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Li Z, Zhao W, Shang L, Mosley TH, Kardia SLR, Smith JA, Zhou X. METRO: Multi-ancestry transcriptome-wide association studies for powerful gene-trait association detection. Am J Hum Genet 2022; 109:783-801. [PMID: 35334221 DOI: 10.1016/j.ajhg.2022.03.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 03/01/2022] [Indexed: 12/23/2022] Open
Abstract
Integrative analysis of genome-wide association studies (GWASs) and gene expression studies in the form of a transcriptome-wide association study (TWAS) has the potential to better elucidate the molecular mechanisms underlying disease etiology. Here we present a method, METRO, that can leverage gene expression data collected from multiple genetic ancestries to enhance TWASs. METRO incorporates expression prediction models constructed in different genetic ancestries through a likelihood-based inference framework, producing calibrated p values with substantially improved TWAS power. We illustrate the benefits of METRO in both simulations and applications to seven complex traits and diseases obtained from four GWASs. These GWASs include two of primarily European ancestry (n = 188,577 and 339,226) and two of primarily African ancestry (n = 42,752 and 23,827). In the real data applications, we leverage gene expression data measured on 1,032 African Americans and 801 European Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study to identify a substantially larger number of gene-trait associations as compared to existing TWAS approaches. The benefits of METRO are most prominent in applications to GWASs of African ancestry where the sample size is much smaller than GWASs of European ancestry and where a more powerful TWAS method is crucial. Among the identified associations are high-density lipoprotein-associated genes including PLTP and PPARG that are critical for maintaining lipid homeostasis and the type II diabetes-associated gene MAPT that supports microtubule-associated protein tau as a key component underlying impaired insulin secretion.
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Affiliation(s)
- Zheng Li
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lulu Shang
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Thomas H Mosley
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
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Vimaleswaran KS. GeNuIne (gene-nutrient interactions) Collaboration: towards implementing multi-ethnic population-based nutrigenetic studies of vitamin B 12 and D deficiencies and metabolic diseases. Proc Nutr Soc 2021; 80:1-11. [PMID: 34548115 DOI: 10.1017/s0029665121002822] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Gene-nutrient interactions (GeNuIne) collaboration, a large-scale collaborative project, has been initiated to investigate the impact of gene-nutrient interactions on cardiometabolic diseases using population-based studies from ethnically diverse populations. In this project, the relationship between deficiencies of vitamins B12 and D, and metabolic diseases was explored using a nutrigenetic approach. A genetic risk score (GRS) analysis was used to examine the combined effect of several genetic variations that have been shown to be associated with metabolic diseases and vitamin B12 and D deficiencies, respectively. In Sri Lankan, Indonesian and Brazilian populations, those carrying a high B12-GRS had an increased risk of metabolic diseases under the influence of dietary protein, fibre and carbohydrate intakes, respectively; however, in Asian Indians, genetically instrumented metabolic disease risk showed a significant association with low vitamin B12 status. With regards to nutrigenetic studies on vitamin D status, although high metabolic-GRS showed an interaction with dietary carbohydrate intake on vitamin D status, the study in Indonesian women demonstrated a vitamin D GRS-carbohydrate interaction on body fat percentage. In summary, these nutrigenetic studies from multiple ethnic groups have provided evidence for the influence of the dietary factors on the relationship between vitamin B12/D deficiency and metabolic outcomes. Furthermore, these studies highlight the existence of genetic heterogeneity in gene-diet interactions across ethnically diverse populations, which further implicates the significance of personalised dietary approaches for the prevention of these micronutrient deficiencies and metabolic diseases.
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Affiliation(s)
- Karani S Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, Reading, UK
- The Institute for Food, Nutrition, and Health (IFNH), University of Reading, Reading, UK
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Tchio C, Musani SK, Quarshie A, Tosini G. Association between MTNR1B polymorphisms and obesity in African American: findings from the Jackson Heart Study. BMC Med Genomics 2021; 14:136. [PMID: 34020621 PMCID: PMC8138980 DOI: 10.1186/s12920-021-00983-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 05/13/2021] [Indexed: 01/02/2023] Open
Abstract
Background Melatonin is a hormone that is secreted at night by the pineal gland. It exerts its function by binding to the MT1 and MT2 receptors, which are encoded by the MTNR1A and MTNR1B genes, respectively. Previous studies reveal that MTNR1B variants are associated with insulin secretion impairments and an increased body mass index (BMI) in individuals of European and Asian ancestries. Obesity is highly prevalent in the US and disproportionately affects African Americans. Here, we hypothesized that common single nucleotide polymorphisms (SNPs) imputed in 1000 Genomes in the MTNR1B gene are associated with adiposity in African American adult men and women and that the association is modified by insomnia. Methods We used an additive genetic model to describe the association between the adiposity traits (BMI and waist circumference) and selected MTNR1B variants in 3,029 Jackson Heart Study participants, with an average age of 55.13 ± 12.84 years, and 62% were women. We regressed the adiposity measures on the estimated allelic or genotypic dosage at every selected SNP and adjusted for age, sex, population stratification, and insomnia. Thirty common SNPs, spanning the MTNR1B gene, with a minor allele frequency ≥ 5%, a call rate ≥ 90%, a Hardy–Weinberg equilibrium p value > 10–6, were available for the analysis. Results The allele T of rs76371840 was associated with adiposity (OR = 1.47 [1.13—1.82]; PFDR-adjusted = 0.0499), and the allele A of rs8192552 showed a significant association with waist circumference (β = 0.023 ± 0.007; PFDR-adjusted = 0.0077) after correcting for multiple testing. When insomnia was included in the adiposity analysis model, the following four variants became significantly associated with adiposity: rs6483208; rs4388843; rs4601728; and rs12804291. Conclusions Our data indicate that polymorphisms in the MTNR1B gene are associated with obesity traits in African Americans. To the best of our knowledge, this is the first study to explore the effect of insomnia on the association between the circadian MTNR1B genetic variants and metabolic traits in an African American sample population. We observed that insomnia affected the association between the MTNR1B variants and adiposity.
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Affiliation(s)
- Cynthia Tchio
- Circadian Rhythms and Sleep Disorders Program, Neuroscience Institute, Morehouse School of Medicine, 720 Westview Dr. SW, Atlanta, GA, 30130, USA.,Department of Pharmacology and Toxicology, Morehouse School of Medicine, Atlanta, GA, USA
| | - Solomon K Musani
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Alexander Quarshie
- Clinical Research Center, Morehouse School of Medicine, Atlanta, GA, USA
| | - Gianluca Tosini
- Circadian Rhythms and Sleep Disorders Program, Neuroscience Institute, Morehouse School of Medicine, 720 Westview Dr. SW, Atlanta, GA, 30130, USA. .,Department of Pharmacology and Toxicology, Morehouse School of Medicine, Atlanta, GA, USA.
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Omics Approaches in Adipose Tissue and Skeletal Muscle Addressing the Role of Extracellular Matrix in Obesity and Metabolic Dysfunction. Int J Mol Sci 2021; 22:ijms22052756. [PMID: 33803198 PMCID: PMC7963192 DOI: 10.3390/ijms22052756] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 03/03/2021] [Accepted: 03/05/2021] [Indexed: 12/14/2022] Open
Abstract
Extracellular matrix (ECM) remodeling plays important roles in both white adipose tissue (WAT) and the skeletal muscle (SM) metabolism. Excessive adipocyte hypertrophy causes fibrosis, inflammation, and metabolic dysfunction in adipose tissue, as well as impaired adipogenesis. Similarly, disturbed ECM remodeling in SM has metabolic consequences such as decreased insulin sensitivity. Most of described ECM molecular alterations have been associated with DNA sequence variation, alterations in gene expression patterns, and epigenetic modifications. Among others, the most important epigenetic mechanism by which cells are able to modulate their gene expression is DNA methylation. Epigenome-Wide Association Studies (EWAS) have become a powerful approach to identify DNA methylation variation associated with biological traits in humans. Likewise, Genome-Wide Association Studies (GWAS) and gene expression microarrays have allowed the study of whole-genome genetics and transcriptomics patterns in obesity and metabolic diseases. The aim of this review is to explore the molecular basis of ECM in WAT and SM remodeling in obesity and the consequences of metabolic complications. For that purpose, we reviewed scientific literature including all omics approaches reporting genetic, epigenetic, and transcriptomic (GWAS, EWAS, and RNA-seq or cDNA arrays) ECM-related alterations in WAT and SM as associated with metabolic dysfunction and obesity.
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Abstract
As human populations spread across the world, they adapted genetically to local conditions. So too did the resident microorganism communities that everyone carries with them. However, the collective influence of the diverse and dynamic community of resident microbes on host evolution is poorly understood. The taxonomic composition of the microbiota varies among individuals and displays a range of sometimes redundant functions that modify the physicochemical environment of the host and may alter selection pressures. Here we review known human traits and genes for which the microbiota may have contributed or responded to changes in host diet, climate, or pathogen exposure. Integrating host–microbiota interactions in human adaptation could offer new approaches to improve our understanding of human health and evolution.
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Affiliation(s)
- Taichi A. Suzuki
- Department of Microbiome Science, Max Planck Institute for Developmental Biology, Tübingen, Germany
| | - Ruth E. Ley
- Department of Microbiome Science, Max Planck Institute for Developmental Biology, Tübingen, Germany
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Sun C, Kovacs P, Guiu-Jurado E. Genetics of Obesity in East Asians. Front Genet 2020; 11:575049. [PMID: 33193685 PMCID: PMC7606890 DOI: 10.3389/fgene.2020.575049] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 09/17/2020] [Indexed: 12/31/2022] Open
Abstract
Obesity has become a public health problem worldwide. Compared with Europe, people in Asia tend to suffer from type 2 diabetes with a lower body mass index (BMI). Genome-wide association studies (GWASs) have identified over 750 loci associated with obesity. Although the majority of GWAS results were conducted in individuals of European ancestry, a recent GWAS in individuals of Asian ancestry has made a significant contribution to the identification of obesity susceptibility loci. Indeed, owing to the multifactorial character of obesity with a strong environmental component, the revealed loci may have distinct contributions in different ancestral genetic backgrounds and in different environments as presented through diet and exercise among other factors. Uncovering novel, yet unrevealed genes in non-European ancestries may further contribute to explaining the missing heritability for BMI. In this review, we aimed to summarize recent advances in obesity genetics in individuals of Asian ancestry. We therefore compared proposed mechanisms underlying susceptibility loci for obesity associated with individuals of European and Asian ancestries and discussed whether known genetic variants might explain ethnic differences in obesity risk. We further acknowledged that GWAS implemented in individuals of Asian ancestries have not only validated the potential role of previously specified obesity susceptibility loci but also exposed novel ones, which have been missed in the initial genetic studies in individuals of European ancestries. Thus, multi-ethnic studies have a great potential not only to contribute to a better understanding of the complex etiology of human obesity but also potentially of ethnic differences in the prevalence of obesity, which may ultimately pave new avenues in more targeted and personalized obesity treatments.
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Affiliation(s)
| | - Peter Kovacs
- Medical Department III – Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
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Zhu S, Ye L, Bennett S, Xu H, He D, Xu J. Molecular structure and function of microfibrillar-associated proteins in skeletal and metabolic disorders and cancers. J Cell Physiol 2020; 236:41-48. [PMID: 32572962 DOI: 10.1002/jcp.29893] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 06/11/2020] [Accepted: 06/11/2020] [Indexed: 12/16/2022]
Abstract
Microfibrillar-associated proteins (MFAPs) are extracellular matrix glycoproteins, which play a role in microfibril assembly, elastinogenesis, and tissue homeostasis. MFAPs consist of five subfamily members, including MFAP1, MFAP2, MFAP3, MFAP4, and MFAP5. Among these, MFAP2 and MFAP5 are most closely related, and exhibit very limited amino acid sequence homology with MFAP1, MFAP3, and MFAP4. Gene expression profiling analysis reveals that MFAP2, MFAP5, and MFAP4 are specifically expressed in osteoblastic like cells, whereas MFAP1 and MFAP3 are more ubiquitously expressed, indicative of their diverse role in the tropism of tissues. Molecular structural analysis shows that each MFAP family member has distinct features, and functional evidence reveals discrete purposes of individual MFAPs. Animal studies indicate that MFAP2-deficient mice exhibit progressive osteopenia with elevated receptor activator of NF-κB ligand (RANKL) expression, whereas MFAP5-deficient mice are neutropenic, and MFAP4-deficient mice displayed emphysema-like pathology and the impaired formation of neointimal hyperplasia. Emerging data also suggest that MFAPs are involved in cancer progression and fat metabolism. Further understanding of tissue-specific pathophysiology of MFAPs might offer potential novel therapeutic targets for related diseases, such as skeletal and metabolic disorders, and cancers.
