bastarache L, Benn M, Bergmann S, Bielak LF, Blüher M, Boehnke M, Boeing H, Boerwinkle E, Böger CA, Bork-Jensen J, Bots ML, Bottinger EP, Bowden DW, Brandslund I, Breen G, Brilliant MH, Broer L, Brumat M, Burt AA, Butterworth AS, Campbell PT, Cappellani S, Carey DJ, Catamo E, Caulfield MJ, Chambers JC, Chasman DI, Chen YDI, Chowdhury R, Christensen C, Chu AY, Cocca M, Collins FS, Cook JP, Corley J, Corominas Galbany J, Cox AJ, Crosslin DS, Cuellar-Partida G, D'Eustacchio A, Danesh J, Davies G, Bakker PIW, Groot MCH, Mutsert R, Deary IJ, Dedoussis G, Demerath EW, Heijer M, Hollander AI, Ruijter HM, Dennis JG, Denny JC, Di Angelantonio E, Drenos F, Du M, Dubé MP, Dunning AM, Easton DF, Edwards TL, Ellinghaus D, Ellinor PT, Elliott P, Evangelou E, Farmaki AE, Farooqi IS, Faul JD, Fauser S, Feng S, Ferrannini E, Ferrieres J, Florez JC, Ford I, Fornage M, Franco OH, Franke A, Franks PW, Friedrich N, Frikke-Schmidt R, Galesloot TE, Gan W, Gandin I, Gasparini P, Gibson J, Giedraitis V, Gjesing AP, Gordon-Larsen P, Gorski M, Grabe HJ, Grant SFA, Grarup N, Griffiths HL, Grove ML, Gudnason V, Gustafsson S, Haessler J, Hakonarson H, Hammerschlag AR, Hansen T, Harris KM, Harris TB, Hattersley AT, Have CT, Hayward C, He L, Heard-Costa NL, Heath AC, Heid IM, Helgeland Ø, Hernesniemi J, Hewitt AW, Holmen OL, Hovingh GK, Howson JMM, Hu Y, Huang PL, Huffman JE, Ikram MA, Ingelsson E, Jackson AU, Jansson JH, Jarvik GP, Jensen GB, Jia Y, Johansson S, Jørgensen ME, Jørgensen T, Jukema JW, Kahali B, Kahn RS, Kähönen M, Kamstrup PR, Kanoni S, Kaprio J, Karaleftheri M, Kardia SLR, Karpe F, Kathiresan S, Kee F, Kiemeney LA, Kim E, Kitajima H, Komulainen P, Kooner JS, Kooperberg C, Korhonen T, Kovacs P, Kuivaniemi H, Kutalik Z, Kuulasmaa K, Kuusisto J, Laakso M, Lakka TA, Lamparter D, Lange EM, Lange LA, Langenberg C, Larson EB, Lee NR, Lehtimäki T, Lewis CE, Li H, Li J, Li-Gao R, Lin H, Lin KH, Lin LA, Lin X, Lind L, Lindström J, Linneberg A, Liu CT, Liu DJ, Liu Y, Lo KS, Lophatananon A, Lotery AJ, Loukola A, Luan J, Lubitz SA, Lyytikäinen LP, Männistö S, Marenne G, Mazul AL, McCarthy MI, McKean-Cowdin R, Medland SE, Meidtner K, Milani L, Mistry V, Mitchell P, Mohlke KL, Moilanen L, Moitry M, Montgomery GW, Mook-Kanamori DO, Moore C, Mori TA, Morris AD, Morris AP, Müller-Nurasyid M, Munroe PB, Nalls MA, Narisu N, Nelson CP, Neville M, Nielsen SF, Nikus K, Njølstad PR, Nordestgaard BG, Nyholt DR, O'Connel JR, O'Donoghue ML, Olde Loohuis LM, Ophoff RA, Owen KR, Packard CJ, Padmanabhan S, Palmer CNA, Palmer ND, Pasterkamp G, Patel AP, Pattie A, Pedersen O, Peissig PL, Peloso GM, Pennell CE, Perola M, Perry JA, Perry JRB, Pers TH, Person TN, Peters A, Petersen ERB, Peyser PA, Pirie A, Polasek O, Polderman TJ, Puolijoki H, Raitakari OT, Rasheed A, Rauramaa R, Reilly DF, Renström F, Rheinberger M, Ridker PM, Rioux JD, Rivas MA, Roberts DJ, Robertson NR, Robino A, Rolandsson O, Rudan I, Ruth KS, Saleheen D, Salomaa V, Samani NJ, Sapkota Y, Sattar N, Schoen RE, Schreiner PJ, Schulze MB, Scott RA, Segura-Lepe MP, Shah SH, Sheu WHH, Sim X, Slater AJ, Small KS, Smith AV, Southam L, Spector TD, Speliotes EK, Starr JM, Stefansson K, Steinthorsdottir V, Stirrups KE, Strauch K, Stringham HM, Stumvoll M, Sun L, Surendran P, Swift AJ, Tada H, Tansey KE, Tardif JC, Taylor KD, Teumer A, Thompson DJ, Thorleifsson G, Thorsteinsdottir U, Thuesen BH, Tönjes A, Tromp G, Trompet S, Tsafantakis E, Tuomilehto J, Tybjaerg-Hansen A, Tyrer JP, Uher R, Uitterlinden AG, Uusitupa M, Laan SW, Duijn CM, Leeuwen N, van Setten J, Vanhala M, Varbo A, Varga TV, Varma R, Velez Edwards DR, Vermeulen SH, Veronesi G, Vestergaard H, Vitart V, Vogt TF, Völker U, Vuckovic D, Wagenknecht LE, Walker M, Wallentin L, Wang F, Wang CA, Wang S, Wang Y, Ware EB, Wareham NJ, Warren HR, Waterworth DM, Wessel J, White HD, Willer CJ, Wilson JG, Witte DR, Wood AR, Wu Y, Yaghootkar H, Yao J, Yao P, Yerges-Armstrong LM, Young R, Zeggini E, Zhan X, Zhang W, Zhao JH, Zhao W, Zhao W, Zhou W, Zondervan KT, Rotter JI, Pospisilik JA, Rivadeneira F, Borecki IB, Deloukas P, Frayling TM, Lettre G, North KE, Lindgren CM, Hirschhorn JN, Loos RJF. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet 2018; 50:26-41. [PMID: 29273807 PMCID: PMC5945951 DOI: 10.1038/s41588-017-0011-x] [Citation(s) in RCA: 235] [Impact Index Per Article: 39.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Accepted: 11/15/2017] [Indexed: 02/02/2023]
Abstract
Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
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Affiliation(s)
- Valérie Turcot
- Montreal Heart Institute, Université de Montréal, Montreal, Quebec, Canada
| | - Yingchang Lu
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
- Human Genetics Center, University of Texas School of Public Health, University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Claudia Schurmann
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Anne E Justice
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Rebecca S Fine
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
| | - Jonathan P Bradfield
- Center for Applied Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Quantinuum Research, LLC, San Diego, CA, USA
| | - Tõnu Esko
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Ayush Giri
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Audrey E Hendricks
- Wellcome Trust Sanger Institute, Hinxton, UK
- Department of Mathematical and Statistical Sciences, University of Colorado, Denver, CO, USA
| | - Tugce Karaderi
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Biological Sciences, Faculty of Arts and Sciences, Eastern Mediterranean University, Famagusta, Cyprus
| | - Adelheid Lempradl
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Adam E Locke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Suthesh Sivapalaratnam
- Department of Vascular Medicine, AMC, Amsterdam, The Netherlands
- Massachusetts General Hospital, Boston, MA, USA
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Kristin L Young
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Tamuno Alfred
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Nicholas G D Masca
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, UK
- NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, UK
| | - Alisa K Manning
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Medical and Population Genetics Program, Broad Institute, Cambridge, MA, USA
| | - Carolina Medina-Gomez
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Poorva Mudgal
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Maggie C Y Ng
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Sailaja Vedantam
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA
| | - Sara M Willems
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Gonçalo Abecasis
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Katja K Aben
- Netherlands Comprehensive Cancer Organisation, Utrecht, The Netherlands
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Dewan S Alam
- School of Kinesiology and Health Science, Faculty of Health, York University, Toronto, Ontario, Canada
| | - Sameer E Alharthi
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | - Matthew Allison
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Philippe Amouyel
- INSERM U1167, Lille, France
- Institut Pasteur de Lille, U1167, Lille, France
- Université de Lille, U1167, RID-AGE, Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
- Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, The Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
| | - Paul L Auer
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Beverley Balkau
- INSERM U1018, Centre de Recherche en Épidémiologie et Santé des Populations (CESP), Villejuif, France
| | - Lia E Bang
- Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Inês Barroso
- Wellcome Trust Sanger Institute, Hinxton, UK
- Metabolic Research Laboratories, University of Cambridge, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA
| | - Marianne Benn
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Matthias Blüher
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke (DIfE), Nuthetal, Germany
| | - Eric Boerwinkle
- School of Public Health, Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Carsten A Böger
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Michiel L Bots
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Erwin P Bottinger
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Donald W Bowden
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Ivan Brandslund
- Department of Clinical Biochemistry, Lillebaelt Hospital, Vejle, Denmark
- Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
| | - Gerome Breen
- MRC Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- NIHR Biomedical Research Centre for Mental Health, South London and Maudsley Hospital, London, UK
| | | | - Linda Broer
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Marco Brumat
- Department of Medical Sciences, University of Trieste, Trieste, Italy
| | - Amber A Burt
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Adam S Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Peter T Campbell
- Epidemiology Research Program, American Cancer Society, Atlanta, GA, USA
| | - Stefania Cappellani
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - David J Carey
- Weis Center for Research, Geisinger Health System, Danville, PA, USA
| | - Eulalia Catamo
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Mark J Caulfield
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - John C Chambers
- Department of Cardiology, London North West Healthcare NHS Trust, Ealing Hospital, Middlesex, UK
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, London, UK
| | - Daniel I Chasman
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Rajiv Chowdhury
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Audrey Y Chu
- NHLBI Framingham Heart Study, Framingham, MA, USA
- Genetics and Pharmacogenomics, Merck, Sharp & Dohme, Boston, MA, USA
| | - Massimiliano Cocca
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy
| | - Francis S Collins
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, USA
| | - James P Cook
- Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Janie Corley
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Jordi Corominas Galbany
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Amanda J Cox
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Menzies Health Institute Queensland, Griffith University, Southport, Queensland, Australia
| | - David S Crosslin
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
| | - Gabriel Cuellar-Partida
- Diamantina Institute, University of Queensland, Brisbane, Queensland, Australia
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Angela D'Eustacchio
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - John Danesh
- Wellcome Trust Sanger Institute, Hinxton, UK
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cambridge Centre of Excellence, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Gail Davies
- Department of Biostatistics, University of Liverpool, Liverpool, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Paul I W Bakker
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mark C H Groot
- Department of Clinical Chemistry and Haematology, Division of Laboratory and Pharmacy, University Medical Center Utrecht, Utrecht, The Netherlands
- Utrecht Institute for Pharmaceutical Sciences, Division Pharmacoepidemiology and Clinical Pharmacology, Utrecht University, Utrecht, The Netherlands
| | - Renée Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ian J Deary
- Department of Biostatistics, University of Liverpool, Liverpool, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Ellen W Demerath
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Martin Heijer
- Department of Internal Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Anneke I Hollander
- Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Hester M Ruijter
- Laboratory of Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Joe G Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Josh C Denny
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA
| | - Emanuele Di Angelantonio
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Fotios Drenos
- Institute of Cardiovascular Science, University College London, London, UK
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Mengmeng Du
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Marie-Pierre Dubé
- Montreal Heart Institute, Université de Montréal, Montreal, Quebec, Canada
- Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany
| | - Patrick T Ellinor
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
- Medical and Population Genetics Program, Broad Institute, Cambridge, MA, USA
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Aliki-Eleni Farmaki
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - I Sadaf Farooqi
- Metabolic Research Laboratories, University of Cambridge, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Sascha Fauser
- Department of Ophthalmology, University of Cologne, Cologne, Germany
| | - Shuang Feng
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Ele Ferrannini
- CNR Institute of Clinical Physiology, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Jean Ferrieres
- Toulouse University School of Medicine, Toulouse, France
| | - Jose C Florez
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Medical and Population Genetics Program, Broad Institute, Cambridge, MA, USA
| | - Ian Ford
- University of Glasgow, Glasgow, UK
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Oscar H Franco
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany
| | - Paul W Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmo, Sweden
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA
- Department of Public Health and Clinical Medicine, Unit of Medicine, Umeå University, Umeå, Sweden
| | - Nele Friedrich
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Ruth Frikke-Schmidt
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Tessel E Galesloot
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Wei Gan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Paolo Gasparini
- Department of Medical Sciences, University of Trieste, Trieste, Italy
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Jane Gibson
- Centre for Biological Sciences, Faculty of Natural and Environmental Sciences, University of Southampton, Southampton, UK
| | | | - Anette P Gjesing
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Penny Gordon-Larsen
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Mathias Gorski
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Hans-Jörgen Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Greifswald, Germany
| | - Struan F A Grant
- Center for Applied Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Endocrinology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Helen L Griffiths
- Vision Sciences, Clinical Neurosciences Research Group, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Megan L Grove
- School of Public Health, Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Vilmundur Gudnason
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | - Stefan Gustafsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Jeff Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Anke R Hammerschlag
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, The Netherlands
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kathleen Mullan Harris
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Sociology, University of North Carolina, Chapel Hill, NC, USA
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, US National Institutes of Health, Bethesda, MD, USA
| | | | - Christian T Have
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Liang He
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Nancy L Heard-Costa
- NHLBI Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Andrew C Heath
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Øyvind Helgeland
- Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Jussi Hernesniemi
- Department of Cardiology, Heart Center, Tampere University Hospital and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Alex W Hewitt
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Victoria, Australia
- Centre for Ophthalmology and Vision Science, Lions Eye Institute, University of Western Australia, Perth, Western Australia, Australia
- Menzies Research Institute Tasmania, University of Tasmania, Hobart, Tasmania, Australia
| | - Oddgeir L Holmen
- KG Jebsen Center for Genetic Epidemiology, Department of Public Health, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - G Kees Hovingh
- Department of Vascular Medicine, AMC, Amsterdam, The Netherlands
| | - Joanna M M Howson
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Yao Hu
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, China
| | | | - Jennifer E Huffman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Erik Ingelsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jan-Håkan Jansson
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
- Research Unit Skellefteå, Skellefteå, Sweden
| | - Gail P Jarvik
- Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Gorm B Jensen
- Copenhagen City Heart Study, Frederiksberg Hospital, Frederiksberg, Denmark
| | - Yucheng Jia
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Stefan Johansson
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Marit E Jørgensen
- National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Torben Jørgensen
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Medicine, Aalborg University, Aalborg, Denmark
- Research Center for Prevention and Health, Capital Region of Denmark, Glostrup, Denmark
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Interuniversity Cardiology Institute of the Netherlands, Utrecht, The Netherlands