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Affiliation(s)
- Sipin Zhu
- Department of Orthopaedics, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.,Division of Regenerative Biology, School of Biomedical Sciences, University of Western Australia, Perth, Australia
| | - Lin Ye
- Department of Orthopaedic Surgery, Lishui Municipal Central Hospital, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
| | - Samuel Bennett
- Division of Regenerative Biology, School of Biomedical Sciences, University of Western Australia, Perth, Australia
| | - Huazi Xu
- Department of Orthopaedics, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Dengwei He
- Department of Orthopaedic Surgery, Lishui Municipal Central Hospital, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
| | - Jiake Xu
- Department of Orthopaedics, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.,Division of Regenerative Biology, School of Biomedical Sciences, University of Western Australia, Perth, Australia
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Tziastoudi M, Stefanidis I, Stravodimos K, Zintzaras E. Identification of Chromosomal Regions Linked to Diabetic Nephropathy: A Meta-Analysis of Genome-Wide Linkage Scans. Genet Test Mol Biomarkers 2019; 23:105-117. [DOI: 10.1089/gtmb.2018.0209] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Affiliation(s)
- Maria Tziastoudi
- Department of Biomathematics, Faculty of Medicine, University of Thessaly, Larissa, Greece
| | - Ioannis Stefanidis
- Department of Nephrology, Faculty of Medicine, University of Thessaly, Larissa, Greece
| | - Konstantinos Stravodimos
- 1st University Department of Urology, Laiko General Hospital, National and Kapodistrian Athens University, Athens, Greece
| | - Elias Zintzaras
- Department of Biomathematics, Faculty of Medicine, University of Thessaly, Larissa, Greece
- The Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Tufts University School of Medicine, Boston, Massachusetts
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Aldehyde Dehydrogenases Genetic Polymorphism and Obesity: From Genomics to Behavior and Health. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1193:135-154. [PMID: 31368102 DOI: 10.1007/978-981-13-6260-6_8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Obesity is multifactorial and complex. Remarkable progress has been made recently in search for polygenic obesity through genome-wide association study (GWAS), but biology of polygenic effects on obesity is largely poor. This review summarizes the available evidence and provides an overview of the links between ALDH2 variants and adiposity, which were firstly and mainly derived from studies of polygenic obesity and also indirectly investigated by using cell lines and mice. The genetic association studies have observed consistent associations of ALDH2 variants with obesity-related traits including BMI, waist circumference (WC), waist-to-hip ratio (WHR), and visceral fat accumulation. In consideration of ALDH2 variants with enzyme activity and alcohol consumption behavior in physiological mechanism studies, we proposed a model by which the physiological and behavioral consequences of alcohol consumption serve as an intermediary process between polymorphisms in ALDH2 and obesity.
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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: 96] [Impact Index Per Article: 16.0] [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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Munthali RJ, Sahibdeen V, Kagura J, Hendry LM, Norris SA, Ong KK, Day FR, Lombard Z. Genetic risk score for adult body mass index associations with childhood and adolescent weight gain in an African population. GENES AND NUTRITION 2018; 13:24. [PMID: 30123368 PMCID: PMC6090951 DOI: 10.1186/s12263-018-0613-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Accepted: 07/13/2018] [Indexed: 11/10/2022]
Abstract
Background Ninety-seven independent single nucleotide polymorphisms (SNPs) are robustly associated with adult body mass index (BMI kg/m2) in Caucasian populations. The relevance of such variants in African populations at different stages of the life course (such as childhood) is unclear. We tested whether a genetic risk score composed of the aforementioned SNPs was associated with BMI from infancy to early adulthood. We further tested whether this genetic effect was mediated by conditional weight gain at different growth periods. We used data from the Birth to Twenty Plus Cohort (Bt20+), for 971 urban South African black children from birth to 18 years. DNA was collected at 13 years old and was genotyped using the Metabochip (Illumina) array. The weighted genetic risk score (wGRS) for BMI was constructed based on 71 of the 97 previously reported SNPs. Results The cross-sectional association between the wGRS and BMI strengthened with age from 5 to 18 years. The significant associations were observed from 11 to 18 years, and peak effect sizes were observed at 13 and 14 years of age. Results from the linear mixed effects models showed significant interactions between the wGRS and age on longitudinal BMI but no such interactions were observed in sex and the wGRS. A higher wGRS was associated with an increased relative risk of belonging to the early onset obese longitudinal BMI trajectory (relative risk = 1.88; 95%CI 1.28 to 2.76) compared to belonging to a normal longitudinal BMI trajectory. Adolescent conditional relative weight gain had a suggestive mediation effect of 56% on the association between wGRS and obesity risk at 18 years. Conclusions The results suggest that genetic susceptibility to higher adult BMI can be tracked from childhood in this African population. This supports the notion that prevention of adult obesity should begin early in life. The genetic risk score combined with other non-genetic risk factors, such as BMI trajectory membership in our case, has the potential to be used to screen for early identification of individuals at increased risk of obesity and other related NCD risk factors in order to reduce the adverse health risk outcomes later. Electronic supplementary material The online version of this article (10.1186/s12263-018-0613-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Richard J Munthali
- 1Faculty of Science, School of Molecular and Cell Biology, University of the Witwatersrand, Johannesburg, South Africa.,2Sydney Brenner Institute for Molecular Bioscience (SBIMB), University of the Witwatersrand, The Mount, 9 Jubilee Road, Parktown, Johannesburg, Gauteng 2193 South Africa.,3MRC/Wits Developmental Pathways for Health Research Unit (DPHRU), University of the Witwatersrand, Johannesburg, South Africa
| | - Venesa Sahibdeen
- 2Sydney Brenner Institute for Molecular Bioscience (SBIMB), University of the Witwatersrand, The Mount, 9 Jubilee Road, Parktown, Johannesburg, Gauteng 2193 South Africa.,4Faculty of Health Sciences, Division of Human Genetics, School of Pathology, University of the Witwatersrand and National Health Laboratory Service, Johannesburg, South Africa
| | - Juliana Kagura
- 3MRC/Wits Developmental Pathways for Health Research Unit (DPHRU), University of the Witwatersrand, Johannesburg, South Africa
| | - Liesl M Hendry
- 1Faculty of Science, School of Molecular and Cell Biology, University of the Witwatersrand, Johannesburg, South Africa.,2Sydney Brenner Institute for Molecular Bioscience (SBIMB), University of the Witwatersrand, The Mount, 9 Jubilee Road, Parktown, Johannesburg, Gauteng 2193 South Africa
| | - Shane A Norris
- 3MRC/Wits Developmental Pathways for Health Research Unit (DPHRU), University of the Witwatersrand, Johannesburg, South Africa
| | - Ken K Ong
- 3MRC/Wits Developmental Pathways for Health Research Unit (DPHRU), University of the Witwatersrand, Johannesburg, South Africa.,5MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Felix R Day
- 5MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Zané Lombard
- 1Faculty of Science, School of Molecular and Cell Biology, University of the Witwatersrand, Johannesburg, South Africa.,2Sydney Brenner Institute for Molecular Bioscience (SBIMB), University of the Witwatersrand, The Mount, 9 Jubilee Road, Parktown, Johannesburg, Gauteng 2193 South Africa.,4Faculty of Health Sciences, Division of Human Genetics, School of Pathology, University of the Witwatersrand and National Health Laboratory Service, Johannesburg, South Africa
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Sahibdeen V, Crowther NJ, Soodyall H, Hendry LM, Munthali RJ, Hazelhurst S, Choudhury A, Norris SA, Ramsay M, Lombard Z. Genetic variants in SEC16B are associated with body composition in black South Africans. Nutr Diabetes 2018; 8:43. [PMID: 30026463 PMCID: PMC6053407 DOI: 10.1038/s41387-018-0050-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Revised: 05/14/2018] [Accepted: 05/23/2018] [Indexed: 12/12/2022] Open
Abstract
Objective The latest genome-wide association studies of obesity-related traits have identified several genetic loci contributing to body composition (BC). These findings have not been robustly replicated in African populations, therefore, this study aimed to assess whether European BC-associated gene loci played a similar role in a South African black population. Methods A replication and fine-mapping study was performed in participants from the Birth to Twenty cohort (N = 1,926) using the Metabochip. Measurements included body mass index (BMI), waist and hip circumference, waist-to-hip ratio (WHR), total fat mass, total lean mass and percentage fat mass (PFM). Results SNPs in several gene loci, including SEC16B (Padj < 9.48 × 10−7), NEGR1 (Padj < 1.64 × 10−6), FTO (Padj < 2.91 × 10−5), TMEM18 (Padj < 2.27 × 10−5), and WARS2(Padj < 3.25 × 10−5) were similarly associated (albeit not at array-wide signficance (P ≤ 6.7 × 10−7) with various phenotypes including fat mass, PFM, WHR linked to BC in this African cohort, however the associations were driven by different sentinel SNPs. More importantly, DXA-derived BC measures revealed stronger genetic associations than simple anthropometric measures. Association signals generated in this study were shared by European and African populations, as well as unique to this African cohort. Moreover, sophisticated estimates like DXA measures enabled an enhanced characterisation of genetic associations for BC traits. Conclusion Results from this study suggest that in-depth genomic studies in larger African cohorts may reveal novel SNPs for body composition and adiposity, which will provide greater insight into the aetiology of obesity.
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Affiliation(s)
- Venesa Sahibdeen
- Division of Human Genetics, School of Pathology, Faculty of Health Sciences, National Health Laboratory Service & University of the Witwatersrand, Johannesburg, South Africa. .,Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
| | - Nigel J Crowther
- Department of Chemical Pathology, School of Pathology, Faculty of Health Sciences, National Health Laboratory Service & University of the Witwatersrand, Johannesburg, South Africa
| | - Himla Soodyall
- Division of Human Genetics, School of Pathology, Faculty of Health Sciences, National Health Laboratory Service & University of the Witwatersrand, Johannesburg, South Africa
| | - Liesl M Hendry
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,School of Molecular and Cell Biology, Faculty of Science, University of the Witwatersrand, Johannesburg, South Africa
| | - Richard J Munthali
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,School of Molecular and Cell Biology, Faculty of Science, University of the Witwatersrand, Johannesburg, South Africa.,MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Shane A Norris
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Michèle Ramsay
- Division of Human Genetics, School of Pathology, Faculty of Health Sciences, National Health Laboratory Service & University of the Witwatersrand, Johannesburg, South Africa.,Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Zané Lombard
- Division of Human Genetics, School of Pathology, Faculty of Health Sciences, National Health Laboratory Service & University of the Witwatersrand, Johannesburg, South Africa.,Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,School of Molecular and Cell Biology, Faculty of Science, University of the Witwatersrand, Johannesburg, South Africa
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Weissbrod O, Rothschild D, Barkan E, Segal E. Host genetics and microbiome associations through the lens of genome wide association studies. Curr Opin Microbiol 2018; 44:9-19. [PMID: 29909175 DOI: 10.1016/j.mib.2018.05.003] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Revised: 03/15/2018] [Accepted: 05/25/2018] [Indexed: 12/22/2022]
Abstract
Recent studies indicate that the gut microbiome is partially heritable, motivating the need to investigate microbiome-host genome associations via microbial genome-wide association studies (mGWAS). Existing mGWAS demonstrate that microbiome-host genotype associations are typically weak and are spread across multiple variants, similar to associations often observed in genome-wide association studies (GWAS) of complex traits. Here we reconsider mGWAS by viewing them through the lens of GWAS, and demonstrate that there are striking similarities between the challenges and pitfalls faced by the two study designs. We further advocate the mGWAS community to adopt three key lessons learned over the history of GWAS: firstly, adopting uniform data and reporting formats to facilitate replication and meta-analysis efforts; secondly, enforcing stringent statistical criteria to reduce the number of false positive findings; and thirdly, considering the microbiome and the host genome as distinct entities, rather than studying different taxa and single nucleotide polymorphism (SNPs) separately. Finally, we anticipate that mGWAS sample sizes will have to increase by orders of magnitude to reproducibly associate the host genome with the gut microbiome.
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Affiliation(s)
- Omer Weissbrod
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Daphna Rothschild
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Elad Barkan
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Eran Segal
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel; Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, Israel.
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14
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Verbrugge SAJ, Schönfelder M, Becker L, Yaghoob Nezhad F, Hrabě de Angelis M, Wackerhage H. Genes Whose Gain or Loss-Of-Function Increases Skeletal Muscle Mass in Mice: A Systematic Literature Review. Front Physiol 2018; 9:553. [PMID: 29910734 PMCID: PMC5992403 DOI: 10.3389/fphys.2018.00553] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Accepted: 04/30/2018] [Indexed: 12/20/2022] Open
Abstract
Skeletal muscle mass differs greatly in mice and humans and this is partially inherited. To identify muscle hypertrophy candidate genes we conducted a systematic review to identify genes whose experimental loss or gain-of-function results in significant skeletal muscle hypertrophy in mice. We found 47 genes that meet our search criteria and cause muscle hypertrophy after gene manipulation. They are from high to small effect size: Ski, Fst, Acvr2b, Akt1, Mstn, Klf10, Rheb, Igf1, Pappa, Ppard, Ikbkb, Fstl3, Atgr1a, Ucn3, Mcu, Junb, Ncor1, Gprasp1, Grb10, Mmp9, Dgkz, Ppargc1a (specifically the Ppargc1a4 isoform), Smad4, Ltbp4, Bmpr1a, Crtc2, Xiap, Dgat1, Thra, Adrb2, Asb15, Cast, Eif2b5, Bdkrb2, Tpt1, Nr3c1, Nr4a1, Gnas, Pld1, Crym, Camkk1, Yap1, Inhba, Tp53inp2, Inhbb, Nol3, Esr1. Knock out, knock down, overexpression or a higher activity of these genes causes overall muscle hypertrophy as measured by an increased muscle weight or cross sectional area. The mean effect sizes range from 5 to 345% depending on the manipulated gene as well as the muscle size variable and muscle investigated. Bioinformatical analyses reveal that Asb15, Klf10, Tpt1 are most highly expressed hypertrophy genes in human skeletal muscle when compared to other tissues. Many of the muscle hypertrophy-regulating genes are involved in transcription and ubiquitination. Especially genes belonging to three signaling pathways are able to induce hypertrophy: (a) Igf1-Akt-mTOR pathway, (b) myostatin-Smad signaling, and (c) the angiotensin-bradykinin signaling pathway. The expression of several muscle hypertrophy-inducing genes and the phosphorylation of their protein products changes after human resistance and high intensity exercise, in maximally stimulated mouse muscle or in overloaded mouse plantaris.
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Affiliation(s)
- Sander A. J. Verbrugge
- Exercise Biology Group, Faculty of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Martin Schönfelder
- Exercise Biology Group, Faculty of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Lore Becker
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Fakhreddin Yaghoob Nezhad
- Exercise Biology Group, Faculty of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Martin Hrabě de Angelis
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany
- Chair of Experimental Genetics, School of Life Science Weihenstephan, Technische Universität München, Freising, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Henning Wackerhage
- Exercise Biology Group, Faculty of Sport and Health Sciences, Technical University of Munich, Munich, Germany
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15
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Song QY, Meng XR, Hinney A, Song JY, Huang T, Ma J, Wang HJ. Waist-hip ratio related genetic loci are associated with risk of impaired fasting glucose in Chinese children: a case control study. Nutr Metab (Lond) 2018; 15:34. [PMID: 29755575 PMCID: PMC5934898 DOI: 10.1186/s12986-018-0270-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Accepted: 04/18/2018] [Indexed: 01/13/2023] Open
Abstract
Background The meta-analyses of genome-wide association studies identified several waist-hip ratio (WHR) related loci in individuals of European ancestry. Since the pattern of fat distribution and the relationship between fat distribution and glucose metabolism disturbance in Chinese are different from those in Europeans, the present study aimed to explore the individual and cumulative effects of WHR-related loci on glycemic phenotypes in Chinese children. Methods A total of 2030 children were recruited from two independent studies. Eleven single nucleotide polymorphisms (SNPs) were selected and genotyped using matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS). Logistic regression and linear regression model were used to examine the association of 11 SNPs and genetic risk score (GRS) with impaired fasting glucose (IFG) and fasting plasma glucose (FPG), respectively. Results Three SNPs (rs6795735, rs984222 and rs1011731) were nominally associated with IFG (all P < 0.05). Each WHR-increasing (C) allele of rs6795735 (ADAMTS9) was associated with a 40.1% increased risk of IFG (OR = 1.401, 95% CI = 1.131–1.735, P = 0.002), which remained significant after Bonferroni correction. We observed no association of both weighted and unweighted GRS with FPG and IFG (all P > 0.05). Conclusions We identified individual effects of rs6795735 (ADAMTS9), rs984222 (TBX15-WARS2), and rs1011731 (DNM3-PIGC) on glycemic phenotypes in Chinese children for the first time. The study suggests that genetic predisposition to central obesity is associated with impaired fasting glucose, providing more evidence for the pathogenesis of diabetes. Electronic supplementary material The online version of this article (10.1186/s12986-018-0270-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Qi-Ying Song
- 1Department of Maternal and Child Health, School of Public Health, Peking University, No.38 Xueyuan Road, Haidian District, Beijing, 100191 China
| | - Xiang-Rui Meng
- 2Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, 100191 China.,3Center for Global Health Research, Usher Institute of Population and Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland UK
| | - Anke Hinney
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Jie-Yun Song
- 2Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, 100191 China
| | - Tao Huang
- 5Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191 China
| | - Jun Ma
- 2Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, 100191 China
| | - Hai-Jun Wang
- 1Department of Maternal and Child Health, School of Public Health, Peking University, No.38 Xueyuan Road, Haidian District, Beijing, 100191 China
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16
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Hussain MRM, Hoessli DC, Fang M. N-acetylgalactosaminyltransferases in cancer. Oncotarget 2018; 7:54067-54081. [PMID: 27322213 PMCID: PMC5288242 DOI: 10.18632/oncotarget.10042] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2016] [Accepted: 05/30/2016] [Indexed: 12/11/2022] Open
Abstract
Aberrant mucin-type O-glycosylation by glycosyltransferases is a well-described hallmark of many cancers and is also associated with additional non-cancerous developmental and metabolic disorders. The current review focuses on N-acetylgalactosaminyltransferase genes (GALNTs) and proteins (GalNAcTs) to illustrate their importance in cancer biology. Aberrant O-glycosylation by GalNAcTs activates a wide range of proteins that carry out interactions of sessile and motile cells affecting organogenesis, responses to agonists and stimulating hyperproliferation and metastatisation of neoplastic cells. As genome-wide analyses have provided abundant clues regarding under- or over-expressed genes that characterize different types of cancers, GALNTs and their transferase products have attracted attention by being unexpected actors in neoplastic contexts. We intend to review the current knowledge on GALNTs and their encoded transferases in cancer and suggest what could be the significance of such information in cancer pathogenesis and management.
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Affiliation(s)
- Muhammad Ramzan Manwar Hussain
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Daniel C Hoessli
- Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Pakistan
| | - Min Fang
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
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17
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Stevenson NL, Bergen DJM, Skinner REH, Kague E, Martin-Silverstone E, Robson Brown KA, Hammond CL, Stephens DJ. Giantin-knockout models reveal a feedback loop between Golgi function and glycosyltransferase expression. J Cell Sci 2017; 130:4132-4143. [PMID: 29093022 PMCID: PMC5769581 DOI: 10.1242/jcs.212308] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 10/21/2017] [Indexed: 12/14/2022] Open
Abstract
The Golgi is the cellular hub for complex glycosylation, controlling accurate processing of complex proteoglycans, receptors, ligands and glycolipids. Its structure and organisation are dependent on golgins, which tether cisternal membranes and incoming transport vesicles. Here, we show that knockout of the largest golgin, giantin, leads to substantial changes in gene expression but only limited effects on Golgi structure. Notably, 22 Golgi-resident glycosyltransferases, but not glycan-processing enzymes or the ER glycosylation machinery, are differentially expressed following giantin ablation. This includes near-complete loss of function of GALNT3 in both mammalian cell and zebrafish models. Giantin-knockout zebrafish exhibit hyperostosis and ectopic calcium deposits, recapitulating phenotypes of hyperphosphatemic familial tumoral calcinosis, a disease caused by mutations in GALNT3. These data reveal a new feature of Golgi homeostasis: the ability to regulate glycosyltransferase expression to generate a functional proteoglycome.
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Affiliation(s)
- Nicola L Stevenson
- Cell Biology Laboratories, School of Biochemistry, University of Bristol, Biomedical Sciences Building, University Walk, Bristol BS8 1TD, UK
| | - Dylan J M Bergen
- Cell Biology Laboratories, School of Biochemistry, University of Bristol, Biomedical Sciences Building, University Walk, Bristol BS8 1TD, UK
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Biomedical Sciences Building, University Walk, Bristol BS8 1TD, UK
| | - Roderick E H Skinner
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Biomedical Sciences Building, University Walk, Bristol BS8 1TD, UK
| | - Erika Kague
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Biomedical Sciences Building, University Walk, Bristol BS8 1TD, UK
| | - Elizabeth Martin-Silverstone
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Biomedical Sciences Building, University Walk, Bristol BS8 1TD, UK
| | - Kate A Robson Brown
- Computed Tomography Laboratory, School of Arts, University of Bristol, 43 Woodland Road, Bristol BS8 1UU, UK
| | - Chrissy L Hammond
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Biomedical Sciences Building, University Walk, Bristol BS8 1TD, UK
| | - David J Stephens
- Cell Biology Laboratories, School of Biochemistry, University of Bristol, Biomedical Sciences Building, University Walk, Bristol BS8 1TD, UK
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18
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Goodrich JK, Davenport ER, Clark AG, Ley RE. The Relationship Between the Human Genome and Microbiome Comes into View. Annu Rev Genet 2017; 51:413-433. [PMID: 28934590 PMCID: PMC5744868 DOI: 10.1146/annurev-genet-110711-155532] [Citation(s) in RCA: 173] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The body's microbiome, composed of microbial cells that number in the trillions, is involved in human health and disease in ways that are just starting to emerge. The microbiome is assembled at birth, develops with its host, and is greatly influenced by environmental factors such as diet and other exposures. Recently, a role for human genetic variation has emerged as also influential in accounting for interpersonal differences in microbiomes. Thus, human genes may influence health directly or by promoting a beneficial microbiome. Studies of the heritability of gut microbiotas reveal a subset of microbes whose abundances are partly genetically determined by the host. However, the use of genome-wide association studies (GWASs) to identify human genetic variants associated with microbiome phenotypes has proven challenging. Studies to date are small by GWAS standards, and cross-study comparisons are hampered by differences in analytical approaches. Nevertheless, associations between microbes or microbial genes and human genes have emerged that are consistent between human populations. Most notably, higher levels of beneficial gut bacteria called Bifidobacteria are associated with the human lactase nonpersister genotype, which typically confers lactose intolerance, in several different human populations. It is time for the microbiome to be incorporated into studies that quantify interactions among genotype, environment, and the microbiome in order to predict human disease susceptibility.
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Affiliation(s)
- Julia K Goodrich
- Department of Microbiome Science, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany;
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA
| | - Emily R Davenport
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA
| | - Andrew G Clark
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA
| | - Ruth E Ley
- Department of Microbiome Science, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany;
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853, USA
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19
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Abstract
Taxonomic and functional changes to the composition of the gut microbiome have been implicated in multiple human diseases. Recent microbiome genome-wide association studies reveal that variants in many human genes involved in immunity and gut architecture are associated with an altered composition of the gut microbiome. Although many factors can affect the microbial organisms residing in the gut, a number of recent findings support the hypothesis that certain host genetic variants predispose an individual towards microbiome dysbiosis. This condition, in which the normal microbiome population structure is disturbed, is a key feature in disorders of metabolism and immunity.
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Affiliation(s)
- Andrew Brantley Hall
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 02142, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA
| | - Andrew C Tolonen
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 02142, USA
| | - Ramnik J Xavier
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 02142, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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20
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Rotimi CN, Bentley AR, Doumatey AP, Chen G, Shriner D, Adeyemo A. The genomic landscape of African populations in health and disease. Hum Mol Genet 2017; 26:R225-R236. [PMID: 28977439 PMCID: PMC6075021 DOI: 10.1093/hmg/ddx253] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Revised: 06/19/2017] [Accepted: 06/29/2017] [Indexed: 12/12/2022] Open
Abstract
A deeper appreciation of the complex architecture of African genomes is critical to the global effort to understand human history, biology and differential distribution of disease by geography and ancestry. Here, we report on how the growing engagement of African populations in genome science is providing new insights into the forces that shaped human genomes before and after the Out-of-Africa migrations. As a result of this human evolutionary history, African ancestry populations have the greatest genomic diversity in the world, and this diversity has important ramifications for genomic research. In the case of pharmacogenomics, for instance, variants of consequence are not limited to those identified in other populations, and diversity within African ancestry populations precludes summarizing risk across different African ethnic groups. Exposure of Africans to fatal pathogens, such as Plasmodium falciparum, Lassa Virus and Trypanosoma brucei rhodesiense, has resulted in elevated frequencies of alleles conferring survival advantages for infectious diseases, but that are maladaptive in modern-day environments. Illustrating with cardiometabolic traits, we show that while genomic research in African ancestry populations is still in early stages, there are already many examples of novel and African ancestry-specific disease loci that have been discovered. Furthermore, the shorter haplotypes in African genomes have facilitated fine-mapping of loci discovered in other human ancestry populations. Given the insights already gained from the interrogation of African genomes, it is imperative to continue and increase our efforts to describe genomic risk in and across African ancestry populations.