| | - Bratati Kahali
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
- Centre for Brain Research, Indian Institute of Science, Bangalore, India
| | - René S Kahn
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mika Kähönen
- Department of Clinical Physiology, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - Pia R Kamstrup
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | | | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | - Sekar Kathiresan
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Frank Kee
- UKCRC Centre of Excellence for Public Health Research, Queens University Belfast, Belfast, UK
| | - Lambertus A Kiemeney
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Eric Kim
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Hidetoshi Kitajima
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Pirjo Komulainen
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Jaspal S Kooner
- Department of Cardiology, London North West Healthcare NHS Trust, Ealing Hospital, Middlesex, UK
- Imperial College Healthcare NHS Trust, London, UK
- National Heart and Lung Institute, Imperial College London, Hammersmith Hospital Campus, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Tellervo Korhonen
- Department of Public Health, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Peter Kovacs
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | - Helena Kuivaniemi
- Weis Center for Research, Geisinger Health System, Danville, PA, USA
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Kari Kuulasmaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Timo A Lakka
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - David Lamparter
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ethan M Lange
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Leslie A Lange
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Eric B Larson
- Department of Medicine, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
| | - Nanette R Lee
- Department of Anthropology, Sociology and History, University of San Carlos, Cebu City, Philippines
- USC-Office of Population Studies Foundation, Inc., University of San Carlos, Cebu City, Philippines
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Cora E Lewis
- Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Huaixing Li
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, China
| | - Jin Li
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Honghuang Lin
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Keng-Hung Lin
- Department of Ophthalmology, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Li-An Lin
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xu Lin
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, China
| | - Lars Lind
- Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden
| | - Jaana Lindström
- National Institute for Health and Welfare, Helsinki, Finland
| | - Allan Linneberg
- Research Center for Prevention and Health, Capital Region of Denmark, Glostrup, Denmark
- Department of Clinical Experimental Research, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Dajiang J Liu
- Department of Public Health Sciences, Institute for Personalized Medicine, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Yongmei Liu
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Ken S Lo
- Montreal Heart Institute, Université de Montréal, Montreal, Quebec, Canada
| | - Artitaya Lophatananon
- Division of Health Sciences, Warwick Medical School, Warwick University, Coventry, UK
| | - Andrew J Lotery
- Vision Sciences, Clinical Neurosciences Research Group, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Anu Loukola
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Steven A Lubitz
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
- Medical and Population Genetics Program, Broad Institute, Cambridge, MA, USA
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Satu Männistö
- National Institute for Health and Welfare, Helsinki, Finland
| | | | - Angela L Mazul
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Mark I McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | - Roberta McKean-Cowdin
- Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Karina Meidtner
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke (DIfE), Nuthetal, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Vanisha Mistry
- Metabolic Research Laboratories, University of Cambridge, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Paul Mitchell
- Westmead Millennium Institute of Medical Research, Centre for Vision Research and Department of Ophthalmology, University of Sydney, Sydney, New South Wales, Australia
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Leena Moilanen
- Department of Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Marie Moitry
- Department of Epidemiology and Public Health, University of Strasbourg, Strasbourg, France
- Department of Public Health, University Hospital of Strasbourg, Strasbourg, France
| | - Grant W Montgomery
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Carmel Moore
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- INTERVAL Coordinating Centre, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Trevor A Mori
- School of Medicine and Pharmacology, University of Western Australia, Perth, Western Australia, Australia
| | - Andrew D Morris
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Andrew P Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Department of Medicine I, University Hospital Großhadern, Ludwig-Maximilians-Universitat, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Patricia B Munroe
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, US National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
| | - Narisu Narisu
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, UK
- NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, UK
| | - Matt Neville
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | - Sune F Nielsen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kjell Nikus
- Department of Cardiology, Heart Center, Tampere University Hospital and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Pål R Njølstad
- Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Dale R Nyholt
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Jeffrey R O'Connel
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Michelle L O'Donoghue
- Division of Cardiovascular Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Loes M Olde Loohuis
- Center for Neurobehavioral Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Roel A Ophoff
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
- Center for Neurobehavioral Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Katharine R Owen
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | | | | | - Colin N A Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Medical Research Institute, Ninewells Hospital and Medical School, Dundee, UK
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Gerard Pasterkamp
- Laboratory of Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
- Laboratory of Clinical Chemistry and Hematology, Division of Laboratories and Pharmacy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Aniruddh P Patel
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Alison Pattie
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Gina M Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Craig E Pennell
- School of Women's and Infants' Health, University of Western Australia, Perth, Western Australia, Australia
| | - Markus Perola
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
- Diabetes and Obesity Research Program, University of Helsinki, Helsinki, Finland
| | - James A Perry
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - John R B Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Tune H Pers
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | | | - Annette Peters
- German Center for Diabetes Research, Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Eva R B Petersen
- Department of Clinical Immunology and Biochemistry, Lillebaelt Hospital, Vejle, Denmark
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Ailith Pirie
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Ozren Polasek
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- School of Medicine, University of Split, Split, Croatia
| | - Tinca J Polderman
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, The Netherlands
| | - Hannu Puolijoki
- Central Hospital of Southern Ostrobothnia, Seinäjoki, Finland
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Asif Rasheed
- Centre for Non-Communicable Diseases, Karachi, Pakistan
| | - Rainer Rauramaa
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
| | - Dermot F Reilly
- Genetics and Pharmacogenomics, Merck, Sharp & Dohme, Boston, MA, USA
| | - Frida Renström
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmo, Sweden
- Department of Biobank Research, Umeå University, Umeå, Sweden
| | - Myriam Rheinberger
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - John D Rioux
- Montreal Heart Institute, Université de Montréal, Montreal, Quebec, Canada
- Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
| | - Manuel A Rivas
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Wellcome Trust Centre for Human Genetics, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - David J Roberts
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NHS Blood and Transplant-Oxford Centre, Oxford, UK
- BRC Haematology Theme and Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Neil R Robertson
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Antonietta Robino
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Olov Rolandsson
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
- Department of Public Health and Clinical Medicine, Unit of Family Medicine, Umeå University, Umeå, Sweden
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Katherine S Ruth
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Danish Saleheen
- Centre for Non-Communicable Diseases, Karachi, Pakistan
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, UK
- NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, UK
| | - Yadav Sapkota
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - Robert E Schoen
- Departments of Medicine and Epidemiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke (DIfE), Nuthetal, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Robert A Scott
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Marcelo P Segura-Lepe
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Svati H Shah
- Duke Molecular Physiology Institute, Duke University, Durham, NC, USA
| | - Wayne H-H Sheu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Xueling Sim
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore
| | - Andrew J Slater
- Genetics, Target Sciences, GlaxoSmithKline, Research Triangle Park, NC, USA
- OmicSoft at Qiagen Company, Cary, NC, USA
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Albert V Smith
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | - Lorraine Southam
- Wellcome Trust Sanger Institute, Hinxton, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Timothy D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Elizabeth K Speliotes
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Kari Stefansson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | | | - Kathleen E Stirrups
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Michael Stumvoll
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Liang Sun
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Praveen Surendran
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Amy J Swift
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, US National Institutes of Health, Bethesda, MD, USA
| | - Hayato Tada
- Division of Cardiovascular Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Kanazawa University, Kanazawa, Japan
| | - Katherine E Tansey
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
- College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
| | - Jean-Claude Tardif
- Montreal Heart Institute, Université de Montréal, Montreal, Quebec, Canada
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Unnur Thorsteinsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | - Betina H Thuesen
- Research Center for Prevention and Health, Capital Region of Denmark, Glostrup, Denmark
| | - Anke Tönjes
- Center for Pediatric Research, Department for Women's and Child Health, University of Leipzig, Leipzig, Germany
| | - Gerard Tromp
- Weis Center for Research, Geisinger Health System, Danville, PA, USA
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Jaakko Tuomilehto
- National Institute for Health and Welfare, Helsinki, Finland
- Centre for Vascular Prevention, Danube University Krems, Krems, Austria
- Dasman Diabetes Institute, Dasman, Kuwait
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Anne Tybjaerg-Hansen
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Jonathan P Tyrer
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Matti Uusitupa
- Department of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Sander W Laan
- Laboratory of Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cornelia M Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Nienke Leeuwen
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
- Department of Molecular Cell Biology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jessica van Setten
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mauno Vanhala
- Primary Health Care Unit, Central Hospital of Central Finland, Jyväskylä, Finland
- Primary Health Care Unit, Kuopio University Hospital, Kuopio, Finland
| | - Anette Varbo
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tibor V Varga
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmo, Sweden
| | - Rohit Varma
- USC Roski Eye Institute, Department of Ophthalmology, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
| | - Digna R Velez Edwards
- Department of Obstetrics and Gynecology, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Sita H Vermeulen
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Giovanni Veronesi
- Research Center on Epidemiology and Preventive Medicine, Department of Medicine and Surgery, University of Insubria, Varese, Italy
| | - Henrik Vestergaard
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Thomas F Vogt
- Cardiometabolic Disease, Merck, Sharp & Dohme, Kenilworth, NJ, USA
| | - Uwe Völker
- German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Dragana Vuckovic
- Department of Medical Sciences, University of Trieste, Trieste, Italy
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Mark Walker
- Institute of Cellular Medicine, Medical School, Newcastle University, Newcastle, UK
| | - Lars Wallentin
- Department of Medical Sciences, Cardiology, Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden
| | - Feijie Wang
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, China
| | - Carol A Wang
- School of Women's and Infants' Health, University of Western Australia, Perth, Western Australia, Australia
| | - Shuai Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Yiqin Wang
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, China
| | - Erin B Ware
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Helen R Warren
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Dawn M Waterworth
- Genetics, Target Sciences, GlaxoSmithKline, King of Prussia, PA, USA
| | - Jennifer Wessel
- Departments of Epidemiology and Medicine, Diabetes Translational Research Center, Fairbanks School of Public Health and School of Medicine, Indiana University, Indianapolis, IN, USA
| | - Harvey D White
- Green Lane Cardiovascular Service, Auckland City Hospital and University of Auckland, Auckland, New Zealand
| | - Cristen J Willer
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Daniel R Witte
- Danish Diabetes Academy, Odense, Denmark
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Andrew R Wood
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Hanieh Yaghootkar
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Pang Yao
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, China
| | - Laura M Yerges-Armstrong
- Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- GlaxoSmithKline, King of Prussia, PA, USA
| | - Robin Young
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- University of Glasgow, Glasgow, UK
| | | | - Xiaowei Zhan
- Department of Clinical Sciences, Quantitative Biomedical Research Center, Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Weihua Zhang
- Department of Cardiology, London North West Healthcare NHS Trust, Ealing Hospital, Middlesex, UK
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Jing Hua Zhao
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Wei Zhao
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Krina T Zondervan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Endometriosis CaRe Centre, Nuffield Department of Obstetrics and Gynaecology, University of Oxford, Oxford, UK
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - John A Pospisilik
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ingrid B Borecki
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Guillaume Lettre
- Montreal Heart Institute, Université de Montréal, Montreal, Quebec, Canada
- Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada
| | - Kari E North
- Department of Epidemiology and Carolina Center of Genome Sciences, Chapel Hill, NC, USA
| | - Cecilia M Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Li Ka Shing Centre for Health Information and Discovery, Big Data Institute, University of Oxford, Oxford, UK
| | - Joel N Hirschhorn
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Genetics, Harvard Medical School, Boston, MA, USA.