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Affiliation(s)
- Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Amy R. Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Ayo P. Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD 20892, USA
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21
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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: 70] [Impact Index Per Article: 10.0] [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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Graff M, Scott RA, Justice AE, Young KL, Feitosa MF, Barata L, Winkler TW, Chu AY, Mahajan A, Hadley D, Xue L, Workalemahu T, Heard-Costa NL, den Hoed M, Ahluwalia TS, Qi Q, Ngwa JS, Renström F, Quaye L, Eicher JD, Hayes JE, Cornelis M, Kutalik Z, Lim E, Luan J, Huffman JE, Zhang W, Zhao W, Griffin PJ, Haller T, Ahmad S, Marques-Vidal PM, Bien S, Yengo L, Teumer A, Smith AV, Kumari M, Harder MN, Justesen JM, Kleber ME, Hollensted M, Lohman K, Rivera NV, Whitfield JB, Zhao JH, Stringham HM, Lyytikäinen LP, Huppertz C, Willemsen G, Peyrot WJ, Wu Y, Kristiansson K, Demirkan A, Fornage M, Hassinen M, Bielak LF, Cadby G, Tanaka T, Mägi R, van der Most PJ, Jackson AU, Bragg-Gresham JL, Vitart V, Marten J, Navarro P, Bellis C, Pasko D, Johansson Å, Snitker S, Cheng YC, Eriksson J, Lim U, Aadahl M, Adair LS, Amin N, Balkau B, Auvinen J, Beilby J, Bergman RN, Bergmann S, Bertoni AG, Blangero J, Bonnefond A, Bonnycastle LL, Borja JB, Brage S, Busonero F, Buyske S, Campbell H, Chines PS, Collins FS, Corre T, Smith GD, Delgado GE, Dueker N, Dörr M, Ebeling T, Eiriksdottir G, Esko T, Faul JD, Fu M, Færch K, Gieger C, Gläser S, Gong J, Gordon-Larsen P, Grallert H, Grammer TB, Grarup N, van Grootheest G, Harald K, Hastie ND, Havulinna AS, Hernandez D, Hindorff L, Hocking LJ, Holmens OL, Holzapfel C, Hottenga JJ, Huang J, Huang T, Hui J, Huth C, Hutri-Kähönen N, James AL, Jansson JO, Jhun MA, Juonala M, Kinnunen L, Koistinen HA, Kolcic I, Komulainen P, Kuusisto J, Kvaløy K, Kähönen M, Lakka TA, Launer LJ, Lehne B, Lindgren CM, Lorentzon M, Luben R, Marre M, Milaneschi Y, Monda KL, Montgomery GW, De Moor MHM, Mulas A, Müller-Nurasyid M, Musk AW, Männikkö R, Männistö S, Narisu N, Nauck M, Nettleton JA, Nolte IM, Oldehinkel AJ, Olden M, Ong KK, Padmanabhan S, Paternoster L, Perez J, Perola M, Peters A, Peters U, Peyser PA, Prokopenko I, Puolijoki H, Raitakari OT, Rankinen T, Rasmussen-Torvik LJ, Rawal R, Ridker PM, Rose LM, Rudan I, Sarti C, Sarzynski MA, Savonen K, Scott WR, Sanna S, Shuldiner AR, Sidney S, Silbernagel G, Smith BH, Smith JA, Snieder H, Stančáková A, Sternfeld B, Swift AJ, Tammelin T, Tan ST, Thorand B, Thuillier D, Vandenput L, Vestergaard H, van Vliet-Ostaptchouk JV, Vohl MC, Völker U, Waeber G, Walker M, Wild S, Wong A, Wright AF, Zillikens MC, Zubair N, Haiman CA, Lemarchand L, Gyllensten U, Ohlsson C, Hofman A, Rivadeneira F, Uitterlinden AG, Pérusse L, Wilson JF, Hayward C, Polasek O, Cucca F, Hveem K, Hartman CA, Tönjes A, Bandinelli S, Palmer LJ, Kardia SLR, Rauramaa R, Sørensen TIA, Tuomilehto J, Salomaa V, Penninx BWJH, de Geus EJC, Boomsma DI, Lehtimäki T, Mangino M, Laakso M, Bouchard C, Martin NG, Kuh D, Liu Y, Linneberg A, März W, Strauch K, Kivimäki M, Harris TB, Gudnason V, Völzke H, Qi L, Järvelin MR, Chambers JC, Kooner JS, Froguel P, Kooperberg C, Vollenweider P, Hallmans G, Hansen T, Pedersen O, Metspalu A, Wareham NJ, Langenberg C, Weir DR, Porteous DJ, Boerwinkle E, Chasman DI, Abecasis GR, Barroso I, McCarthy MI, Frayling TM, O’Connell JR, van Duijn CM, Boehnke M, Heid IM, Mohlke KL, Strachan DP, Fox CS, Liu CT, Hirschhorn JN, Klein RJ, Johnson AD, Borecki IB, Franks PW, North KE, Cupples LA, Loos RJF, Kilpeläinen TO. Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults. PLoS Genet 2017; 13:e1006528. [PMID: 28448500 PMCID: PMC5407576 DOI: 10.1371/journal.pgen.1006528] [Citation(s) in RCA: 119] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 12/07/2016] [Indexed: 11/23/2022] Open
Abstract
Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
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Affiliation(s)
- Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Robert A. Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Anne E. Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kristin L. Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Mary F. Feitosa
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Llilda Barata
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Thomas W. Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Audrey Y. Chu
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - David Hadley
- Division of Population Health Sciences and Education, St. George's, University of London, London, United Kingdom
| | - Luting Xue
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Tsegaselassie Workalemahu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Nancy L. Heard-Costa
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, United States of America
| | - Marcel den Hoed
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Tarunveer S. Ahluwalia
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center, Gentofte, Denmark
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Julius S. Ngwa
- Howard University, Department of Internal Medicine, Washington DC, United States of America
| | - Frida Renström
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
- Department of Biobank Research, Umeå University, Umeå, Sweden
| | - Lydia Quaye
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - John D. Eicher
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, The Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - James E. Hayes
- Cell and Developmental Biology Graduate Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, New York, United States of America
- Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Marilyn Cornelis
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Zoltan Kutalik
- Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Elise Lim
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Jian’an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Jennifer E. Huffman
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Cardiology, Ealing Hospital HNS Trust, Middlesex, United Kingdom
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Paula J. Griffin
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Toomas Haller
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Shafqat Ahmad
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
| | - Pedro M. Marques-Vidal
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Stephanie Bien
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Loic Yengo
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Albert Vernon Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Meena Kumari
- ISER, University of Essex, Colchester, Essex, United Kingdom
| | - Marie Neergaard Harder
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Johanne Marie Justesen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marcus E. Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Nutrition, Friedrich Schiller University Jena, Jena, Germany
| | - Mette Hollensted
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kurt Lohman
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Natalia V. Rivera
- Karolinska Institutet, Respiratory Unit, Department of Medicine Solna, Stockholm, Sweden
| | - John B. Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jing Hua Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Heather M. Stringham
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere, Finland
| | - Charlotte Huppertz
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
- Department of Public and Occupational Health, VU University Medical Center, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
| | - Wouter J. Peyrot
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Kati Kristiansson
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Ayse Demirkan
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
- Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Maija Hassinen
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Gemma Cadby
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Western Australia, Australia
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, Maryland, United States of America
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Peter J. van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Anne U. Jackson
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Jennifer L. Bragg-Gresham
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jonathan Marten
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Claire Bellis
- Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research of Singapore, Singapore
- Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Dorota Pasko
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Søren Snitker
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Yu-Ching Cheng
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Veterans Affairs Maryland Health Care System, University of Maryland, Baltimore, Maryland, United States of America
| | - Joel Eriksson
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Unhee Lim
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Mette Aadahl
- Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Linda S. Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Beverley Balkau
- INSERM U-1018, CESP, Renal and Cardiovascular Epidemiology, UVSQ-UPS, Villejuif, France
| | - Juha Auvinen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - John Beilby
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- PathWest Laboratory Medicine of WA, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Pathology and Laboratory Medicine, The University of Western Australia, Crawley, Western Australia, Australia
| | - Richard N. Bergman
- Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Sven Bergmann
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - Alain G. Bertoni
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - John Blangero
- Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Amélie Bonnefond
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
| | - Lori L. Bonnycastle
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Judith B. Borja
- USC-Office of Population Studies Foundation, Inc., University of San Carlos, Cebu City, Philippines
- Department of Nutrition and Dietetics, University of San Carlos, Cebu City, Philippines
| | - Søren Brage
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Fabio Busonero
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
| | - Steve 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
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
| | - Peter S. Chines
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Francis S. Collins
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Tanguy Corre
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - George Davey Smith
- MRC Integrative Epidemiology Unit & School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Graciela E. Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Nicole Dueker
- University of Maryland School of Medicine, Department of Epidemiology & Public Health, Baltimore, Maryland, United States of America
| | - Marcus Dörr
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Tapani Ebeling
- Department of Medicine, Oulu University Hospital, Oulu, Finland
- Institute of Clinical Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
| | | | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Division of Endocrinology, Boston Children's Hospital, Boston, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Mao Fu
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | | | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Sven Gläser
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Jian Gong
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Penny Gordon-Larsen
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Tanja B. Grammer
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Gerard van Grootheest
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Kennet Harald
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Nicholas D. Hastie
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Aki S. Havulinna
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Dena Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, Maryland, United States of America
| | - Lucia Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Lynne J. Hocking
- Musculoskeletal Research Programme, Division of Applied Medicine, University of Aberdeen, Foresterhill, Aberdeen, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Christina Holzapfel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Nutritional Medicine, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- NCA Institute, VU University & VU Medical Center, Amsterdam, The Netherlands
| | - Jie Huang
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Tao Huang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Jennie Hui
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- PathWest Laboratory Medicine of WA, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Population Health, The University of Western Australia, Crawley, Western Australia, Australia
| | - Cornelia Huth
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Nina Hutri-Kähönen
- Department of Pediatrics, Tampere University Hospital, Tampere, Finland
- Department of Pediatrics, University of Tampere School of Medicine, Tampere, Finland
| | - Alan L. James
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia
| | - John-Olov Jansson
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Min A. Jhun
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Markus Juonala
- Department of Medicine, University of Turku, Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
| | - Leena Kinnunen
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Heikki A. Koistinen
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Department of Medicine and Abdominal Center: Endocrinology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Ivana Kolcic
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | | | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kirsti Kvaløy
- HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
- Department of Clinical Physiology, University of Tampere School of Medicine, Tampere, Finland
| | - Timo A. Lakka
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, Physiology, University of Eastern Finland, Kuopio Campus, Finland
| | - Lenore J. Launer
- Neuroepidemiology Section, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Cecilia M. Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- The Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Mattias Lorentzon
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Geriatric Medicine, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Robert Luben
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Michel Marre
- INSERM U-1138, Équipe 2: Pathophysiology and Therapeutics of Vascular and Renal diseases Related to Diabetes, Centre de Recherche des Cordeliers, Paris, France
- Department of Endocrinology, Diabetology, Nutrition, and Metabolic Diseases, Bichat Claude Bernard Hospital, Paris, France
| | - Yuri Milaneschi
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Keri L. Monda
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Center for Observational Research, Amgen Inc., Thousand Oaks, California, United States of America
| | - Grant W. Montgomery
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Marleen H. M. De Moor
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
- Section of Clinical Child and Family Studies, Department of Educational and Family Studies, Vrije Universiteit, Amsterdam, The Netherlands
| | - Antonella Mulas
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
- Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Department of Medicine I, Ludwig-Maximilians-Universität, Munich, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - A. W. Musk
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- School of Population Health, The University of Western Australia, Crawley, Western Australia, Australia
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
| | - Reija Männikkö
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Satu Männistö
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Narisu Narisu
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Jennifer A. Nettleton
- Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Ilja M. Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Albertine J. Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Matthias Olden
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Ken K. Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Sandosh Padmanabhan
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Institute of Cardiovascular and Medical Sciences, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, United Kingdom
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit & School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Jeremiah Perez
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Markus Perola
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- University of Tartu, Estonian Genome Centre, Tartu, Estonia
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Inga Prokopenko
- Genomics of Common Disease, Imperial College London, London, United Kingdom
| | | | - 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
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Rajesh Rawal
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Lynda M. Rose
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
| | - Cinzia Sarti
- Social Services and Health Care Department, City of Helsinki, Helsinki, Finland
| | - Mark A. Sarzynski
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Kai Savonen
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - William R. Scott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Serena Sanna
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