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, USA.
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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Méndez-Giráldez R, Gogarten SM, Below JE, Yao J, Seyerle AA, Highland HM, Kooperberg C, Soliman EZ, Rotter JI, Kerr KF, Ryckman KK, Taylor KD, Petty LE, Shah SJ, Conomos MP, Sotoodehnia N, Cheng S, Heckbert SR, Sofer T, Guo X, Whitsel EA, Lin HJ, Hanis CL, Laurie CC, Avery CL. GWAS of the electrocardiographic QT interval in Hispanics/Latinos generalizes previously identified loci and identifies population-specific signals. Sci Rep 2017; 7:17075. [PMID: 29213071 PMCID: PMC5719082 DOI: 10.1038/s41598-017-17136-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Accepted: 11/21/2017] [Indexed: 01/08/2023] Open
Abstract
QT interval prolongation is a heritable risk factor for ventricular arrhythmias and can predispose to sudden death. Most genome-wide association studies (GWAS) of QT were performed in European ancestral populations, leaving other groups uncharacterized. Herein we present the first QT GWAS of Hispanic/Latinos using data on 15,997 participants from four studies. Study-specific summary results of the association between 1000 Genomes Project (1000G) imputed SNPs and electrocardiographically measured QT were combined using fixed-effects meta-analysis. We identified 41 genome-wide significant SNPs that mapped to 13 previously identified QT loci. Conditional analyses distinguished six secondary signals at NOS1AP (n = 2), ATP1B1 (n = 2), SCN5A (n = 1), and KCNQ1 (n = 1). Comparison of linkage disequilibrium patterns between the 13 lead SNPs and six secondary signals with previously reported index SNPs in 1000G super populations suggested that the SCN5A and KCNE1 lead SNPs were potentially novel and population-specific. Finally, of the 42 suggestively associated loci, AJAP1 was suggestively associated with QT in a prior East Asian GWAS; in contrast BVES and CAP2 murine knockouts caused cardiac conduction defects. Our results indicate that whereas the same loci influence QT across populations, population-specific variation exists, motivating future trans-ethnic and ancestrally diverse QT GWAS.
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Affiliation(s)
| | | | - Jennifer E Below
- The Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Amanda A Seyerle
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA.,Division of Epidemiology and Community, University of Minnesota, Minneapolis, MN, USA
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Elsayed Z Soliman
- Department of Internal Medicine, Section on Cardiology, Wake Forest School of Medicine, Winston-Salem, NC, USA.,Epidemiological Cardio Research Center (EPICARE), Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kathleen F Kerr
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Kelli K Ryckman
- Departments of Epidemiology and Pediatrics, University of Iowa, Iowa City, IA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Lauren E Petty
- Human Genetics Center, University of Texas, Health Science Center at Houston, Houston, TX, USA.,Center for Precision Medicine, University of Texas, Health Science Center at Houston, Houston, TX, USA
| | - Sanjiv J Shah
- Division of Cardiology, Bluhm Cardiovascular Institute, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Division of Cardiology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Susan Cheng
- Brigham and Women's Hospital, Division of Cardiovascular Medicine, Boston, MA, USA
| | - Susan R Heckbert
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA.,Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Eric A Whitsel
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA.,Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Henry J Lin
- The Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA.,Division of Medical Genetics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Craig L Hanis
- Human Genetics Center, University of Texas, Health Science Center at Houston, Houston, TX, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Christy L Avery
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA. .,Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA.
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Dorajoo R, Ong RTH, Sim X, Wang L, Liu W, Tai ES, Liu J, Saw SM. The contribution of recently identified adult BMI risk loci to paediatric obesity in a Singaporean Chinese childhood dataset. Pediatr Obes 2017; 12:e46-e50. [PMID: 27780307 DOI: 10.1111/ijpo.12175] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Revised: 07/01/2016] [Accepted: 07/18/2016] [Indexed: 11/28/2022]
Abstract
INTRODUCTION Recent genome-wide association studies have identified 103 adult obesity risk loci; however, it is unclear if these findings are relevant to East-Asian childhood body mass index (BMI) levels. METHODS AND RESULTS We evaluated for paediatric obesity associations at these risk loci utilizing genome-wide data from Chinese childhood subjects in the Singapore Cohort study Of the Risk factors for Myopia study (N = 1006). A weighted gene-risk score of all adult obesity risk loci in the Singapore Cohort study Of the Risk factors for Myopia study showed strong associations with BMI at age 9 (p-value = 3.40 × 10-12 ) and 4-year average BMI (age 9 to 12, p-value = 6.67 × 10-8 ). Directionally consistent nominal associations for 15 index single nucleotide polymorphisms (SNPs) (p-value < 0.05) were observed. Pathway analysis with genes from these 15 replicating loci revealed over-representation for the G-protein-coupled receptor (GPCR)-mediated integration of entero-endocrine signalling pathway exemplified by L-cell (adjusted p-value = 0.018). Evaluations of birth weight to modify the effects of BMI risk SNPs in paediatric obesity did not reveal significant interactions, and these SNPs were generally not associated with birth weight. CONCLUSIONS At least some common adult BMI risk variants predispose to paediatric obesity risk in East-Asians.
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Affiliation(s)
- R Dorajoo
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
| | - R T-H Ong
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - X Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - L Wang
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
| | - W Liu
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
| | - E S Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.,Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore.,Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - J Liu
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.,Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - S-M Saw
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.,Duke-National University of Singapore Graduate Medical School, Singapore, Singapore.,Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
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Mao L, Fang Y, Campbell M, Southerland WM. Population differentiation in allele frequencies of obesity-associated SNPs. BMC Genomics 2017; 18:861. [PMID: 29126384 PMCID: PMC5681842 DOI: 10.1186/s12864-017-4262-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Accepted: 11/02/2017] [Indexed: 08/11/2023] Open
Abstract
BACKGROUND Obesity is emerging as a global health problem, with more than one-third of the world's adult population being overweight or obese. In this study, we investigated worldwide population differentiation in allele frequencies of obesity-associated SNPs (single nucleotide polymorphisms). RESULTS We collected a total of 225 obesity-associated SNPs from a public database. Their population-level allele frequencies were derived based on the genotype data from 1000 Genomes Project (phase 3). We used hypergeometric model to assess whether the effect allele at a given SNP is significantly enriched or depleted in each of the 26 populations surveyed in the 1000 Genomes Project with respect to the overall pooled population. Our results indicate that 195 out of 225 SNPs (86.7%) possess effect alleles significantly enriched or depleted in at least one of the 26 populations. Populations within the same continental group exhibit similar allele enrichment/depletion patterns whereas inter-continental populations show distinct patterns. Among the 225 SNPs, 15 SNPs cluster in the first intron region of the FTO gene, which is a major gene associated with body-mass index (BMI) and fat mass. African populations exhibit much smaller blocks of LD (linkage disequilibrium) among these15 SNPs while European and Asian populations have larger blocks. To estimate the cumulative effect of all variants associated with obesity, we developed the personal composite genetic risk score for obesity. Our results indicate that the East Asian populations have the lowest averages of the composite risk scores, whereas three European populations have the highest averages. In addition, the population-level average of composite genetic risk scores is significantly correlated (R2 = 0.35, P = 0.0060) with obesity prevalence. CONCLUSIONS We have detected substantial population differentiation in allele frequencies of obesity-associated SNPs. The results will help elucidate the genetic basis which may contribute to population disparities in obesity prevalence.
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Affiliation(s)
- Linyong Mao
- Department of Biochemistry and Molecular Biology, Howard University College of Medicine, 520 W Street NW, Washington, DC 20059 USA
| | - Yayin Fang
- Department of Biochemistry and Molecular Biology, Howard University College of Medicine, 520 W Street NW, Washington, DC 20059 USA
| | - Michael Campbell
- Department of Biology, Howard University, 415 College Street NW, Washington, 20059 DC USA
| | - William M. Southerland
- Department of Biochemistry and Molecular Biology, Howard University College of Medicine, 520 W Street NW, Washington, DC 20059 USA
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Cheng Z, Zheng L, Almeida FA. Epigenetic reprogramming in metabolic disorders: nutritional factors and beyond. J Nutr Biochem 2017; 54:1-10. [PMID: 29154162 DOI: 10.1016/j.jnutbio.2017.10.004] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Revised: 09/26/2017] [Accepted: 10/10/2017] [Indexed: 12/13/2022]
Abstract
Environmental factors (e.g., malnutrition and physical inactivity) contribute largely to metabolic disorders including obesity, type 2 diabetes, cardiometabolic disease and nonalcoholic fatty liver diseases. The abnormalities in metabolic activity and pathways have been increasingly associated with altered DNA methylation, histone modification and noncoding RNAs, whereas lifestyle interventions targeting diet and physical activity can reverse the epigenetic and metabolic changes. Here we review recent evidence primarily from human studies that links DNA methylation reprogramming to metabolic derangements or improvements, with a focus on cross-tissue (e.g., the liver, skeletal muscle, pancreas, adipose tissue and blood samples) epigenetic markers, mechanistic mediators of the epigenetic reprogramming, and the potential of using epigenetic traits to predict disease risk and intervention response. The challenges in epigenetic studies addressing the mechanisms of metabolic diseases and future directions are also discussed and prospected.
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Affiliation(s)
- Zhiyong Cheng
- Department of Human Nutrition, Foods, and Exercise, Fralin Translational Obesity Research Center, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA 24061, USA.
| | - Louise Zheng
- Department of Human Nutrition, Foods, and Exercise, Fralin Translational Obesity Research Center, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA 24061, USA
| | - Fabio A Almeida
- Department of Health Promotion, Social & Behavioral Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA.
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Abstract
Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.
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127
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Genome-wide association study identifies 112 new loci for body mass index in the Japanese population. Nat Genet 2017; 49:1458-1467. [DOI: 10.1038/ng.3951] [Citation(s) in RCA: 267] [Impact Index Per Article: 38.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Accepted: 08/14/2017] [Indexed: 12/15/2022]
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128
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The role of established East Asian obesity-related loci on pediatric leptin levels highlights a neuronal influence on body weight regulation in Chinese children and adolescents: the BCAMS study. Oncotarget 2017; 8:93593-93607. [PMID: 29212175 PMCID: PMC5706821 DOI: 10.18632/oncotarget.20547] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2017] [Accepted: 08/08/2017] [Indexed: 12/16/2022] Open
Abstract
Genome-wide association studies have identified multiple variants associated with adult obesity, mostly in European-ancestry populations. We aimed to systematically assess the contribution of key loci, which had been previously shown to be associated in East Asian adults, to childhood obesity, related adipokine profiles and metabolic traits in a Chinese pediatric population. Twelve single-nucleotide polymorphisms (SNPs) plus metabolic profiles and levels of five adipokines (leptin, adiponectin, resistin, fibroblast growth factor 21 and retinol binding protein 4) were evaluated in 3,506 Chinese children and adolescents aged 6-18. After correction for multiple comparisons, six of these SNPs were robustly associated with childhood obesity: FTO-rs1558902 (P=5.6×10−5), MC4R-rs2331841 (P=4.4×10−4), GNPDA2-rs16858082 (P = 3.4×10−4), PCSK1-rs261967 (P = 0.001), SEC16B-rs516636 (P = 0.004) and MAP2K5-rs4776970 (P = 0.004), with odds ratios ranging from 1.211 to 1.421; while ITIH4-rs2535633 and BDNF-rs2030323 yielded nominal association with the same trait (P < 0.05). Moreover, the risk alleles of six SNPs displayed significant (P < 0.004) or nominal (P < 0.05) association with leptin levels, namely at in/near PCSK1, MC4R, FTO, MAP2K5, GNPDA2 and BDNF plus their cumulative genetic score yielded stronger association with increased leptin levels (P = 6.2×10−11). Our results reveal that key obesity-associated loci previously reported in Europeans, but also associated with East Asian adults, are also associated with obesity and/or metabolic quantitative traits in Chinese children. These associations coincide with six brain-expressed loci that correlate with leptin levels, thus may point to an important neuronal influence on body weight regulation in the pediatric setting.
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Wang S, Song J, Yang Y, Zhang Y, Chawla NV, Ma J, Wang H. Interaction between obesity and the Hypoxia Inducible Factor 3 Alpha Subunit rs3826795 polymorphism in relation with plasma alanine aminotransferase. BMC MEDICAL GENETICS 2017; 18:80. [PMID: 28754107 PMCID: PMC5534125 DOI: 10.1186/s12881-017-0437-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Accepted: 07/13/2017] [Indexed: 12/14/2022]
Abstract
BACKGROUND Hypoxia Inducible Factor 3 Alpha Subunit (HIF3A) DNA has been demonstrated to be associated with obesity in the methylation level, and it also has a Body Mass Index (BMI)-independent association with plasma alanine aminotransferase (ALT). However, the relation among obesity, plasma ALT, HIF3A polymorphism and methylation remains unclear. This study aims to identify the association between HIF3A polymorphism and plasma ALT, and further to determine whether the effect of HIF3A polymorphism on ALT could be modified by obesity or mediated by DNA methylation. METHODS The HIF3A rs3826795 polymorphism was genotyped in a case-control study including 2030 Chinese children aged 7-18 years (705 obese cases and 1325 non-obese controls). Furthermore, the HIF3A DNA methylation of the peripheral blood was measured in 110 severely obese children and 110 age- and gender- matched normal-weight controls. RESULTS There was no overall association between the HIF3A rs3826795 polymorphism and ALT. A significant interaction between obesity and rs3826795 in relation with ALT was found (P inter = 0.042), with rs3826795 G-allele number elevating ALT significantly only in obese children (β' = 0.075, P = 0.037), but not in non-obese children (β' = -0.009, P = 0.741). Additionally, a mediation effect of HIF3A methylation was found in the association between the HIF3A rs3826795 polymorphism and ALT among obese children (β' = 0.242, P = 0.014). CONCLUSION This is the first study to report the interaction between obesity and HIF3A gene in relation with ALT, and also to reveal a mediation effect among the HIF3A polymorphism, methylation and ALT. This study provides new evidence to the function of HIF3A gene, which would be helpful for future risk assessment and personalized treatment of liver diseases.
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Affiliation(s)
- Shuo Wang
- Institute of Child and Adolescent Health of Peking University, School of Public Health, Peking University Health Science Center, Beijing, 100191, China.,Interdisciplinary Center for Network Science and Applications (iCeNSA), University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Jieyun Song
- Institute of Child and Adolescent Health of Peking University, School of Public Health, Peking University Health Science Center, Beijing, 100191, China
| | - Yide Yang
- Institute of Child and Adolescent Health of Peking University, School of Public Health, Peking University Health Science Center, Beijing, 100191, China
| | - Yining Zhang
- Institute of Child and Adolescent Health of Peking University, School of Public Health, Peking University Health Science Center, Beijing, 100191, China
| | - Nitesh V Chawla
- Interdisciplinary Center for Network Science and Applications (iCeNSA), University of Notre Dame, Notre Dame, IN, 46556, USA.,Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Jun Ma
- Institute of Child and Adolescent Health of Peking University, School of Public Health, Peking University Health Science Center, Beijing, 100191, China.
| | - Haijun Wang
- Division of Maternal and Child Health, School of Public Health, Peking University Health Science Center, Beijing, 100191, China.
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Luijken J, van der Schouw YT, Mensink D, Onland-Moret NC. Association between age at menarche and cardiovascular disease: A systematic review on risk and potential mechanisms. Maturitas 2017; 104:96-116. [PMID: 28923182 DOI: 10.1016/j.maturitas.2017.07.009] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Accepted: 07/20/2017] [Indexed: 10/19/2022]
Abstract
Age at menarche (AAM) has been reported to be associated with the risk of cardiovascular disease (CVD), but the shape of and the mechanisms behind this association remain unclear. We reviewed the data on the association between AAM and different subtypes of CVD, and used shared genetic loci to identify possible mechanisms underlying this association using shared genetic association. We searched the databases of PubMed, Web of Science and Embase through to April 2017. We included articles with any clinically manifest CVD endpoint and for any ethnicity. We identified single nucleotide polymorphisms (SNPs) for AAM in genome-wide association studies (GWAS) in Caucasians through PubMed and HuGE Navigator, and searched whether these SNPs or any of their proxies were associated with any CVD-related trait. Eight studies in Caucasian populations reported an inverse linear relation between AAM and CVD risk, whereas one large study reported a significant U-shaped relation between them. Data from Asian populations were contradictory and inconclusive. In total, 122 AAM SNPs were identified at a genome-wide significance level (p<5×10-8). Of those, 18 were also associated with various CVD-related traits, primarily body mass index (BMI), obesity, and height. In conclusion, early AAM and possibly also late AAM increase the risk of CVD in Caucasian populations. Weight and height may be part of the mechanism underlying the relation between AAM and CVD risk in Caucasians. Data on other ethnicities are too limited for meaningful analysis and conclusions.
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Affiliation(s)
- Janneke Luijken
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Yvonne T van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Daniëlle Mensink
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; Cardialysis, Rotterdam, The Netherlands
| | - N Charlotte Onland-Moret
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
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131
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Genetically predicted high body mass index is associated with increased gastric cancer risk. Eur J Hum Genet 2017. [PMID: 28635950 DOI: 10.1038/ejhg.2017.103] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Epidemiological studies have linked body mass index (BMI) with risk of gastrointestinal cancers. However, for gastric cancer, the relationship is more controversial. In particular, it is unclear whether the observed association is due to confounding or bias inherent in conventional observational studies. To investigate whether BMI is causally associated with gastric cancer risk, we applied Mendelian randomization using individual-level data from 2631 gastric cancer cases and 4373 cancer-free controls. We derived a weighted genetic risk score (wGRS) using 37 BMI-associated genetic variants as an instrumental variable. We used logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between genetically predicted BMI and gastric cancer risk. We observed that higher genetically determined BMI was associated with increased gastric cancer risk (per standard deviation (SD) increase in the wGRS: OR=1.07, 95% CI: 1.02-1.13, P=4.94 × 10-3). Compared with individuals in the bottom tertile of the BMI wGRS, those in the top tertile had 1.14-fold (95% CI: 1.01-1.29) increased risk of developing gastric cancer. Sensitivity analyses using alternative causal inference measures demonstrated consistent association. Our study indicated that genetically high BMI was associated with increased gastric cancer risk, suggesting that high BMI may have a causal role in the etiology of gastric cancer.
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132
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Li ZM, Kong CY, Sun KY, Wang LS. The ALDH2 gene rs671 polymorphism is not associated with essential hypertension. Clin Exp Hypertens 2017; 39:691-695. [PMID: 28613083 DOI: 10.1080/10641963.2017.1299749] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Essential hypertension (EH) is a worldwide problem. Acetaldehyde dehydrogenase 2 (ALDH2) gene has been suggested to be correlated with EH. However, the results are inconsistent. This study aimed to investigate the associations of ALDH2 rs671 polymorphism with EH in a Chinese Han population in Shanghai. Genotype of ALDH2 rs671 was analyzed in 1923 EH patients and 1115 control subjects. We found no association between ALDH2 rs671 and EH risk or EH-related quantitative blood chemistry values. Furthermore, a meta-analysis was performed and the summary results from 11220 patients and 8339 control subjects were consistent with our findings. These results indicated that rs671 of ALDH2 may not associate with the risk of EH.
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Affiliation(s)
- Zhan-Ming Li
- a Center of Molecular Medicine, Ruijin Hospital , Shanghai Jiao-tong University School of Medicine , Shanghai , P.R. China
| | - Chao-Yue Kong
- b Institute of Biomedical Sciences and Emergency Department , Minhang Hospital, Fudan University , Shanghai , P.R. China
| | - Ke-Yu Sun
- b Institute of Biomedical Sciences and Emergency Department , Minhang Hospital, Fudan University , Shanghai , P.R. China
| | - Li-Shun Wang
- a Center of Molecular Medicine, Ruijin Hospital , Shanghai Jiao-tong University School of Medicine , Shanghai , P.R. China
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133
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Fernández-Rhodes L, Gong J, Haessler J, Franceschini N, Graff M, Nishimura KK, Wang Y, Highland HM, Yoneyama S, Bush WS, Goodloe R, Ritchie MD, Crawford D, Gross M, Fornage M, Buzkova P, Tao R, Isasi C, Avilés-Santa L, Daviglus M, Mackey RH, Houston D, Gu CC, Ehret G, Nguyen KDH, Lewis CE, Leppert M, Irvin MR, Lim U, Haiman CA, Le Marchand L, Schumacher F, Wilkens L, Lu Y, Bottinger EP, Loos RJL, Sheu WHH, Guo X, Lee WJ, Hai Y, Hung YJ, Absher D, Wu IC, Taylor KD, Lee IT, Liu Y, Wang TD, Quertermous T, Juang JMJ, Rotter JI, Assimes T, Hsiung CA, Chen YDI, Prentice R, Kuller LH, Manson JE, Kooperberg C, Smokowski P, Robinson WR, Gordon-Larsen P, Li R, Hindorff L, Buyske S, Matise TC, Peters U, North KE. Trans-ethnic fine-mapping of genetic loci for body mass index in the diverse ancestral populations of the Population Architecture using Genomics and Epidemiology (PAGE) Study reveals evidence for multiple signals at established loci. Hum Genet 2017; 136:771-800. [PMID: 28391526 PMCID: PMC5485655 DOI: 10.1007/s00439-017-1787-6] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2016] [Accepted: 03/23/2017] [Indexed: 11/26/2022]
Abstract
Most body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5-70 kg/m2) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p < 0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants.
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Affiliation(s)
- Lindsay Fernández-Rhodes
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Jian Gong
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Nora Franceschini
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Mariaelisa Graff
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Katherine K Nishimura
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Yujie Wang
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Heather M Highland
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sachiko Yoneyama
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - William S Bush
- Department of Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Robert Goodloe
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA
| | - Marylyn D Ritchie
- Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, USA
| | - Dana Crawford
- Department of Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Myriam Fornage
- Center for Human Genetics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Petra Buzkova
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Ran Tao
- Department of Biostatistics, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Carmen Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | | | - Martha Daviglus
- Insitute of Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Rachel H Mackey
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Denise Houston
- Geriatrics and Gerontology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - C Charles Gu
- Division of Biostatistics, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Georg Ehret
- Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
- Division of Cardiology, Geneva University Hospital, Geneva, OH, Switzerland
| | - Khanh-Dung H Nguyen
- Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Cora E Lewis
- Department of Medicine, University of Alabama, Birmingham, AL, USA
| | - Mark Leppert
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | | | - Unhee Lim
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Fredrick Schumacher
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Lynne Wilkens
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Yingchang Lu
- Charles R. Bronfman Instituted for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Erwin P Bottinger
- Charles R. Bronfman Instituted for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ruth J L Loos
- Charles R. Bronfman Instituted for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Wayne H-H Sheu
- Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, National Defense Medical Center, National Yang-Ming University, Taipei, Taiwan
| | - Xiuqing Guo
- Department of Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Wen-Jane Lee
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Yang Hai
- Department of Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yi-Jen Hung
- Division of Endocrinology and Metabolism, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - I-Chien Wu
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan Town, Taiwan
| | - Kent D Taylor
- Department of Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - I-Te Lee
- Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, National Defense Medical Center, National Yang-Ming University, Taipei, Taiwan
| | - Yeheng Liu
- Department of Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Tzung-Dau Wang
- Division of Cardiology, Department of Internal Medicine, Cardiovascular Center, National Taiwan University Hospital, Taipei, Taiwan
| | - Thomas Quertermous
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Jyh-Ming J Juang
- Division of Cardiology, Department of Internal Medicine, Cardiovascular Center, National Taiwan University Hospital, Taipei, Taiwan
| | - Jerome I Rotter
- Department of Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Themistocles Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Chao A Hsiung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan Town, Taiwan
| | - Yii-Der Ida Chen
- Department of Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ross Prentice
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Lewis H Kuller
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - JoAnn E Manson
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Paul Smokowski
- School of Social Welfare, The University of Kansas, Lawrence, KS, USA
| | - Whitney R Robinson
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Penny Gordon-Larsen
- Department of Nutrition, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Rongling Li
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lucia Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Steven Buyske
- Department of Statistics and Biostatistics, Rutgers University, Piscataway, NJ, USA
| | - Tara C Matise
- Department of Genetics, Rutgers University, Piscataway, NJ, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Kari E North
- Department of Epidemiology, UNC Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Fall T, Mendelson M, Speliotes EK. Recent Advances in Human Genetics and Epigenetics of Adiposity: Pathway to Precision Medicine? Gastroenterology 2017; 152:1695-1706. [PMID: 28214526 PMCID: PMC5576453 DOI: 10.1053/j.gastro.2017.01.054] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Revised: 01/26/2017] [Accepted: 01/30/2017] [Indexed: 12/26/2022]
Abstract
Obesity is a heritable trait that contributes to substantial global morbidity and mortality. Here, we summarize findings from the past decade of genetic and epigenetic research focused on unravelling the underpinnings of adiposity. More than 140 genetic regions now are known to influence adiposity traits. The genetics of general adiposity, as measured by body mass index, and that of abdominal obesity, as measured by waist-to-hip ratio, have distinct biological backgrounds. Gene expression associated with general adiposity is enriched in the nervous system. In contrast, genes associated with abdominal adiposity function in adipose tissue. Recent population-based epigenetic analyses have highlighted additional distinct loci. We discuss how associated genetic variants can lead to understanding causal mechanisms, and to disentangling reverse causation in epigenetic analyses. Discoveries emerging from population genomics are identifying new disease markers and potential novel drug targets to better define and combat obesity and related diseases.