| | - Alan R. Shuldiner
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Veterans Affairs Maryland Health Care System, University of Maryland, Baltimore, Maryland, United States of America
| | - Steve Sidney
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Günther Silbernagel
- Division of Angiology, Department of Internal Medicine, Medical University Graz, Austria
| | - Blair H. Smith
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- School of Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, Scotland
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Alena Stančáková
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Barbara Sternfeld
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Amy J. Swift
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Tuija Tammelin
- LIKES Research Center for Sport and Health Sciences, Jyväskylä, Finland
| | - Sian-Tsung Tan
- National Heart and Lung Institute, Imperial College London, United Kingdom
| | - Barbara Thorand
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Dorothée Thuillier
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
| | - Liesbeth Vandenput
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Vestergaard
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center, Gentofte, Denmark
| | - Jana V. van Vliet-Ostaptchouk
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Marie-Claude Vohl
- Institute of Nutrition and Functional Foods, Quebec, Canada
- School of Nutrition, Laval University, Quebec, Canada
| | - Uwe Völker
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Germany
| | - Gérard Waeber
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Mark Walker
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Sarah Wild
- Centre for Population Health Sciences, Usher Institute for Population Health Sciences and Informatics, Teviot Place, Edinburgh, Scotland
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Alan F. Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | | | - Niha Zubair
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Christopher A. Haiman
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Loic Lemarchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Claes Ohlsson
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Leiden University Medical Center, Leiden, The Netherlands
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Leiden University Medical Center, Leiden, The Netherlands
| | - André G. Uitterlinden
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Louis Pérusse
- Institute of Nutrition and Functional Foods, Quebec, Canada
- Department of Kinesiology, Laval University, Quebec, Canada
| | - James F. Wilson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Ozren Polasek
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
- Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy
| | - Kristian Hveem
- HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway
| | - Catharina A. Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Anke Tönjes
- University of Leipzig, Medical Department, Leipzig, Germany
| | | | - Lyle J. Palmer
- School of Public Health, University of Adelaide, Adelaide, South Australia, Australia
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Rainer Rauramaa
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Thorkild I. A. Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- MRC Integrative Epidemiology Unit & School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
- Department of Clinical Epidemiology, Bispebjerg and Frederiksberg Hospitals, The Capital Region, Copenhagen, Denmark
| | - Jaakko Tuomilehto
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Centre for Vascular Prevention, Danube-University Krems, Krems, Austria
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Veikko Salomaa
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Brenda W. J. H. Penninx
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Eco J. C. de Geus
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- NCA Institute, VU University & VU Medical Center, Amsterdam, The Netherlands
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere, Finland
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
- National Institute for Health Research Biomedical Research Centre at Guy's and St. Thomas' Foundation Trust, London, United Kingdom
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Allan Linneberg
- Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark
- Department of Clinical Experimental Research, Rigshospitalet, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Synlab Academy, Synlab Services LLC, Mannheim, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Tamara B. Harris
- Laboratory of Epidemiology and Population Science, National Institute on Aging, Bethesda, Maryland, United States of America
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Lu Qi
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- MRC-PHE Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - John C. Chambers
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Cardiology, Ealing Hospital HNS Trust, Middlesex, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Jaspal S. Kooner
- Department of Cardiology, Ealing Hospital HNS Trust, Middlesex, United Kingdom
- National Heart and Lung Institute, Imperial College London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Philippe Froguel
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
- Hammersmith Hospital, London, United Kingdom
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Peter Vollenweider
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Göran Hallmans
- Department of Biobank Research, Umeå University, Umeå, Sweden
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
| | - David J. Porteous
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Eric Boerwinkle
- Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | | | | | | | - Gonçalo R. Abecasis
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Inês Barroso
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- NIHR Cambridge Biomedical Research Centre, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, United Kingdom
- The University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, United Kingdom
| | - Mark I. McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, United Kingdom
- Oxford NIHR Biomedical Research Centre, Oxford, United Kingdom
| | - Timothy M. Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Jeffrey R. O’Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Leiden University Medical Center, Leiden, The Netherlands
- Center of Medical Systems Biology, Leiden, The Netherlands
| | - Michael Boehnke
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Iris M. Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - David P. Strachan
- Population Health Research Institute, St. George's University of London, London, United Kingdom
| | - Caroline S. Fox
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, The Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Joel N. Hirschhorn
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America
- Divisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Massachusetts, United States of America
| | - Robert J. Klein
- Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Andrew D. Johnson
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, The Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Ingrid B. Borecki
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Paul W. Franks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
- Department of Public Health & Clinical Medicine, Umeå University, Umeå, Sweden
| | - Kari E. North
- Carolina Center for Genome Sciences, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - L. Adrienne Cupples
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Ruth J. F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Genetics of Obesity and Related Metabolic Traits Program, Charles Bronfman Institute for Personalized Medicine, 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
- The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Tuomas O. Kilpeläinen
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
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23
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Williams L, Seki Y, Delahaye F, Cheng A, Fuloria M, Hughes Einstein F, Charron MJ. DNA hypermethylation of CD3(+) T cells from cord blood of infants exposed to intrauterine growth restriction. Diabetologia 2016; 59:1714-23. [PMID: 27185256 DOI: 10.1007/s00125-016-3983-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Accepted: 04/19/2016] [Indexed: 12/18/2022]
Abstract
AIMS/HYPOTHESIS Intrauterine growth restriction (IUGR) is associated with increased susceptibility to obesity, metabolic syndrome and type 2 diabetes. Although the mechanisms underlying the developmental origins of metabolic disease are poorly understood, evidence suggests that epigenomic alterations play a critical role. We sought to identify changes in DNA methylation patterns that are associated with IUGR in CD3(+) T cells purified from umbilical cord blood obtained from male newborns who were appropriate for gestational age (AGA) or who had been exposed to IUGR. METHODS CD3(+) T cells were isolated from cord blood obtained from IUGR and AGA infants. The genome-wide methylation profile in eight AGA and seven IUGR samples was determined using the HELP tagging assay. Validation analysis using targeted bisulfite sequencing and bisulfite massARRAY was performed on the original cohort as well as biological replicates consisting of two AGA and four IUGR infants. The Segway algorithm was used to identify methylation changes within regulatory regions of the genome. RESULTS A global shift towards hypermethylation in IUGR was seen compared with AGA (89.8% of 4,425 differentially methylated loci), targeted to regulatory regions of the genome, specifically promoters and enhancers. Pathway analysis identified dysregulation of pathways involved in metabolic disease (type 2 diabetes mellitus, insulin signalling, mitogen-activated protein kinase signalling) and T cell development, regulation and activation (T cell receptor signalling), as well as transcription factors (TCF3, LEF1 and NFATC) that regulate T cells. Furthermore, bump-hunting analysis revealed differentially methylated regions in PRDM16 and HLA-DPB1, genes important for adipose tissue differentiation, stem cell maintenance and function and T cell activation. CONCLUSIONS/INTERPRETATION Our findings suggest that the alterations in methylation patterns observed in IUGR CD3(+) T cells may have functional consequences in targeted genes, regulatory regions and transcription factors. These may serve as biomarkers to identify those at 'high risk' for diminished attainment of full health potential who can benefit from early interventions. ACCESS TO RESEARCH MATERIALS HELP tagging data: Gene Expression Omnibus database (GSE77268), scheduled to be released on 25 January 2019.
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Affiliation(s)
- Lyda Williams
- Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Rm F312, Bronx, NY, 10461, USA
| | - Yoshinori Seki
- Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Rm F312, Bronx, NY, 10461, USA
| | - Fabien Delahaye
- Department of Obstetrics and Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Alex Cheng
- Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Rm F312, Bronx, NY, 10461, USA
| | - Mamta Fuloria
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Francine Hughes Einstein
- Department of Obstetrics and Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Maureen J Charron
- Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Rm F312, Bronx, NY, 10461, USA.
- Department of Obstetrics and Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, USA.
- Department of Medicine, Division of Endocrinology, Albert Einstein College of Medicine, Bronx, NY, USA.
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24
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Srivastava A, Srivastava N, Mittal B. Genetics of Obesity. Indian J Clin Biochem 2015; 31:361-71. [PMID: 27605733 DOI: 10.1007/s12291-015-0541-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2015] [Accepted: 12/08/2015] [Indexed: 12/29/2022]
Abstract
Numerous classical genetic studies have proved that genes are contributory factors for obesity. Genes are directly responsible for obesity associated disorders such as Bardet-Biedl and Prader-Willi syndromes. However, both genes as well as environment are associated with obesity in the general population. Genetic epidemiological approaches, particularly genome-wide association studies, have unraveled many genes which play important roles in human obesity. Elucidation of their biological functions can be very useful for understanding pathobiology of obesity. In the near future, further exploration of obesity genetics may help to develop useful diagnostic and predictive tests for obesity treatment.
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Affiliation(s)
- Apurva Srivastava
- Department of Medical Genetics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Rae Bareli Road, Lucknow, Uttar Pradesh 226014 India ; Department of Physiology, King George's Medical University, Chowk, Lucknow, Uttar Pradesh 226003 India
| | - Neena Srivastava
- Department of Physiology, King George's Medical University, Chowk, Lucknow, Uttar Pradesh 226003 India
| | - Balraj Mittal
- Department of Medical Genetics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Rae Bareli Road, Lucknow, Uttar Pradesh 226014 India
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25
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Schjoldager KT, Joshi HJ, Kong Y, Goth CK, King SL, Wandall HH, Bennett EP, Vakhrushev SY, Clausen H. Deconstruction of O-glycosylation--GalNAc-T isoforms direct distinct subsets of the O-glycoproteome. EMBO Rep 2015; 16:1713-22. [PMID: 26566661 PMCID: PMC4693523 DOI: 10.15252/embr.201540796] [Citation(s) in RCA: 84] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2015] [Revised: 10/05/2015] [Accepted: 10/16/2015] [Indexed: 12/20/2022] Open
Abstract
GalNAc-type O-glycosylation is found on most proteins trafficking through the secretory pathway in metazoan cells. The O-glycoproteome is regulated by up to 20 polypeptide GalNAc-Ts and the contributions and biological functions of individual GalNAc-Ts are poorly understood. Here, we used a zinc-finger nuclease (ZFN)-directed knockout strategy to probe the contributions of the major GalNAc-Ts (GalNAc-T1 and GalNAc-T2) in liver cells and explore how the GalNAc-T repertoire quantitatively affects the O-glycoproteome. We demonstrate that the majority of the O-glycoproteome is covered by redundancy, whereas distinct subsets of substrates are modified by non-redundant functions of GalNAc-T1 and GalNAc-T2. The non-redundant O-glycoproteome subsets and specific transcriptional responses for each isoform are related to different cellular processes; for the GalNAc-T2 isoform, these support a role in lipid metabolism. The results demonstrate that GalNAc-Ts have different non-redundant glycosylation functions, which may affect distinct cellular processes. The data serves as a comprehensive resource for unique GalNAc-T substrates. Our study provides a new view of the differential regulation of the O-glycoproteome, suggesting that the plurality of GalNAc-Ts arose to regulate distinct protein functions and cellular processes.
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Affiliation(s)
- Katrine T Schjoldager
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Hiren J Joshi
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Yun Kong
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Christoffer K Goth
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Sarah Louise King
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Hans H Wandall
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Eric P Bennett
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Sergey Y Vakhrushev
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Henrik Clausen
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Copenhagen N, Denmark
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26
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Genome-Wide Association Studies of the Human Gut Microbiota. PLoS One 2015; 10:e0140301. [PMID: 26528553 PMCID: PMC4631601 DOI: 10.1371/journal.pone.0140301] [Citation(s) in RCA: 176] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2015] [Accepted: 09/05/2015] [Indexed: 12/17/2022] Open
Abstract
The bacterial composition of the human fecal microbiome is influenced by many lifestyle factors, notably diet. It is less clear, however, what role host genetics plays in dictating the composition of bacteria living in the gut. In this study, we examined the association of ~200K host genotypes with the relative abundance of fecal bacterial taxa in a founder population, the Hutterites, during two seasons (n = 91 summer, n = 93 winter, n = 57 individuals collected in both). These individuals live and eat communally, minimizing variation due to environmental exposures, including diet, which could potentially mask small genetic effects. Using a GWAS approach that takes into account the relatedness between subjects, we identified at least 8 bacterial taxa whose abundances were associated with single nucleotide polymorphisms in the host genome in each season (at genome-wide FDR of 20%). For example, we identified an association between a taxon known to affect obesity (genus Akkermansia) and a variant near PLD1, a gene previously associated with body mass index. Moreover, we replicate a previously reported association from a quantitative trait locus (QTL) mapping study of fecal microbiome abundance in mice (genus Lactococcus, rs3747113, P = 3.13 x 10−7). Finally, based on the significance distribution of the associated microbiome QTLs in our study with respect to chromatin accessibility profiles, we identified tissues in which host genetic variation may be acting to influence bacterial abundance in the gut.