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Affiliation(s)
- Tove Fall
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Michael Mendelson
- The Framingham Heart Study, Framingham, Massachusetts,Population Sciences Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland,Department of Cardiology, Boston Children’s Hospital, Boston, Massachusetts
| | - Elizabeth K. Speliotes
- Department of Internal Medicine, Division of Gastroenterology,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
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Ng MCY, Graff M, Lu Y, Justice AE, Mudgal P, Liu CT, Young K, Yanek LR, Feitosa MF, Wojczynski MK, Rand K, Brody JA, Cade BE, Dimitrov L, Duan Q, Guo X, Lange LA, Nalls MA, Okut H, Tajuddin SM, Tayo BO, Vedantam S, Bradfield JP, Chen G, Chen WM, Chesi A, Irvin MR, Padhukasahasram B, Smith JA, Zheng W, Allison MA, Ambrosone CB, Bandera EV, Bartz TM, Berndt SI, Bernstein L, Blot WJ, Bottinger EP, Carpten J, Chanock SJ, Chen YDI, Conti DV, Cooper RS, Fornage M, Freedman BI, Garcia M, Goodman PJ, Hsu YHH, Hu J, Huff CD, Ingles SA, John EM, Kittles R, Klein E, Li J, McKnight B, Nayak U, Nemesure B, Ogunniyi A, Olshan A, Press MF, Rohde R, Rybicki BA, Salako B, Sanderson M, Shao Y, Siscovick DS, Stanford JL, Stevens VL, Stram A, Strom SS, Vaidya D, Witte JS, Yao J, Zhu X, Ziegler RG, Zonderman AB, Adeyemo A, Ambs S, Cushman M, Faul JD, Hakonarson H, Levin AM, Nathanson KL, Ware EB, Weir DR, Zhao W, Zhi D, Arnett DK, Grant SFA, Kardia SLR, Oloapde OI, Rao DC, Rotimi CN, Sale MM, Williams LK, Zemel BS, Becker DM, Borecki IB, Evans MK, Harris TB, Hirschhorn JN, Li Y, Patel SR, Psaty BM, Rotter JI, Wilson JG, Bowden DW, Cupples LA, Haiman CA, Loos RJF, North KE. Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium. PLoS Genet 2017; 13:e1006719. [PMID: 28430825 PMCID: PMC5419579 DOI: 10.1371/journal.pgen.1006719] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Revised: 05/05/2017] [Accepted: 03/29/2017] [Indexed: 11/20/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10−8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations. Genome-wide association studies (GWAS) have identified >300 genetic regions that influence body size and shape as measured by body mass index (BMI) and waist-to-hip ratio (WHR), respectively, but few have been identified in populations of African ancestry. We conducted large scale high coverage GWAS and replication of these traits in 52,895 and 23,095 individuals of African ancestry, respectively, followed by additional replication in European populations. We identified 10 genome-wide significant loci in all individuals, and an additional seven loci by analyzing men and women separately. We combined African and European ancestry GWAS and were able to narrow down 43 out of 74 African ancestry associated genetic regions to contain small number of putative causal variants. Our results highlight the improvement of applying high density genome coverage and combining multiple ancestries in the identification and refinement of location of genetic regions associated with adiposity traits.
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Affiliation(s)
- Maggie C. Y. Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States of America
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Icachn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Anne E. Justice
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States of America
| | - Poorva Mudgal
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America
| | - Kristin Young
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States of America
| | - Lisa R. Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Mary F. Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis MO, United States of America
| | - Mary K. Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis MO, United States of America
| | - Kristin Rand
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, United States of America
| | - Brian E. Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Latchezar Dimitrov
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
| | - Qing Duan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Leslie A. Lange
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
| | - Michael A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, United States of America
- Data Tecnica International, Glen Echo, MD, United States of America
| | - Hayrettin Okut
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
| | - Salman M. Tajuddin
- National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Bamidele O. Tayo
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, IL, United States of America
| | - Sailaja Vedantam
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, United States of America
- Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
| | - Jonathan P. Bradfield
- Center for Applied Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, United States of America
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States of America
| | - Wei-Min Chen
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, United States of America
| | - Alessandra Chesi
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, United States of America
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Badri Padhukasahasram
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI, United States of America
| | - Jennifer A. Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, United States of America
| | - Matthew A. Allison
- Division of Preventive Medicine, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, United States of America
| | - Christine B. Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY, United States of America
| | - Elisa V. Bandera
- Department of Population Science, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States of America
| | - Traci M. Bartz
- Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Sonja I. Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, United States of America
| | - Leslie Bernstein
- Beckman Research Institute of the City of Hope, Duarte, CA, United States of America
| | - William J. Blot
- International Epidemiology Institute, Rockville, MD, United States of America
| | - Erwin P. Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icachn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - John Carpten
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, United States of America
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - David V. Conti
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
| | - Richard S. Cooper
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, IL, United States of America
| | - Myriam Fornage
- Center for Human Genetics, University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | - Barry I. Freedman
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
| | - Melissa Garcia
- National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Phyllis J. Goodman
- SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
| | - Yu-Han H. Hsu
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, United States of America
- Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, United States of America
| | - Jennifer Hu
- Sylvester Comprehensive Cancer Center, University of Miami Leonard Miller School of Medicine, Miami, FL, United States of America
- Department of Public Health Sciences, University of Miami Leonard Miller School of Medicine, Miami, FL, United States of America
| | - Chad D. Huff
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, United States of America
| | - Sue A. Ingles
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, United States of America
| | - Esther M. John
- Cancer Prevention Institute of California, Fremont, CA, United States of America
- Department of Health Research and Policy (Epidemiology) and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, United States of America
| | - Rick Kittles
- Division of Urology, Department of Surgery, The University of Arizona, Tucson, AZ, United States of America
| | - Eric Klein
- Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH, United States of America
| | - Jin Li
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Palo Alto, CA, United States of America
| | - Barbara McKnight
- Cardiovascular Health Research Unit, Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Uma Nayak
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, United States of America
| | - Barbara Nemesure
- Department of Preventive Medicine, Stony Brook University, Stony Brook, NY, United States of America
| | | | - Andrew Olshan
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, Chapel Hill, NC, United States of America
| | - Michael F. Press
- Department of Pathology and Norris Comprehensive Cancer Center, University of Southern California Keck School of Medicine, Los Angeles, CA, United States of America
| | - Rebecca Rohde
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States of America
| | - Benjamin A. Rybicki
- Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, United States of America
| | | | - Maureen Sanderson
- Department of Family and Community Medicine, Meharry Medical College, Nashville, TN, United States of America
| | - Yaming Shao
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States of America
| | - David S. Siscovick
- The New York Academy of Medicine, New York, NY, United States of America
| | - Janet L. Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States of America
| | - Victoria L. Stevens
- Epidemiology Research Program, American Cancer Society, Atlanta, GA, United States of America
| | - Alex Stram
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
| | - Sara S. Strom
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, United States of America
| | - Dhananjay Vaidya
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
- Department of Epidemiology, Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - John S. Witte
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States of America
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, United States of America
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, United States of America
| | - Regina G. Ziegler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States of America
| | - Alan B. Zonderman
- National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States of America
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, National Cancer Institute, Bethesda, MD, United States of America
| | - Mary Cushman
- Department of Medicine, University of Vermont College of Medicine, Burlington, VT, United States of America
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States of America
| | - Hakon Hakonarson
- Center for Applied Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, United States of America
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Albert M. Levin
- Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, United States of America
| | - Katherine L. Nathanson
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Erin B. Ware
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States of America
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States of America
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America
| | - Degui Zhi
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | | | - Donna K. Arnett
- School of Public Health, University of Kentucky, Lexington, KY, United States of America
| | - Struan F. A. Grant
- Center for Applied Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, United States of America
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, United States of America
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Division of Endocrinology, The Children’s Hospital of Philadelphia, Philadelphia, PA, United States of America
| | - Sharon L. R. Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America
| | - Olufunmilayo I. Oloapde
- Center for Clinical Cancer Genetics, Department of Medicine and Human Genetics, University of Chicago, Chicago, IL, United States of America
| | - D. C. Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States of America
| | - Michele M. Sale
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, United States of America
| | - L. Keoki Williams
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI, United States of America
- Department of Internal Medicine, Henry Ford Health System, Detroit, MI, United States of America
| | - Babette S. Zemel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Division of Gastroenterology, Hepatology and Nutrition, The Children’s Hospital of Philadelphia, Philadelphia, PA, United States of America
| | - Diane M. Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Ingrid B. Borecki
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis MO, United States of America
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Inc, United States of America
| | - Michele K. Evans
- National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Tamara B. Harris
- National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Joel N. Hirschhorn
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA, United States of America
- Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
- Departments of Genetics and Pediatrics, Harvard Medical School, Boston, MA, United States of America
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
| | - Sanjay R. Patel
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA, United States of America
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States of America
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, United States of America
- Division of Genomic Outcomes, Departments of Pediatrics and Medicine, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Los Angeles, CA, United States of America
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, United States of America
| | - Donald W. Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
| | - L. Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America
- NHLBI Framingham Heart Study, Framingham, MA, United States of America
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, United States of America
- * E-mail: (CAH); (RJFL); (KEN)
| | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icachn School of Medicine at Mount Sinai, New York, NY, United States of America
- The Mindich Child Health and Development Institute, Ichan School of Medicine at Mount Sinai, New York, NY, United States of America
- * E-mail: (CAH); (RJFL); (KEN)
| | - Kari E. North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States of America
- * E-mail: (CAH); (RJFL); (KEN)
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Zhu Y, Zhang D, Zhou D, Li Z, Li Z, Fang L, Yang M, Shan Z, Li H, Chen J, Zhou X, Ye W, Yu S, Li H, Cai L, Liu C, Zhang J, Wang L, Lai Y, Ruan L, Sun Z, Zhang S, Wang H, Liu Y, Xu Y, Ling J, Xu C, Zhang Y, Lv D, Yuan Z, Zhang J, Zhang Y, Shi Y, Lai M. Susceptibility loci for metabolic syndrome and metabolic components identified in Han Chinese: a multi-stage genome-wide association study. J Cell Mol Med 2017; 21:1106-1116. [PMID: 28371326 PMCID: PMC5431133 DOI: 10.1111/jcmm.13042] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2016] [Accepted: 10/20/2016] [Indexed: 12/19/2022] Open
Abstract
Metabolic syndrome (MetS), a cluster of metabolic disturbances that increase the risk for cardiovascular disease and diabetes, was because of genetic susceptibility and environmental risk factors. To identify the genetic variants associated with MetS and metabolic components, we conducted a genome-wide association study followed by replications in totally 12,720 participants from the north, north-eastern and eastern China. In combined analyses, independent of the top known signal at rs651821 on APOA5, we newly identified a secondary triglyceride-associated signal at rs180326 on BUD13 (Pcombined = 2.4 × 10-8 ). Notably, by an integrated analysis of the genotypes and the serum levels of APOA5, BUD13 and triglyceride, we observed that BUD13 was another potential mediator, besides APOA5, of the association between rs651821 and serum triglyceride. rs671 (ALDH2), an east Asian-specific common variant, was found to be associated with MetS (Pcombined = 9.7 × 10-22 ) in Han Chinese. The effects of rs671 on metabolic components were more prominent in drinkers than in non-drinkers. The replicated loci provided information on the genetic basis and mechanisms of MetS and metabolic components in Han Chinese.
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Affiliation(s)
- Yimin Zhu
- Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, Zhejiang, China
| | - Dandan Zhang
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.,Key Laboratory of Disease Proteomics of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Dan Zhou
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.,Key Laboratory of Disease Proteomics of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Zhenli Li
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.,Key Laboratory of Disease Proteomics of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Zhiqiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China.,Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, China
| | - Le Fang
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Min Yang
- Department of Nutrition and Food Safety, Zhejiang University School of Public Health, Hangzhou, China
| | - Zhongyan Shan
- The Endocrine Institute and Liaoning Provincial Key Laboratory of Endocrine Diseases, Department of Endocrinology and Metabolism, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Hong Li
- Department of Endocrinology, Sir Run Run Shaw Hospital Affiliated to School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jianhua Chen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China.,Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, China
| | - Xianghai Zhou
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Beijing, China.,Peking University Diabetes Center, Beijing, China
| | - Wei Ye
- Key Laboratory of Laboratory Medicine, Ministry of Education of China, School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Senhai Yu
- Daicun Town Community Health Service Center, Xiaoshan District, Hangzhou, Zhejiang, China
| | - Huabin Li
- Xiaoshan District Sixth People's Hospital, Hangzhou, Zhejiang, China
| | - Libin Cai
- Xiaoshan District Third People's Hospital, Hangzhou, Zhejiang, China
| | - Chengguo Liu
- Putuo District People's Hospital, Zhoushan, Zhejiang, China
| | - Jie Zhang
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Lixin Wang
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Yaxin Lai
- The Endocrine Institute and Liaoning Provincial Key Laboratory of Endocrine Diseases, Department of Endocrinology and Metabolism, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Liansheng Ruan
- Putuo District People's Hospital, Zhoushan, Zhejiang, China
| | - Zhanhang Sun
- Putuo District People's Hospital, Zhoushan, Zhejiang, China
| | - Shuai Zhang
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.,Key Laboratory of Disease Proteomics of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Hao Wang
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.,Key Laboratory of Disease Proteomics of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Yi Liu
- Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, Zhejiang, China
| | - Yuyang Xu
- Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, Zhejiang, China
| | - Jie Ling
- Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, Zhejiang, China
| | - Chunxiao Xu
- Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, Zhejiang, China.,Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Yan Zhang
- Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, Zhejiang, China
| | - Duo Lv
- Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, Zhejiang, China
| | - Zheping Yuan
- Department of Epidemiology & Biostatistics, Zhejiang University School of Public Health, Hangzhou, Zhejiang, China
| | - Jing Zhang
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.,Key Laboratory of Disease Proteomics of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Yingqi Zhang
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.,Key Laboratory of Disease Proteomics of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China.,Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, China
| | - Maode Lai
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.,Key Laboratory of Disease Proteomics of Zhejiang Province, Hangzhou, Zhejiang, China
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Bricard G, Cros-Perrial E, Machon C, Dumontet C, Jordheim LP. Stably transfected adherent cancer cell models with decreased expression of 5'-nucleotidase cN-II. NUCLEOSIDES NUCLEOTIDES & NUCLEIC ACIDS 2017; 35:604-612. [PMID: 27906612 DOI: 10.1080/15257770.2016.1163375] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
The 5'-nucleotidase cN-II has been shown to be associated with the sensitivity to nucleoside analogues, the survival of cytarabine treated leukemia patients and to cell proliferation. Due to the lack of relevant cell models for solid tumors, we developed four cell lines with low cN-II expression and characterized them concerning their in vitro sensitivity to cancer drugs and their intracellular nucleotide pools. All four cell models had an important decrease of cN-II expression but did not show modified sensitivity, cell proliferation or nucleotide pools. Our cell models will be important for the study of the role of cN-II in human cancer cells.
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Affiliation(s)
- Gabriel Bricard
- a Université de Lyon , Lyon , France.,b Université de Lyon , Lyon , France.,c INSERM U1052, Centre de Recherche en Cancérologie de Lyon , Lyon , France.,d CNRS UMR 5286, Centre de Recherche en Cancérologie de Lyon , Lyon , France.,e Centre Léon Bérard , Lyon , France
| | - Emeline Cros-Perrial
- a Université de Lyon , Lyon , France.,b Université de Lyon , Lyon , France.,c INSERM U1052, Centre de Recherche en Cancérologie de Lyon , Lyon , France.,d CNRS UMR 5286, Centre de Recherche en Cancérologie de Lyon , Lyon , France.,e Centre Léon Bérard , Lyon , France
| | - Christelle Machon
- a Université de Lyon , Lyon , France.,b Université de Lyon , Lyon , France.,f Hospices Civils de Lyon , Lyon , France
| | - Charles Dumontet
- a Université de Lyon , Lyon , France.,b Université de Lyon , Lyon , France.,c INSERM U1052, Centre de Recherche en Cancérologie de Lyon , Lyon , France.,d CNRS UMR 5286, Centre de Recherche en Cancérologie de Lyon , Lyon , France.,e Centre Léon Bérard , Lyon , France.,f Hospices Civils de Lyon , Lyon , France
| | - Lars Petter Jordheim
- a Université de Lyon , Lyon , France.,b Université de Lyon , Lyon , France.,c INSERM U1052, Centre de Recherche en Cancérologie de Lyon , Lyon , France.,d CNRS UMR 5286, Centre de Recherche en Cancérologie de Lyon , Lyon , France.,e Centre Léon Bérard , Lyon , France
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138
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The transcriptional architecture of phenotypic dimorphism. Nat Ecol Evol 2017; 1:6. [PMID: 28812569 DOI: 10.1038/s41559-016-0006] [Citation(s) in RCA: 94] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Accepted: 09/06/2016] [Indexed: 12/11/2022]
Abstract
The profound differences in gene expression between the sexes are increasingly used to study the molecular basis of sexual dimorphism, sexual selection and sexual conflict. Studies of transcriptional architecture, based on comparisons of gene expression, have also been implemented for a wide variety of other intra-specific polymorphisms. These efforts are based on key assumptions regarding the relationship between transcriptional architecture, phenotypic variation and the target of selection. Some of these assumptions are better supported by available evidence than others. In all cases, the evidence is largely circumstantial, leaving considerable gaps in our understanding of the relationship between transcriptional and phenotypic dimorphism.
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139
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Amare AT, Schubert KO, Klingler-Hoffmann M, Cohen-Woods S, Baune BT. The genetic overlap between mood disorders and cardiometabolic diseases: a systematic review of genome wide and candidate gene studies. Transl Psychiatry 2017; 7:e1007. [PMID: 28117839 PMCID: PMC5545727 DOI: 10.1038/tp.2016.261] [Citation(s) in RCA: 212] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Revised: 10/21/2016] [Accepted: 10/31/2016] [Indexed: 12/11/2022] Open
Abstract
Meta-analyses of genome-wide association studies (meta-GWASs) and candidate gene studies have identified genetic variants associated with cardiovascular diseases, metabolic diseases and mood disorders. Although previous efforts were successful for individual disease conditions (single disease), limited information exists on shared genetic risk between these disorders. This article presents a detailed review and analysis of cardiometabolic diseases risk (CMD-R) genes that are also associated with mood disorders. First, we reviewed meta-GWASs published until January 2016, for the diseases 'type 2 diabetes, coronary artery disease, hypertension' and/or for the risk factors 'blood pressure, obesity, plasma lipid levels, insulin and glucose related traits'. We then searched the literature for published associations of these CMD-R genes with mood disorders. We considered studies that reported a significant association of at least one of the CMD-R genes and 'depression' or 'depressive disorder' or 'depressive symptoms' or 'bipolar disorder' or 'lithium treatment response in bipolar disorder', or 'serotonin reuptake inhibitors treatment response in major depression'. Our review revealed 24 potential pleiotropic genes that are likely to be shared between mood disorders and CMD-Rs. These genes include MTHFR, CACNA1D, CACNB2, GNAS, ADRB1, NCAN, REST, FTO, POMC, BDNF, CREB, ITIH4, LEP, GSK3B, SLC18A1, TLR4, PPP1R1B, APOE, CRY2, HTR1A, ADRA2A, TCF7L2, MTNR1B and IGF1. A pathway analysis of these genes revealed significant pathways: corticotrophin-releasing hormone signaling, AMPK signaling, cAMP-mediated or G-protein coupled receptor signaling, axonal guidance signaling, serotonin or dopamine receptors signaling, dopamine-DARPP32 feedback in cAMP signaling, circadian rhythm signaling and leptin signaling. Our review provides insights into the shared biological mechanisms of mood disorders and cardiometabolic diseases.
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Affiliation(s)
- A T Amare
- Discipline of Psychiatry, School of Medicine, The University of Adelaide, Adelaide, SA, Australia
| | - K O Schubert
- Discipline of Psychiatry, School of Medicine, The University of Adelaide, Adelaide, SA, Australia,Northern Adelaide Local Health Network, Mental Health Services, Adelaide, SA, Australia
| | - M Klingler-Hoffmann
- Adelaide Proteomics Centre, School of Biological Sciences, The University of Adelaide, Adelaide, SA, Australia
| | - S Cohen-Woods
- School of Psychology, Faculty of Social and Behavioural Sciences, Flinders University, Adelaide, SA, Australia
| | - B T Baune
- Discipline of Psychiatry, School of Medicine, The University of Adelaide, Adelaide, SA, Australia,Discipline of Psychiatry, School of Medicine, The University of Adelaide, North Terrace, Adelaide, SA 5005, Australia. E-mail:
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140
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Shi J, Zhang B, Choi JY, Gao YT, Li H, Lu W, Long J, Kang D, Xiang YB, Wen W, Park SK, Ye X, Noh DY, Zheng Y, Wang Y, Chung S, Lin X, Cai Q, Shu XO. Age at menarche and age at natural menopause in East Asian women: a genome-wide association study. AGE (DORDRECHT, NETHERLANDS) 2016; 38:513-523. [PMID: 27629107 PMCID: PMC5266214 DOI: 10.1007/s11357-016-9939-5] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2015] [Accepted: 07/14/2016] [Indexed: 06/06/2023]
Abstract
Age at menarche (AM) and age at natural menopause (ANM) are complex traits with a high heritability. Abnormal timing of menarche or menopause is associated with a reduced span of fertility and risk for several age-related diseases including breast, endometrial and ovarian cancer, cardiovascular disease, and osteoporosis. To identify novel genetic loci for AM or ANM in East Asian women and to replicate previously identified loci primarily in women of European ancestry by genome-wide association studies (GWASs), we conducted a two-stage GWAS. Stage I aimed to discover promising novel AM and ANM loci using GWAS data of 8073 women from Shanghai, China. The Stage II replication study used the data from another Chinese GWAS (n = 1230 for AM and n = 1458 for ANM), a Korean GWAS (n = 4215 for AM and n = 1739 for ANM), and de novo genotyping of 2877 additional Chinese women. Previous GWAS-identified loci for AM and ANM were also evaluated. We identified two suggestive menarcheal age loci tagged by rs79195475 at 10q21.3 (beta = -0.118 years, P = 3.4 × 10-6) and rs1023935 at 4p15.1 (beta = -0.145 years, P = 4.9 × 10-6) and one menopausal age locus tagged by rs3818134 at 22q12.2 (beta = -0.276 years, P = 8.8 × 10-6). These suggestive loci warrant a further validation in independent populations. Although limited by low statistical power, we replicated 19 of the 98 menarche loci and 5 of the 20 menopause loci previously identified in women of European ancestry in East Asian women, suggesting a shared genetic architecture for these two traits across populations.
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Affiliation(s)
- Jiajun Shi
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA
| | - Ben Zhang
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA
| | - Ji-Yeob Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Korea
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Huaixing Li
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai, China
| | - Wei Lu
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Jirong Long
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA
| | - Daehee Kang
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Korea
| | - Yong-Bing Xiang
- Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Wanqing Wen
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA
| | - Sue K Park
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Korea
| | - Xingwang Ye
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai, China
| | - Dong-Young Noh
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
| | - Ying Zheng
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Yiqin Wang
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai, China
| | - Seokang Chung
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
| | - Xu Lin
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai, China
| | - Qiuyin Cai
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA
| | - Xiao-Ou Shu
- Department of Medicine, Vanderbilt Epidemiology Center and Division of Epidemiology, Vanderbilt University School of Medicine, 2525 West End Avenue, Suite 600, IMPH, Nashville, Tennessee, 37203, USA.
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141
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Joint association analysis of a binary and a quantitative trait in family samples. Eur J Hum Genet 2016; 25:130-136. [PMID: 27782109 DOI: 10.1038/ejhg.2016.134] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2016] [Revised: 07/05/2016] [Accepted: 09/06/2016] [Indexed: 12/12/2022] Open
Abstract
In recent years, improved genotyping and sequencing technologies have enabled the discovery of new loci associated with various diseases or traits. For instance, by testing the association with each single-nucleotide variant (SNV) separately, genome-wide association studies (GWAS) have achieved tremendous success in identifying SNVs associated with specific traits. However, little is known about the common genetic basis of multiple traits owing to lack of efficient methods. With the use of extended quasi-likelihood, a Wald test has been proposed to perform a bivariate analysis of a continuous and a binary trait in unrelated samples. However, owing to its low computational efficiency, it has not been implemented in real applications to large-scale genetic studies. In this paper, we propose an efficient bivariate robust score test for two traits, one continuous and one binary, based on extended generalized estimating equations. Our approach is applicable to both family-based and unrelated study designs and can be extended to test the association of multiple traits. Our simulation studies demonstrate the type-I error rate of our approach is well controlled in all minor allele frequency (MAF) scenarios, with MAF ranging from 1 to 30%, and the method is more powerful in certain MAF scenarios than univariate testing with correction for multiple testing. Because of the computational advantage of score tests, our approach is readily applicable to GWAS or sequencing studies. Finally, we present a real application to uncover genetic variants associated with body mass index and type-2 diabetes in the Framingham Heart Study.