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27
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Voisin S, Almén MS, Zheleznyakova GY, Lundberg L, Zarei S, Castillo S, Eriksson FE, Nilsson EK, Blüher M, Böttcher Y, Kovacs P, Klovins J, Rask-Andersen M, Schiöth HB. Many obesity-associated SNPs strongly associate with DNA methylation changes at proximal promoters and enhancers. Genome Med 2015; 7:103. [PMID: 26449484 PMCID: PMC4599317 DOI: 10.1186/s13073-015-0225-4] [Citation(s) in RCA: 90] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2015] [Accepted: 09/21/2015] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND The mechanisms by which genetic variants, such as single nucleotide polymorphisms (SNPs), identified in genome-wide association studies act to influence body mass remain unknown for most of these SNPs, which continue to puzzle the scientific community. Recent evidence points to the epigenetic and chromatin states of the genome as having important roles. METHODS We genotyped 355 healthy young individuals for 52 known obesity-associated SNPs and obtained DNA methylation levels in their blood using the Illumina 450 K BeadChip. Associations between alleles and methylation at proximal cytosine residues were tested using a linear model adjusted for age, sex, weight category, and a proxy for blood cell type counts. For replication in other tissues, we used two open-access datasets (skin fibroblasts, n = 62; four brain regions, n = 121-133) and an additional dataset in subcutaneous and visceral fat (n = 149). RESULTS We found that alleles at 28 of these obesity-associated SNPs associate with methylation levels at 107 proximal CpG sites. Out of 107 CpG sites, 38 are located in gene promoters, including genes strongly implicated in obesity (MIR148A, BDNF, PTPMT1, NR1H3, MGAT1, SCGB3A1, HOXC12, PMAIP1, PSIP1, RPS10-NUDT3, RPS10, SKOR1, MAP2K5, SIX5, AGRN, IMMP1L, ELP4, ITIH4, SEMA3G, POMC, ADCY3, SSPN, LGR4, TUFM, MIR4721, SULT1A1, SULT1A2, APOBR, CLN3, SPNS1, SH2B1, ATXN2L, and IL27). Interestingly, the associated SNPs are in known eQTLs for some of these genes. We also found that the 107 CpGs are enriched in enhancers in peripheral blood mononuclear cells. Finally, our results indicate that some of these associations are not blood-specific as we successfully replicated four associations in skin fibroblasts. CONCLUSIONS Our results strongly suggest that many obesity-associated SNPs are associated with proximal gene regulation, which was reflected by association of obesity risk allele genotypes with differential DNA methylation. This study highlights the importance of DNA methylation and other chromatin marks as a way to understand the molecular basis of genetic variants associated with human diseases and traits.
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Affiliation(s)
- Sarah Voisin
- Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, Sweden.
| | - Markus Sällman Almén
- Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, Sweden.
- Department of Medical Biochemistry and Microbiology, Uppsala University, SE-751 23, Uppsala, Sweden.
| | - Galina Y Zheleznyakova
- Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, Sweden.
| | - Lina Lundberg
- Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, Sweden.
| | - Sanaz Zarei
- Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, Sweden.
| | - Sandra Castillo
- Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, Sweden.
| | - Fia Ence Eriksson
- Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, Sweden.
| | - Emil K Nilsson
- Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, Sweden.
| | - Matthias Blüher
- Medical Faculty, IFB Adiposity Diseases, University of Leipzig, Liebigstrasse 21, 04103, Leipzig, Germany.
| | - Yvonne Böttcher
- Medical Faculty, IFB Adiposity Diseases, University of Leipzig, Liebigstrasse 21, 04103, Leipzig, Germany.
| | - Peter Kovacs
- Medical Faculty, IFB Adiposity Diseases, University of Leipzig, Liebigstrasse 21, 04103, Leipzig, Germany.
| | - Janis Klovins
- Latvian Biomedical Research and Study Center, Ratsupites 1, Riga, LV-1067, Latvia.
| | - Mathias Rask-Andersen
- Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, Sweden.
| | - Helgi B Schiöth
- Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, Sweden.
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28
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Horikoshi M, Mӓgi R, van de Bunt M, Surakka I, Sarin AP, Mahajan A, Marullo L, Thorleifsson G, Hӓgg S, Hottenga JJ, Ladenvall C, Ried JS, Winkler TW, Willems SM, Pervjakova N, Esko T, Beekman M, Nelson CP, Willenborg C, Wiltshire S, Ferreira T, Fernandez J, Gaulton KJ, Steinthorsdottir V, Hamsten A, Magnusson PKE, Willemsen G, Milaneschi Y, Robertson NR, Groves CJ, Bennett AJ, Lehtimӓki T, Viikari JS, Rung J, Lyssenko V, Perola M, Heid IM, Herder C, Grallert H, Müller-Nurasyid M, Roden M, Hypponen E, Isaacs A, van Leeuwen EM, Karssen LC, Mihailov E, Houwing-Duistermaat JJ, de Craen AJM, Deelen J, Havulinna AS, Blades M, Hengstenberg C, Erdmann J, Schunkert H, Kaprio J, Tobin MD, Samani NJ, Lind L, Salomaa V, Lindgren CM, Slagboom PE, Metspalu A, van Duijn CM, Eriksson JG, Peters A, Gieger C, Jula A, Groop L, Raitakari OT, Power C, Penninx BWJH, de Geus E, Smit JH, Boomsma DI, Pedersen NL, Ingelsson E, Thorsteinsdottir U, Stefansson K, Ripatti S, Prokopenko I, McCarthy MI, Morris AP. Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation. PLoS Genet 2015; 11:e1005230. [PMID: 26132169 PMCID: PMC4488845 DOI: 10.1371/journal.pgen.1005230] [Citation(s) in RCA: 64] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2014] [Accepted: 04/18/2015] [Indexed: 11/19/2022] Open
Abstract
Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated. Human genetic studies have demonstrated that quantitative human anthropometric and metabolic traits, including body mass index, waist-hip ratio, and plasma concentrations of glucose and insulin, are highly heritable, and are established risk factors for type 2 diabetes and cardiovascular diseases. Although many regions of the genome have been associated with these traits, the specific genes responsible have not yet been identified. By making use of advanced statistical “imputation” techniques applied to more than 87,000 individuals of European ancestry, and publicly available “reference panels” of more than 37 million genetic variants, we have been able to identify novel regions of the genome associated with these glycaemic and obesity-related traits and localise genes within these regions that are most likely to be causal. This improved understanding of the biological mechanisms underlying glycaemic and obesity-related traits is extremely important because it may advance drug development for downstream disease endpoints, ultimately leading to public health benefits.
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Affiliation(s)
- Momoko Horikoshi
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
- * E-mail:
| | - Reedik Mӓgi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Martijn van de Bunt
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Ida Surakka
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Letizia Marullo
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | | | - Sara Hӓgg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Medical Sciences, Molecular Epidemiology, and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Claes Ladenvall
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
| | - Janina S. Ried
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas W. Winkler
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Sara M. Willems
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Children’s Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Marian Beekman
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - Christopher P. Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health Research Leicester Cardiovascular Disease Biomedical Research Unit, Glenfield Hospital, Leicester, United Kingdom
| | - Christina Willenborg
- Institute for Integrative and Experimental Genomics, University of Lübeck, Lübeck, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Hamburg/Kiel/Lübeck, Lübeck, Germany
| | - Steven Wiltshire
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Teresa Ferreira
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Juan Fernandez
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Kyle J. Gaulton
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | | | - Anders Hamsten
- Cardiovascular Genetics and Genomics Group, Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Patrik K. E. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Gonneke Willemsen
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Yuri Milaneschi
- Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands
| | - Neil R. Robertson
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Christopher J. Groves
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Amanda J. Bennett
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Terho Lehtimӓki
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Tampere, Finland
| | - Jorma S. Viikari
- Department of Medicine, University of Turku and Division of Medicine, Turku University Hospital, Turku, Finland
| | - Johan Rung
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
- Steno Diabetes Center A/S, Gentofte, Denmark
| | - Markus Perola
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Iris M. Heid
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Germany
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - 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-Universität, Munich, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
| | - Michael Roden
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Germany
- Department of Endocrinology and Diabetology, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Elina Hypponen
- School of Population Health, University of South Australia, Adelaide, Australia
- Centre for Paediatric Epidemiology and Biostatistics, University College London Institute of Child Health, London, United Kingdom
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Center for Medical Systems Biology, Leiden, The Netherlands
| | - Elisabeth M. van Leeuwen
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lennart C. Karssen
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | | | - Anton J. M. de Craen
- Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Joris Deelen
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - Aki S. Havulinna
- Unit of Chronic Disease Epidemiology and Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Matthew Blades
- Bioinformatics and Biostatistics Support Hub (B/BASH), University of Leicester, Leicester, United Kingdom
| | - Christian Hengstenberg
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Munich, Munich, Germany
| | - Jeanette Erdmann
- Institute for Integrative and Experimental Genomics, University of Lübeck, Lübeck, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Hamburg/Kiel/Lübeck, Lübeck, Germany
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- DZHK German Center for Cardiovascular Research, Partner Site Munich, Munich, Germany
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
- The Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Martin D. Tobin
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health Research (NIHR) Leicester Respiratory Biomedical Research Unit, Glenfield Hospital, Leicester, United Kingdom
| | - Nilesh J. Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health Research Leicester Cardiovascular Disease Biomedical Research Unit, Glenfield Hospital, Leicester, United Kingdom
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Akademiska Sjukhuset, Uppsala, Sweden
| | - Veikko Salomaa
- Unit of Chronic Disease Epidemiology and Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Cecilia M. Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
| | - P. Eline Slagboom
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Center for Medical Systems Biology, Leiden, The Netherlands
| | - Johan G. Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- Vasa Central Hospital, Vasa, Finland
- Department of Health Promotion and Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Annette Peters
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Antti Jula
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Turku, Finland
| | - Leif Groop
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
| | - Olli T. Raitakari
- Research Center of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, University of Turku and Turku University Hospital, Turku, Finland
| | - Chris Power
- Centre for Paediatric Epidemiology and Biostatistics, University College London Institute of Child Health, London, United Kingdom
| | | | - Eco de Geus
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
- EMGO Institute for Health and Care Research, VU University & VU University Medical Center, Amsterdam, The Netherlands
| | - Johannes H. Smit
- Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Erik Ingelsson
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Department of Medical Sciences, Molecular Epidemiology, and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Unnur Thorsteinsdottir
- deCode Genetic - Amgen Inc, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Kari Stefansson
- deCode Genetic - Amgen Inc, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
- The Department of Public Health, University of Helsinki, Helsinki, Finland
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Inga Prokopenko
- Deparment of Genomics of Common Disease, School of Public Health, Imperial College London, London, United Kingdom
| | - Mark I. McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
- Oxford National Institute for Health Research Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom
| | - Andrew P. Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Department of Biostatistics, University of Liverpool, Liverpool, United Kingdom
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, United Kingdom
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Dong C, Della-Morte D, Beecham A, Wang L, Cabral D, Blanton SH, Sacco RL, Rundek T. Genetic variants in LEKR1 and GALNT10 modulate sex-difference in carotid intima-media thickness: a genome-wide interaction study. Atherosclerosis 2015; 240:462-7. [PMID: 25898001 PMCID: PMC4441583 DOI: 10.1016/j.atherosclerosis.2015.04.019] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2015] [Revised: 03/27/2015] [Accepted: 04/13/2015] [Indexed: 12/22/2022]
Abstract
BACKGROUND There is an established sex-difference in carotid artery intima-media thickness (cIMT), a recognized marker of subclinical atherosclerosis. However, the genetic underpinnings of sex-differences in gene-IMT associations are largely unknown. METHODS With a multistage design using 731,037 single nucleotide polymorphisms (SNP), a genome wide interaction study was performed in a discovery sample of 931 unrelated Hispanics, followed by replication in 153 non-Hispanic whites and 257 non-Hispanic blacks. Assuming an additive genetic model, we tested for sex-SNP interactions on cIMT using regression analysis. RESULTS We did not identify any genome-wide significant SNPs but identified 14 loci with suggestive significance. Specifically, SNP-by-sex interaction was found for rs7616559 within LEKR1 gene (P = 3.5E-06 in Hispanic discovery sample, P = 0.018 in White, and P = 1.3E-06 in combined analysis) and for rs2081015 located within GALNT10 gene (P = 4.5E-06 in Hispanic discovery sample, P = 0.042 in Blacks, and P = 5.3E-07 in combined analysis). For rs7616559 within LEKR1, men had greater cIMT than women in G allele carriers (beta ± SE: 0.044 ± 0.007, P = 4.2E-09 in AG carriers; beta ± SE: 0.064 ± 0.007, P = 6.2E-05 in GG carriers). For rs2081015 within GALNT10, men had greater cIMT than women in C allele carriers (beta ± SE: 0.022 ± 0.007, P = 0.002 in CT carriers; beta ± SE: 0.051 ± 0.008, P = 3.1E-10 in CC carriers). CONCLUSIONS Our genome-wide interaction analysis reveals multiple loci that may modulate sex difference in cIMT. Of them, genetic variants on LEKR1 and GALNT10 genes have been associated with control of adiposity and weight. Given the consistent findings across different-ethnic groups, further studies are warranted to perform investigations of functional genetic variants in these regions.
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Affiliation(s)
- Chuanhui Dong
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - David Della-Morte
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA; Department of Systems Medicine, School of Medicine, University of Rome Tor Vergata, Rome, Italy; IRCCS San Raffaele Pisana, Rome, Italy
| | - Ashley Beecham
- John T. McDonald Department of Human Genetics, John P Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Liyong Wang
- John T. McDonald Department of Human Genetics, John P Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Digna Cabral
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Susan H Blanton
- John T. McDonald Department of Human Genetics, John P Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Ralph L Sacco
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA; John T. McDonald Department of Human Genetics, John P Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA; Department of Epidemiology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Tatjana Rundek
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA; Department of Epidemiology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA.