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142
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de Toro-Martín J, Guénard F, Tchernof A, Deshaies Y, Pérusse L, Biron S, Lescelleur O, Biertho L, Marceau S, Vohl MC. A GWAS follow-up of obesity-related SNPs in SYPL2 reveals sex-specific association with hip circumference. Obes Sci Pract 2016; 2:407-414. [PMID: 28090346 PMCID: PMC5192540 DOI: 10.1002/osp4.74] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Revised: 09/07/2016] [Accepted: 09/15/2016] [Indexed: 01/03/2023] Open
Abstract
Objective A novel single‐nucleotide polymorphism (SNP) associated with morbid obesity was recently identified by exome sequencing. The purpose of this study was to follow up this low‐frequency coding SNP located within the SYPL2 locus and associated with body mass index in order to reveal novel associations with obesity‐related traits. Methods The body mass index‐associated SNP (rs62623713 A>G [chr1:109476817/hg19]) and two tagging SNPs within the SYPL2 locus, rs9661614 T>C (chr1:109479215) and rs485660 G>A (chr1:109480810), were genotyped in the obesity (n = 3,017) and the infogene (n = 676) cohorts, which were further combined, leading to a larger cohort of 3,693 individuals. Association testing was performed by general linear models in the obesity cohort and validated by joint analysis in the combined cohort. Results rs9661614 and rs485660 were significantly associated with hip circumference (HC) in the obesity cohort, with heterozygotes exhibiting a significantly lower HC. These results were validated by joint analysis for rs9661614 (false discovery rate [FDR]‐corrected P = 7.5 × 10−4) and, to a lesser extent, for rs485660 (FDR corrected P = 3.9 × 10−2). The association with HC remained significant for rs9661614 when tested independently in women (FDR‐corrected P = 1.7 × 10−2), but not for rs485660 (FDR‐corrected P = 0.2). Both associations were absent in men. Conclusions This study reveals strong evidence for a novel association between rs9661614 (T>C) and HC in women, which likely reflects a preferential association of SYPL2 to a gynoid profile of fat distribution. The study findings support a clinical significance of SYPL2 worth considering when assessing risk factors associated with obesity.
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Affiliation(s)
- J de Toro-Martín
- Institute of Nutrition and Functional Foods (INAF) Laval University Quebec Quebec Canada; School of Nutrition Laval University Quebec Quebec Canada
| | - F Guénard
- Institute of Nutrition and Functional Foods (INAF) Laval University Quebec Quebec Canada; School of Nutrition Laval University Quebec Quebec Canada
| | - A Tchernof
- School of Nutrition Laval University Quebec Quebec Canada; Quebec Heart and Lung Institute Research Center Quebec Quebec Canada
| | - Y Deshaies
- Quebec Heart and Lung Institute Research Center Quebec Quebec Canada; Department of Medicine Laval University Quebec Quebec Canada
| | - L Pérusse
- Institute of Nutrition and Functional Foods (INAF) Laval University Quebec Quebec Canada; Department of Kinesiology Laval University Quebec Quebec Canada
| | - S Biron
- Department of Surgery Laval University Quebec Quebec Canada
| | - O Lescelleur
- Department of Surgery Laval University Quebec Quebec Canada
| | - L Biertho
- Department of Surgery Laval University Quebec Quebec Canada
| | - S Marceau
- Department of Surgery Laval University Quebec Quebec Canada
| | - M-C Vohl
- Institute of Nutrition and Functional Foods (INAF) Laval University Quebec Quebec Canada; School of Nutrition Laval University Quebec Quebec Canada
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143
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Moyerbrailean GA, Richards AL, Kurtz D, Kalita CA, Davis GO, Harvey CT, Alazizi A, Watza D, Sorokin Y, Hauff N, Zhou X, Wen X, Pique-Regi R, Luca F. High-throughput allele-specific expression across 250 environmental conditions. Genome Res 2016; 26:1627-1638. [PMID: 27934696 PMCID: PMC5131815 DOI: 10.1101/gr.209759.116] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2016] [Accepted: 10/13/2016] [Indexed: 11/24/2022]
Abstract
Gene-by-environment (GxE) interactions determine common disease risk factors and biomedically relevant complex traits. However, quantifying how the environment modulates genetic effects on human quantitative phenotypes presents unique challenges. Environmental covariates are complex and difficult to measure and control at the organismal level, as found in GWAS and epidemiological studies. An alternative approach focuses on the cellular environment using in vitro treatments as a proxy for the organismal environment. These cellular environments simplify the organism-level environmental exposures to provide a tractable influence on subcellular phenotypes, such as gene expression. Expression quantitative trait loci (eQTL) mapping studies identified GxE interactions in response to drug treatment and pathogen exposure. However, eQTL mapping approaches are infeasible for large-scale analysis of multiple cellular environments. Recently, allele-specific expression (ASE) analysis emerged as a powerful tool to identify GxE interactions in gene expression patterns by exploiting naturally occurring environmental exposures. Here we characterized genetic effects on the transcriptional response to 50 treatments in five cell types. We discovered 1455 genes with ASE (FDR < 10%) and 215 genes with GxE interactions. We demonstrated a major role for GxE interactions in complex traits. Genes with a transcriptional response to environmental perturbations showed sevenfold higher odds of being found in GWAS. Additionally, 105 genes that indicated GxE interactions (49%) were identified by GWAS as associated with complex traits. Examples include GIPR–caffeine interaction and obesity and include LAMP3–selenium interaction and Parkinson disease. Our results demonstrate that comprehensive catalogs of GxE interactions are indispensable to thoroughly annotate genes and bridge epidemiological and genome-wide association studies.
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Affiliation(s)
- Gregory A Moyerbrailean
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA
| | - Allison L Richards
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA
| | - Daniel Kurtz
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA
| | - Cynthia A Kalita
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA
| | - Gordon O Davis
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA
| | - Chris T Harvey
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA
| | - Adnan Alazizi
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA
| | - Donovan Watza
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA
| | - Yoram Sorokin
- Department of Obstetrics and Gynecology, Wayne State University, Detroit, Michigan 48201, USA
| | - Nancy Hauff
- Department of Obstetrics and Gynecology, Wayne State University, Detroit, Michigan 48201, USA
| | - Xiang Zhou
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Xiaoquan Wen
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Roger Pique-Regi
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA.,Department of Obstetrics and Gynecology, Wayne State University, Detroit, Michigan 48201, USA
| | - Francesca Luca
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA.,Department of Obstetrics and Gynecology, Wayne State University, Detroit, Michigan 48201, USA
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144
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Overall and central obesity with insulin sensitivity and secretion in a Han Chinese population: a Mendelian randomization analysis. Int J Obes (Lond) 2016. [DOI: 10.1038/ijo.2016.155] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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145
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Dean R, Mank JE. Tissue Specificity and Sex-Specific Regulatory Variation Permit the Evolution of Sex-Biased Gene Expression. Am Nat 2016; 188:E74-84. [PMID: 27501094 DOI: 10.1086/687526] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Genetic correlations between males and females are often thought to constrain the evolution of sexual dimorphism. However, sexually dimorphic traits and the underlying sexually dimorphic gene expression patterns are often rapidly evolving. We explore this apparent paradox by measuring the genetic correlation in gene expression between males and females (Cmf) across broad evolutionary timescales, using two RNA-sequencing data sets spanning multiple populations and multiple species. We find that unbiased genes have higher Cmf than sex-biased genes, consistent with intersexual genetic correlations constraining the evolution of sexual dimorphism. However, we found that highly sex-biased genes (both male and female biased) also had higher tissue specificity, and unbiased genes had greater expression breadth, suggesting that pleiotropy may constrain the breakdown of intersexual genetic correlations. Finally, we show that genes with high Cmf showed some degree of sex-specific changes in gene expression in males and females. Together, our results suggest that genetic correlations between males and females may be less important in constraining the evolution of sex-biased gene expression than pleiotropy. Sex-specific regulatory variation and tissue specificity may resolve the paradox of widespread sex bias within a largely shared genome.
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146
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Dong SS, Guo Y, Zhu DL, Chen XF, Wu XM, Shen H, Chen XD, Tan LJ, Tian Q, Deng HW, Yang TL. Epigenomic elements analyses for promoters identify ESRRG as a new susceptibility gene for obesity-related traits. Int J Obes (Lond) 2016; 40:1170-6. [PMID: 27113491 PMCID: PMC4935547 DOI: 10.1038/ijo.2016.44] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2015] [Revised: 02/23/2016] [Accepted: 02/28/2016] [Indexed: 12/22/2022]
Abstract
OBJECTIVES With ENCODE epigenomic data and results from published genome-wide association studies (GWASs), we aimed to find regulatory signatures of obesity genes and discover novel susceptibility genes. METHODS Obesity genes were obtained from public GWAS databases and their promoters were annotated based on the regulatory element information. Significantly enriched or depleted epigenomic elements in the promoters of obesity genes were evaluated and all human genes were then prioritized according to the existence of the selected elements to predict new candidate genes. Top-ranked genes were subsequently applied to validate their associations with obesity-related traits in three independent in-house GWAS samples. RESULTS We identified RAD21 and EZH2 as over-represented, and STAT2 (signal transducer and activator of transcription 2) and IRF3 (interferon regulatory transcription factor 3) as depleted transcription factors. Histone modification of H3K9me3 and chromatin state segmentation of 'poised promoter' and 'repressed' were over-represented. All genes were prioritized and we selected the top five genes for validation at the population level. Combining results from the three GWAS samples, rs7522101 in ESRRG (estrogen-related receptor-γ) remained significantly associated with body mass index after multiple testing corrections (P=7.25 × 10(-5)). It was also associated with β-cell function (P=1.99 × 10(-3)) and fasting glucose level (P<0.05) in the meta-analyses of glucose and insulin-related traits consortium (MAGIC) data set.Cnoclusions:In summary, we identified epigenomic characteristics for obesity genes and suggested ESRRG as a novel obesity-susceptibility gene.
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Affiliation(s)
- S-S Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, People's Republic of China
| | - Y Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, People's Republic of China
| | - D-L Zhu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, People's Republic of China
| | - X-F Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, People's Republic of China
| | - X-M Wu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, People's Republic of China
| | - H Shen
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - X-D Chen
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, People's Republic of China
| | - L-J Tan
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, People's Republic of China
| | - Q Tian
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - H-W Deng
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - T-L Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Molecular Genetics, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, People's Republic of China
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147
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Gusev A, Ko A, Shi H, Bhatia G, Chung W, Penninx BWJH, Jansen R, de Geus EJC, Boomsma DI, Wright FA, Sullivan PF, Nikkola E, Alvarez M, Civelek M, Lusis AJ, Lehtimäki T, Raitoharju E, Kähönen M, Seppälä I, Raitakari OT, Kuusisto J, Laakso M, Price AL, Pajukanta P, Pasaniuc B. Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet 2016; 48:245-52. [PMID: 26854917 DOI: 10.1038/ng.3506] [Citation(s) in RCA: 1242] [Impact Index Per Article: 155.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2015] [Accepted: 01/14/2016] [Indexed: 02/07/2023]
Abstract
Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance of one or multiple proteins. Here we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated with complex traits. We leverage expression imputation from genetic data to perform a transcriptome-wide association study (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in ∼ 3,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 new genes significantly associated with obesity-related traits (BMI, lipids and height). Many of these genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits.