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Fulford AJ, Ong KK, Elks CE, Prentice AM, Hennig BJ. Progressive influence of body mass index-associated genetic markers in rural Gambians. J Med Genet 2015; 52:375-80. [PMID: 25921383 PMCID: PMC4453496 DOI: 10.1136/jmedgenet-2014-102784] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2014] [Accepted: 12/13/2014] [Indexed: 01/06/2023]
Abstract
Background In populations of European ancestry, the genetic contribution to body mass index (BMI) increases with age during childhood but then declines during adulthood, possibly due to the cumulative effects of environmental factors. How the effects of genetic factors on BMI change with age in other populations is unknown. Subjects and methods In a rural Gambian population (N=2535), we used a combined allele risk score, comprising genotypes at 28 ‘Caucasian adult BMI-associated’ single nucleotide polymorphisms (SNPs), as a marker of the genetic influence on body composition, and related this to internally-standardised z-scores for birthweight (zBW), weight-for-height (zWT-HT), weight-for-age (zWT), height-for-age (zHT), and zBMI cross-sectionally and longitudinally. Results Cross-sectionally, the genetic score was positively associated with adult zWT (0.018±0.009 per allele, p=0.034, N=1426) and zWT-HT (0.025±0.009, p=0.006), but not with size at birth or childhood zWT-HT (0.008±0.005, p=0.11, N=2211). The effect of the genetic score on zWT-HT strengthened linearly with age from birth through to late adulthood (age interaction term: 0.0083 z-scores/allele/year; 95% CI 0.0048 to 0.0118, p=0.0000032). Conclusions Genetic variants for obesity in populations of European ancestry have direct relevance to bodyweight in nutritionally deprived African settings. In such settings, genetic obesity susceptibility appears to regulate change in weight status throughout the life course, which provides insight into its potential physiological role.
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Affiliation(s)
- Anthony J Fulford
- MRC International Nutrition Group at LSHTM, UK & MRC Unit, The Gambia; Department of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
| | - Ken K Ong
- MRC Epidemiology Unit, University of Cambridge, School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Cathy E Elks
- MRC Epidemiology Unit, University of Cambridge, School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Andrew M Prentice
- MRC International Nutrition Group at LSHTM, UK & MRC Unit, The Gambia; Department of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
| | - Branwen J Hennig
- MRC International Nutrition Group at LSHTM, UK & MRC Unit, The Gambia; Department of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
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31
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Yako YY, Echouffo-Tcheugui JB, Balti EV, Matsha TE, Sobngwi E, Erasmus RT, Kengne AP. Genetic association studies of obesity in Africa: a systematic review. Obes Rev 2015; 16:259-72. [PMID: 25641693 DOI: 10.1111/obr.12260] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2014] [Revised: 11/13/2014] [Accepted: 12/05/2014] [Indexed: 12/31/2022]
Abstract
Obesity is increasing in Africa, but the underlying genetic background largely remains unknown. We assessed existing evidence on genetic determinants of obesity among populations within Africa. MEDLINE and EMBASE were searched and the bibliographies of retrieved articles were examined. Included studies had to report on the association of a genetic marker with obesity indices and the presence/occurrence of obesity/obesity trait. Data were extracted on study design and characteristics, genetic determinants and effect estimates of associations with obesity indices. According to this data, over 300 polymorphisms in 42 genes have been studied in various population groups within Africa mostly through the candidate gene approach. Polymorphisms in genes such as ACE, ADIPOQ, ADRB2, AGRP, AR, CAPN10, CD36, C7orf31, DRD4, FTO, MC3R, MC4R, SGIP1 and LEP were found to be associated with various measures of obesity. Of the 36 polymorphisms previously validated by genome-wide association studies (GWAS) elsewhere, only FTO and MC4R polymorphisms showed significant associations with obesity in black South Africans, Nigerians and Ghanaians. However, these data are insufficient to establish the true nature of genetic susceptibility to obesity in populations within Africa. There has been recent progress in describing the genetic architecture of obesity among populations within Africa. This effort needs to be sustained via GWAS studies.
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Affiliation(s)
- Y Y Yako
- Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town, South Africa; Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Cape Town, South Africa
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Apalasamy YD, Mohamed Z. Obesity and genomics: role of technology in unraveling the complex genetic architecture of obesity. Hum Genet 2015; 134:361-74. [PMID: 25687726 DOI: 10.1007/s00439-015-1533-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2014] [Accepted: 02/02/2015] [Indexed: 01/15/2023]
Abstract
Obesity is a complex and multifactorial disease that occurs as a result of the interaction between "obesogenic" environmental factors and genetic components. Although the genetic component of obesity is clear from the heritability studies, the genetic basis remains largely elusive. Successes have been achieved in identifying the causal genes for monogenic obesity using animal models and linkage studies, but these approaches are not fruitful for polygenic obesity. The developments of genome-wide association approach have brought breakthrough discovery of genetic variants for polygenic obesity where tens of new susceptibility loci were identified. However, the common SNPs only accounted for a proportion of heritability. The arrival of NGS technologies and completion of 1000 Genomes Project have brought other new methods to dissect the genetic architecture of obesity, for example, the use of exome genotyping arrays and deep sequencing of candidate loci identified from GWAS to study rare variants. In this review, we summarize and discuss the developments of these genetic approaches in human obesity.
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Affiliation(s)
- Yamunah Devi Apalasamy
- Department of Pharmacology, Pharmacogenomics Laboratory, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia,
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Wang T, Jia W, Hu C. Advancement in genetic variants conferring obesity susceptibility from genome-wide association studies. Front Med 2014; 9:146-61. [PMID: 25556696 DOI: 10.1007/s11684-014-0373-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2014] [Accepted: 08/25/2014] [Indexed: 12/18/2022]
Abstract
Obesity prevalence has increased in recent years. Lifestyle change fuels obesity, but genetic factors cause more than 50% of average variations in obesity. The advent of genome-wide association studies (GWAS) has hastened the progress of polygenic obesity research. As of this writing, more than 73 obesity susceptibility loci have been identified in ethnic groups through GWAS. The identified loci explain only 2% to 4% of obesity heritability, thereby indicating that a large proportion of loci remain undiscovered. Thus, the next step is to identify and confirm novel loci, which may exhibit smaller effects and lower allele frequencies than established loci. However, achieving these tasks has been difficult for researchers. GWAS help researchers discover the causal loci. Moreover, numerous biological studies have been performed on the polygenic effects on obesity, such as studies on fat mass- and obesity-associated gene (FTO), but the role of these polygenic effects in the mechanism of obesity remains unclear. Thus, obesity-causing variations should be identified, and insights into the biology of polygenic effects on obesity are needed.
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Affiliation(s)
- Tao Wang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China
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Huebbe P, Dose J, Schloesser A, Campbell G, Glüer CC, Gupta Y, Ibrahim S, Minihane AM, Baines JF, Nebel A, Rimbach G. Apolipoprotein E (APOE) genotype regulates body weight and fatty acid utilization-Studies in gene-targeted replacement mice. Mol Nutr Food Res 2014; 59:334-43. [DOI: 10.1002/mnfr.201400636] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2014] [Revised: 10/21/2014] [Accepted: 10/29/2014] [Indexed: 11/11/2022]
Affiliation(s)
- Patricia Huebbe
- Institute of Human Nutrition and Food Science; University of Kiel; Kiel Germany
| | - Janina Dose
- Institute of Human Nutrition and Food Science; University of Kiel; Kiel Germany
| | - Anke Schloesser
- Institute of Human Nutrition and Food Science; University of Kiel; Kiel Germany
| | - Graeme Campbell
- Section Biomedical Imaging; Department of Diagnostic Radiology; University of Kiel; Kiel Germany
| | - Claus-Christian Glüer
- Section Biomedical Imaging; Department of Diagnostic Radiology; University of Kiel; Kiel Germany
| | - Yask Gupta
- Department of Dermatology; University of Lübeck; Lübeck Germany
| | - Saleh Ibrahim
- Department of Dermatology; University of Lübeck; Lübeck Germany
| | - Anne-Marie Minihane
- Department of Nutrition; Norwich Medical School; University of East Anglia; Norwich United Kingdom
| | - John F. Baines
- Institute for Experimental Medicine; University of Kiel; Kiel Germany
- Max Planck Institute for Evolutionary Biology; Plön Germany
| | - Almut Nebel
- Institute of Clinical Molecular Biology; University of Kiel; Kiel Germany
| | - Gerald Rimbach
- Institute of Human Nutrition and Food Science; University of Kiel; Kiel Germany
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Peprah E, Xu H, Tekola-Ayele F, Royal CD. Genome-wide association studies in Africans and African Americans: expanding the framework of the genomics of human traits and disease. Public Health Genomics 2014; 18:40-51. [PMID: 25427668 DOI: 10.1159/000367962] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2014] [Accepted: 08/29/2014] [Indexed: 01/11/2023] Open
Abstract
Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.
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36
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Valera B, Sohani Z, Rana A, Poirier P, Anand SS. The ethnoepidemiology of obesity. Can J Cardiol 2014; 31:131-41. [PMID: 25661548 DOI: 10.1016/j.cjca.2014.10.005] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2014] [Revised: 10/02/2014] [Accepted: 10/06/2014] [Indexed: 12/25/2022] Open
Abstract
The prevalence of overweight and obesity varies significantly across ethnic groups and among aboriginal people in Canada and appears to be increasing overall in children and youth, which will have significant health consequences in the future. Individual health behaviours, genetic predisposition, and community-level factors all contribute to the high burden of overweight and obesity across communities in Canada. Preliminary studies indicate that individuals who live in neighbourhoods in Canada with increased walkability, fewer fast food outlets, and higher socioeconomic status have lower rates of overweight/obesity when compared with other neighbourhoods. However, more research is required to understand the impact of community level factors on overweight/obesity trends in Canadian ethnic groups, including children and youth, and aboriginal people.
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Affiliation(s)
- Beatriz Valera
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Québec, Québec, Canada
| | - Zahra Sohani
- Population Genomics Program, Department of Clinical Epidemiology & Biostatistics, Hamilton, Ontario, Canada; Chanchlani Research Centre, McMaster University, Hamilton, Ontario, Canada
| | - Ayesha Rana
- Population Genomics Program, Department of Clinical Epidemiology & Biostatistics, Hamilton, Ontario, Canada; Chanchlani Research Centre, McMaster University, Hamilton, Ontario, Canada
| | - Paul Poirier
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Québec, Québec, Canada; Faculté de pharmacie de l'Université Laval, Québec, Québec, Canada
| | - Sonia S Anand
- Population Genomics Program, Department of Clinical Epidemiology & Biostatistics, Hamilton, Ontario, Canada; Chanchlani Research Centre, McMaster University, Hamilton, Ontario, Canada; Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
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Meng XR, Song JY, Ma J, Liu FH, Shang XR, Guo XJ, Wang HJ. Association study of childhood obesity with eight genetic variants recently identified by genome-wide association studies. Pediatr Res 2014; 76:310-5. [PMID: 24956226 DOI: 10.1038/pr.2014.88] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2013] [Accepted: 04/07/2014] [Indexed: 01/21/2023]
Abstract
BACKGROUND Being overweight or obese is becoming increasingly common in low- and middle-income countries. The present study aimed to examine association of eight genetic variants with obesity and to estimate the cumulative effects of these variants in Chinese children. METHODS We conducted the case-control study in a total of 2,030 subjects. Genotyping of seven novel variants was performed with matrix-assisted laser desorption ionization time of flight mass spectrometry, while rs9939609 was genotyped with tetra-primer amplification refractory mutation system analysis. RESULTS The association of two fat mass and obesity-associated gene (FTO) single-nucleotide polymorphisms (SNPs; rs9939609 and rs62048402) with body mass index (BMI) or obesity reached nominal significance at P < 0.05. We found a cumulative effect of five SNPs on the risk of overweight and obesity (odds ratio (OR) = 1.197, 95% confidence interval (CI) = 1.068-1.342, P = 0.002). Subjects carrying 9 or more effect alleles had a 127% increased risk of overweight and obesity (OR = 2.270, 95% CI = 1.403-3.671, P = 0.001) compared with subjects who carry 6 or fewer effect alleles. CONCLUSION We confirmed two FTO SNPs (rs62048402 and rs9939609) had nominal significant effects on BMI or obesity. We identified the cumulative effect of five SNPs on risk of overweight and obesity. The results provided evidence for identifying genetic factors related to childhood obesity.