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Affiliation(s)
- Alexander Gusev
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Arthur Ko
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.,Molecular Biology Institute, University of California, Los Angeles, Los Angeles, California, USA
| | - Huwenbo Shi
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, California, USA
| | - Gaurav Bhatia
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Wonil Chung
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Brenda W J H Penninx
- Department of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands
| | - Rick Jansen
- Department of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, VU University, Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University, Amsterdam, the Netherlands
| | - Fred A Wright
- Bioinformatics Research Center, Department of Statistics, Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, USA
| | - Patrick F Sullivan
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA.,Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina, USA.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Elina Nikkola
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Marcus Alvarez
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Mete Civelek
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Aldons J Lusis
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.,Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and University of Tampere School of Medicine, Tampere, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories and University of Tampere School of Medicine, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Pirkanmaa Hospital District and University of Tampere School of Medicine, Tampere, Finland
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories and University of Tampere School of Medicine, Tampere, Finland
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.,Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Päivi Pajukanta
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.,Molecular Biology Institute, University of California, Los Angeles, Los Angeles, California, USA
| | - Bogdan Pasaniuc
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.,Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, California, USA.,Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
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148
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Effects of Obesity Related Genetic Variations on Visceral and Subcutaneous Fat Distribution in a Chinese Population. Sci Rep 2016; 6:20691. [PMID: 26848030 PMCID: PMC4742921 DOI: 10.1038/srep20691] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2015] [Accepted: 01/05/2016] [Indexed: 02/07/2023] Open
Abstract
Genome-wide association studies (GWAS) have uncovered numerous variants associated with body mass index (BMI), waist circumference, and waist-to-hip ratio. Our study aims to investigate how these variants are linked to fat distribution. We genotyped 56 validated variants of BMI, waist circumference, and waist-to-hip ratio in 2958 subjects from Chinese community-based populations and performed linear regression analyses to determine the association with visceral fat area (VFA) and subcutaneous fat area (SFA) imaged by magnetic resonance imaging (MRI). We found rs671 in ALDH2 exhibited the significant associations with VFA and the VFA-SFA ratio in all subjects (P = 9.64 × 10−5 and 6.54 × 10−4). rs17782313 near MC4R for VFA and rs4846567 near LYPLAL1 for SFA were found in females only (P = 2.93 × 10−4 and 0.0015), whereas rs671 in ALDH2 for VFA and the VFA-SFA ratio was restricted to males (P = 1.75 × 10−8 and 4.43 × 10−8). Given the robust association of rs671 with alcohol consumption, we next demonstrated the primary effects of rs671 on VFA and the VFA-SFA ratio were restricted to drinkers (P = 1.45 × 10−4 and 4.65 × 10−3). Our data implied that variants of MC4R and LYPLAL1 modulated body fat distribution with sexual dimorphism and that alcohol consumption may mediate the impact of the ALDH2 locus on visceral fat in a Chinese population.
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149
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Wang HJ, Hinney A, Song JY, Scherag A, Meng XR, Grallert H, Illig T, Hebebrand J, Wang Y, Ma J. Association of common variants identified by recent genome-wide association studies with obesity in Chinese children: a case-control study. BMC MEDICAL GENETICS 2016; 17:7. [PMID: 26800887 PMCID: PMC4724138 DOI: 10.1186/s12881-016-0268-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2014] [Accepted: 01/06/2016] [Indexed: 12/15/2022]
Abstract
Background Large-scale genome-wide association studies have identified multiple genetic variants that are associated with elevated body mass index (BMI) or the risk of obesity in Caucasian or Asian populations. We examined whether these variants are individually associated with obesity in Chinese children, and also assessed their cumulative effects and predictive value for obesity risk in Chinese children. Methods We genotyped 40 single nucleotide polymorphisms (SNPs) and conducted association analyses for 32/40 SNPs with an estimated minor allele frequency >1 % in 2 030 unrelated Chinese children, including 607 normal-weight, 718 overweight, and 705 obese individuals from two cross-sectional study groups. Logistic regression and linear regression under the additive model were used to examine associations, and the area under the receiver operating characteristic curve (AUCROC) was reported as prediction summary. Results We identified obesity association for 6 SNPs near SEC16B, RBJ, CDKAL1, TFAP2B, MAP2K5 and FTO (odds ratios (ORs) ranged from 1.19 to 1.41, nominal two-sided P-values < 0.05). Association (Bonferroni corrected) of rs543874 near SEC16B and rs2241423 near MAP2K5 had presumably stronger effects on obesity in Chinese children than in Caucasian populations. Their risk alleles were also associated with BMI standard deviation score (BMI-SDS) variability. We demonstrated the cumulative effects of the 32 SNPs on obesity risk (per risk allele: OR = 1.06, 95 % CI: 1.03-1.11, P = 4.84 × 10-4) and BMI-SDS (β = 0.04, 95 % CI: 0.02-0.06, P = 3.69 × 10-7). The difference in AUCROC for a model with covariates (age, age square, sex and study group) and the model including covariates and all 32 SNPs was 2.8 % (P = 0.0002). Conclusion While six SNPs were individually associated with obesity in Chinese children, the 32 common variants identified by recent GWA studies had cumulative effects and resulted in a limited increase in the AUCROC predictive value for childhood obesity. Electronic supplementary material The online version of this article (doi:10.1186/s12881-016-0268-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Hai-Jun Wang
- Institute of Child and Adolescent Health, Peking University, Beijing, China
| | - Anke Hinney
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Jie-Yun Song
- Institute of Child and Adolescent Health, Peking University, Beijing, China
| | - André Scherag
- Clinical Epidemiology, Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, Jena, 07743, Germany
| | - Xiang-Rui Meng
- Institute of Child and Adolescent Health, Peking University, Beijing, China
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research, Neuherberg, Germany
| | - Thomas Illig
- Research Unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
| | - Johannes Hebebrand
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Yan Wang
- Division of Maternal and Child Health, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Jun Ma
- Institute of Child and Adolescent Health, Peking University, Beijing, China.
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150
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Wen W, Kato N, Hwang JY, Guo X, Tabara Y, Li H, Dorajoo R, Yang X, Tsai FJ, Li S, Wu Y, Wu T, Kim S, Guo X, Liang J, Shungin D, Adair LS, Akiyama K, Allison M, Cai Q, Chang LC, Chen CH, Chen YT, Cho YS, Choi BY, Gao Y, Go MJ, Gu D, Han BG, He M, Hixson JE, Hu Y, Huang T, Isono M, Jung KJ, Kang D, Kim YJ, Kita Y, Lee J, Lee NR, Lee J, Wang Y, Liu JJ, Long J, Moon S, Nakamura Y, Nakatochi M, Ohnaka K, Rao D, Shi J, Sull JW, Tan A, Ueshima H, Wu C, Xiang YB, Yamamoto K, Yao J, Ye X, Yokota M, Zhang X, Zheng Y, Qi L, Rotter JI, Jee SH, Lin D, Mohlke KL, He J, Mo Z, Wu JY, Tai ES, Lin X, Miki T, Kim BJ, Takeuchi F, Zheng W, Shu XO. Genome-wide association studies in East Asians identify new loci for waist-hip ratio and waist circumference. Sci Rep 2016; 6:17958. [PMID: 26785701 PMCID: PMC4726286 DOI: 10.1038/srep17958] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Accepted: 10/16/2015] [Indexed: 01/19/2023] Open
Abstract
Sixty genetic loci associated with abdominal obesity, measured by waist circumference (WC) and waist-hip ratio (WHR), have been previously identified, primarily from studies conducted in European-ancestry populations. We conducted a meta-analysis of associations of abdominal obesity with approximately 2.5 million single nucleotide polymorphisms (SNPs) among 53,052 (for WC) and 48,312 (for WHR) individuals of Asian descent, and replicated 33 selected SNPs among 3,762 to 17,110 additional individuals. We identified four novel loci near the EFEMP1, ADAMTSL3 , CNPY2, and GNAS genes that were associated with WC after adjustment for body mass index (BMI); two loci near the NID2 and HLA-DRB5 genes associated with WHR after adjustment for BMI, and three loci near the CEP120, TSC22D2, and SLC22A2 genes associated with WC without adjustment for BMI. Functional enrichment analyses revealed enrichment of corticotropin-releasing hormone signaling, GNRH signaling, and/or CDK5 signaling pathways for those newly-identified loci. Our study provides additional insight on genetic contribution to abdominal obesity.
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Affiliation(s)
- Wanqing Wen
- Department of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee 37203, USA
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo 1628655, Japan
| | - Joo-Yeon Hwang
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Xingyi Guo
- Department of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee 37203, USA
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Ehime, Japan
| | - Huaixing Li
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Xiaobo Yang
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Fuu-Jen Tsai
- School of Chinese Medicine, China Medical University, Taichung, Taiwan.,Department of Medical Genetics, China Medical University Hospital, Taichung, Taiwan.,Department of Health and Nutrition Biotechnology, Asia University, Taichung, Taiwan
| | - Shengxu Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - Tangchun Wu
- Key Laboratory of Environment and Health, Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Soriul Kim
- Institute for Health Promotion, Yonsei University, Seodaemun-Gu, Seoul 120-749, Korea
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Jun Liang
- Department of Endocrinology, the Central Hospital of Xuzhou, Affiliated Hospital of Southeast University, Xuzhou, Jiangsu, China
| | - Dmitry Shungin
- Department of Clinical Sciences, Genetic &Molecular Epidemiology Unit, Lund University Diabetes Center, Skåne University Hospital, Malmö 205 02, Sweden.,Department of Public Health and Clinical Medicine, Unit of Medicine, Umeå University, Umeå 901 87, Sweden
| | - Linda S Adair
- Department of Medical Chemistry, Kurume University School of Medicine, Kurume, Fukuoka 830-0011, Japan
| | - Koichi Akiyama
- State Key Laboratory of Molecular Oncology, Cancer Institute &Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Matthew Allison
- Division of Preventive Medicine, Department of Family and Preventive Medicine, University of California, San Diego School of Medicine, San Diego, California, USA
| | - Qiuyin Cai
- Department of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee 37203, USA
| | - Li-Ching Chang
- National Center for Genome Medicine, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Chien-Hsiun Chen
- National Center for Genome Medicine, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.,School of Chinese Medicine, China Medical University, Taichung, Taiwan
| | - Yuan-Tsong Chen
- National Center for Genome Medicine, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Yoon Shin Cho
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea.,Department of Biomedical Science, Hallym University, Gangwon-do, Korea
| | - Bo Youl Choi
- Department of Preventive Medicine, College of Medicine, Hanyang University, Seoul, Korea
| | - Yutang Gao
- Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Min Jin Go
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Dongfeng Gu
- Division of Population Genetics, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bok-Ghee Han
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Meian He
- Key Laboratory of Environment and Health, Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - James E Hixson
- Human Genetics Center, University of Texas School of Public Health, Houston, Texas, USA
| | - Yanling Hu
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Medical Scientific Research Center, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Tao Huang
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts 02115, USA
| | - Masato Isono
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo 1628655, Japan
| | - Keum Ji Jung
- Institute for Health Promotion, Yonsei University, Seodaemun-Gu, Seoul 120-749, Korea
| | - Daehee Kang
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Young Jin Kim
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Yoshikuni Kita
- Department of Nursing, Tsuruga University of Nursing, Tsuruga, Japan
| | - Juyoung Lee
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Nanette R Lee
- Office of Population Studies Foundation Inc., University of San Carlos, Talamban, Cebu City, Philippines
| | - Jeannette Lee
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Yiqin Wang
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jian-Jun Liu
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore.,Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore
| | - Jirong Long
- Department of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee 37203, USA
| | - Sanghoon Moon
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Yasuyuki Nakamura
- Department of Health Science, Shiga University of Medical Science, Shiga, Japan.,Cardiovascular Epidemiology, Kyoto Women's University, Kyoto, Japan
| | - Masahiro Nakatochi
- Bioinformatics Section, Center for Advanced Medicine and Clinical Research, Nagoya University Hospital, Showa-ku, Nagoya 466-8560, Japan
| | - Keizo Ohnaka
- Department of Geriatric Medicine, Graduate School of Medical Sciences, Kyushu University, Higashi-ku, Fukuoka 812-8582, Japan
| | - Dabeeru Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jiajun Shi
- Department of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee 37203, USA
| | | | - Aihua Tan
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Department of Chemotherapy, The Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi, China
| | - Hirotsugu Ueshima
- Department of Health Science, Shiga University of Medical Science, Shiga, Japan.,Center for Epidemiologic Research in Asia, Shiga University of Medical Science, Shiga, Japan
| | - Chen Wu
- State Key Laboratory of Molecular Oncology, Cancer Institute &Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yong-Bing Xiang
- Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Ken Yamamoto
- Department of Medical Chemistry, Kurume University School of Medicine, Kurume, Fukuoka 830-0011, Japan
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Xingwang Ye
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Mitsuhiro Yokota
- Department of Genome Science, Aichi-Gakuin University, School of Dentistry, Chikusa-ku, Nagoya, 464-8651, Japan
| | - Xiaomin Zhang
- Key Laboratory of Environment and Health, Ministry of Education, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yan Zheng
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts 02115, USA
| | - Lu Qi
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts 02115, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Sun Ha Jee
- Institute for Health Promotion, Yonsei University, Seodaemun-Gu, Seoul 120-749, Korea
| | - Dongxin Lin
- State Key Laboratory of Molecular Oncology, Cancer Institute &Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | - Zengnan Mo
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.,Institute of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Jer-Yuarn Wu
- National Center for Genome Medicine, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.,School of Chinese Medicine, China Medical University, Taichung, Taiwan
| | - E Shyong Tai
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore.,Duke-National University of Singapore Graduate Medical School, Singapore
| | - Xu Lin
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Tetsuro Miki
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.,Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Ehime, Japan
| | - Bong-Jo Kim
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo 1628655, Japan
| | - Wei Zheng
- Department of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee 37203, USA
| | - Xiao-Ou Shu
- Department of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee 37203, USA
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