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Affiliation(s)
- Xiang-Rui Meng
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Jie-Yun Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Jun Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Fang-Hong Liu
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Xiao-Rui Shang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Xu-Jun Guo
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
| | - Hai-Jun Wang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China
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Scannell Bryan M, Argos M, Pierce B, Tong L, Rakibuz-Zaman M, Ahmed A, Rahman M, Islam T, Yunus M, Parvez F, Roy S, Jasmine F, Baron JA, Kibriya MG, Ahsan H. Genome-wide association studies and heritability estimates of body mass index related phenotypes in Bangladeshi adults. PLoS One 2014; 9:e105062. [PMID: 25133637 PMCID: PMC4136799 DOI: 10.1371/journal.pone.0105062] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2014] [Accepted: 07/18/2014] [Indexed: 11/29/2022] Open
Abstract
Many health outcomes are influenced by a person's body mass index, as well as by the trajectory of body mass index through a lifetime. Although previous research has established that body mass index related traits are influenced by genetics, the relationship between these traits and genetics has not been well characterized in people of South Asian ancestry. To begin to characterize this relationship, we analyzed the association between common genetic variation and five phenotypes related to body mass index in a population-based sample of 5,354 Bangladeshi adults. We discovered a significant association between SNV rs347313 (intron of NOS1AP) and change in body mass index in women over two years. In a linear mixed-model, the G allele was associated with an increase of 0.25 kg/m2 in body mass index over two years (p-value of 2.3·10−8). We also estimated the heritability of these phenotypes from our genotype data. We found significant estimates of heritability for all of the body mass index-related phenotypes. Our study evaluated the genetic determinants of body mass index related phenotypes for the first time in South Asians. The results suggest that these phenotypes are heritable and some of this heritability is driven by variation that differs from those previously reported. We also provide evidence that the genetic etiology of body mass index related traits may differ by ancestry, sex, and environment, and consequently that these factors should be considered when assessing the genetic determinants of the risk of body mass index-related disease.
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Affiliation(s)
- Molly Scannell Bryan
- Department of Health Studies, University of Chicago, Chicago, Illinois, United States of America
| | - Maria Argos
- Department of Health Studies, University of Chicago, Chicago, Illinois, United States of America
| | - Brandon Pierce
- Department of Health Studies, University of Chicago, Chicago, Illinois, United States of America
| | - Lin Tong
- Department of Health Studies, University of Chicago, Chicago, Illinois, United States of America
| | | | | | | | | | - Muhammad Yunus
- International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh
| | - Faruque Parvez
- Department of Environmental Health Sciences, Columbia University, New York, New York, United States of America
| | - Shantanu Roy
- Department of Health Studies, University of Chicago, Chicago, Illinois, United States of America
| | - Farzana Jasmine
- Department of Health Studies, University of Chicago, Chicago, Illinois, United States of America
| | - John A. Baron
- Department of Medicine, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Muhammad G. Kibriya
- Department of Health Studies, University of Chicago, Chicago, Illinois, United States of America
| | - Habibul Ahsan
- Department of Health Studies, University of Chicago, Chicago, Illinois, United States of America
- * E-mail:
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Obesity gene NEGR1 associated with white matter integrity in healthy young adults. Neuroimage 2014; 102 Pt 2:548-57. [PMID: 25072390 DOI: 10.1016/j.neuroimage.2014.07.041] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2014] [Revised: 06/23/2014] [Accepted: 07/22/2014] [Indexed: 12/14/2022] Open
Abstract
Obesity is a crucial public health issue in developed countries, with implications for cardiovascular and brain health as we age. A number of commonly-carried genetic variants are associated with obesity. Here we aim to see whether variants in obesity-associated genes--NEGR1, FTO, MTCH2, MC4R, LRRN6C, MAP2K5, FAIM2, SEC16B, ETV5, BDNF-AS, ATXN2L, ATP2A1, KCTD15, and TNN13K--are associated with white matter microstructural properties, assessed by high angular resolution diffusion imaging (HARDI) in young healthy adults between 20 and 30 years of age from the Queensland Twin Imaging study (QTIM). We began with a multi-locus approach testing how a number of common genetic risk factors for obesity at the single nucleotide polymorphism (SNP) level may jointly influence white matter integrity throughout the brain and found a wide spread genetic effect. Risk allele rs2815752 in NEGR1 was most associated with lower white matter integrity across a substantial portion of the brain. Across the area of significance in the bilateral posterior corona radiata, each additional copy of the risk allele was associated with a 2.2% lower average FA. This is the first study to find an association between an obesity risk gene and differences in white matter integrity. As our subjects were young and healthy, our results suggest that NEGR1 has effects on brain structure independent of its effect on obesity.
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Peterson RE, Maes HH, Lin P, Kramer JR, Hesselbrock VM, Bauer LO, Nurnberger JI, Edenberg HJ, Dick DM, Webb BT. On the association of common and rare genetic variation influencing body mass index: a combined SNP and CNV analysis. BMC Genomics 2014; 15:368. [PMID: 24884913 PMCID: PMC4035084 DOI: 10.1186/1471-2164-15-368] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2013] [Accepted: 04/27/2014] [Indexed: 12/18/2022] Open
Abstract
Background As the architecture of complex traits incorporates a widening spectrum of genetic variation, analyses integrating common and rare variation are needed. Body mass index (BMI) represents a model trait, since common variation shows robust association but accounts for a fraction of the heritability. A combined analysis of single nucleotide polymorphisms (SNP) and copy number variation (CNV) was performed using 1850 European and 498 African-Americans from the Study of Addiction: Genetics and Environment. Genetic risk sum scores (GRSS) were constructed using 32 BMI-validated SNPs and aggregate-risk methods were compared: count versus weighted and proxy versus imputation. Results The weighted SNP-GRSS constructed from imputed probabilities of risk alleles performed best and was highly associated with BMI (p = 4.3×10−16) accounting for 3% of the phenotypic variance. In addition to BMI-validated SNPs, common and rare BMI/obesity-associated CNVs were identified from the literature. Of the 84 CNVs previously reported, only 21-kilobase deletions on 16p12.3 showed evidence for association with BMI (p = 0.003, frequency = 16.9%), with two CNVs nominally associated with class II obesity, 1p36.1 duplications (OR = 3.1, p = 0.009, frequency 1.2%) and 5q13.2 deletions (OR = 1.5, p = 0.048, frequency 7.7%). All other CNVs, individually and in aggregate, were not associated with BMI or obesity. The combined model, including covariates, SNP-GRSS, and 16p12.3 deletion accounted for 11.5% of phenotypic variance in BMI (3.2% from genetic effects). Models significantly predicted obesity classification with maximum discriminative ability for morbid-obesity (p = 3.15×10−18). Conclusion Results show that incorporating validated effect sizes and allelic probabilities improve prediction algorithms. Although rare-CNVs did not account for significant phenotypic variation, results provide a framework for integrated analyses. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-368) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Roseann E Peterson
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Human and Molecular Genetics, School of Medicine, Virginia Commonwealth University, Biotech I, 800 E, Leigh Street, Richmond, VA 23298-0126, USA.
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Fall T, Ingelsson E. Genome-wide association studies of obesity and metabolic syndrome. Mol Cell Endocrinol 2014; 382:740-757. [PMID: 22963884 DOI: 10.1016/j.mce.2012.08.018] [Citation(s) in RCA: 197] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2011] [Revised: 05/04/2012] [Accepted: 08/27/2012] [Indexed: 11/29/2022]
Abstract
Until just a few years ago, the genetic determinants of obesity and metabolic syndrome were largely unknown, with the exception of a few forms of monogenic extreme obesity. Since genome-wide association studies (GWAS) became available, large advances have been made. The first single nucleotide polymorphism robustly associated with increased body mass index (BMI) was in 2007 mapped to a gene with for the time unknown function. This gene, now known as fat mass and obesity associated (FTO) has been repeatedly replicated in several ethnicities and is affecting obesity by regulating appetite. Since the first report from a GWAS of obesity, an increasing number of markers have been shown to be associated with BMI, other measures of obesity or fat distribution and metabolic syndrome. This systematic review of obesity GWAS will summarize genome-wide significant findings for obesity and metabolic syndrome and briefly give a few suggestions of what is to be expected in the next few years.
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Affiliation(s)
- Tove Fall
- Dept. of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Erik Ingelsson
- Dept. of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden.
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Abstract
Single nucleotide polymorphisms (SNPs) that cluster in the first intron of fat mass and obesity associated (FTO) gene are associated obesity traits in genome-wide association studies. The minor allele increases BMI by 0.39 kg/m(2) (or 1,130 g in body weight) and risk of obesity by 1.20-fold. This association has been confirmed across age groups and populations of diverse ancestry; the largest effect is seen in young adulthood. The effect of FTO SNPs on obesity traits in populations of African and Asian ancestry is similar or somewhat smaller than in European ancestry populations. However, the BMI-increasing allele in FTO is substantially less prevalent in populations with non-European ancestry. FTO SNPs do not influence physical activity levels; yet, in physically active individuals, FTO's effect on obesity susceptibility is attenuated by approximately 30%. Evidence from epidemiological and functional studies suggests that FTO confers an increased risk of obesity by subtly changing food intake and preference. Moreover, emerging data suggest a role for FTO in nutrient sensing, regulation of mRNA translation and general growth. In this Review, we discuss the genetic epidemiology of FTO and discuss how its complex biology might link to the regulation of body weight.
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Affiliation(s)
- Ruth J F Loos
- The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1003, New York, NY 10029-6574, USA
| | - Giles S H Yeo
- MRC Metabolic Diseases Unit, University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
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Graff M, Fernández-Rhodes L, Liu S, Carlson C, Wassertheil-Smoller S, Neuhouser M, Reiner A, Kooperberg C, Rampersaud E, Manson JE, Kuller LH, Howard BV, Ochs-Balcom HM, Johnson KC, Vitolins MZ, Sucheston L, Monda K, North KE. Generalization of adiposity genetic loci to US Hispanic women. Nutr Diabetes 2013; 3:e85. [PMID: 23978819 PMCID: PMC3759132 DOI: 10.1038/nutd.2013.26] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2013] [Revised: 06/28/2013] [Accepted: 07/22/2013] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND: Obesity is a public health concern. Yet the identification of adiposity-related genetic variants among United States (US) Hispanics, which is the largest US minority group, remains largely unknown. OBJECTIVE: To interrogate an a priori list of 47 (32 overall body mass and 15 central adiposity) index single-nucleotide polymorphisms (SNPs) previously studied in individuals of European descent among 3494 US Hispanic women in the Women's Health Initiative SNP Health Association Resource (WHI SHARe). DESIGN: Cross-sectional analysis of measured body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) were inverse normally transformed after adjusting for age, smoking, center and global ancestry. WC and WHR models were also adjusted for BMI. Genotyping was performed using the Affymetrix 6.0 array. In the absence of an a priori selected SNP, a proxy was selected (r2⩾0.8 in CEU). RESULTS: Six BMI loci (TMEM18, NUDT3/HMGA1, FAIM2, FTO, MC4R and KCTD15) and two WC/WHR loci (VEGFA and ITPR2-SSPN) were nominally significant (P<0.05) at the index or proxy SNP in the corresponding BMI and WC/WHR models. To account for distinct linkage disequilibrium patterns in Hispanics and further assess generalization of genetic effects at each locus, we interrogated the evidence for association at the 47 surrounding loci within 1 Mb region of the index or proxy SNP. Three additional BMI loci (FANCL, TFAP2B and ETV5) and five WC/WHR loci (DNM3-PIGC, GRB14, ADAMTS9, LY86 and MSRA) displayed Bonferroni-corrected significant associations with BMI and WC/WHR. Conditional analyses of each index SNP (or its proxy) and the most significant SNP within the 1 Mb region supported the possible presence of index-independent signals at each of these eight loci as well as at KCTD15. CONCLUSION: This study provides evidence for the generalization of nine BMI and seven central adiposity loci in Hispanic women. This study expands the current knowledge of common adiposity-related genetic loci to Hispanic women.
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Affiliation(s)
- M Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Al Safar HS, Cordell HJ, Jafer O, Anderson D, Jamieson SE, Fakiola M, Khazanehdari K, Tay GK, Blackwell JM. A genome-wide search for type 2 diabetes susceptibility genes in an extended Arab family. Ann Hum Genet 2013; 77:488-503. [PMID: 23937595 DOI: 10.1111/ahg.12036] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2012] [Accepted: 05/04/2013] [Indexed: 01/17/2023]
Abstract
Twenty percent of people aged 20 to 79 have type 2 diabetes (T2D) in the United Arab Emirates (UAE). Genome-wide association studies (GWAS) to identify genes for T2D have not been reported for Arab countries. We performed a discovery GWAS in an extended UAE family (N=178; 66 diabetic; 112 healthy) genotyped on the Illumina Human 660 Quad Beadchip, with independent replication of top hits in 116 cases and 199 controls. Power to achieve genome-wide significance (commonly P=5×10(-8)) was therefore limited. Nevertheless, transmission disequilibrium testing in FBAT identified top hits at Chromosome 4p12-p13 (KCTD8: rs4407541, P=9.70×10(-6); GABRB1: rs10517178/rs1372491, P=4.19×10(-6)) and 14q13 (PRKD1: rs10144903, 3.92×10(-6)), supported by analysis using a linear mixed model approximation in GenABEL (4p12-p13 GABRG1/GABRA2: rs7662743, Padj-agesex=2.06×10(-5); KCTD8: rs4407541, Padj-agesex=1.42×10(-4); GABRB1: rs10517178/rs1372491, Padj-agesex=0.027; 14q13 PRKD1: rs10144903, Padj-agesex=6.95×10(-5)). SNPs across GABRG1/GABRA2 did not replicate, whereas more proximal SNPs rs7679715 (Padj-agesex=0.030) and rs2055942 (Padj-agesex=0.022) at COX7B2/GABRA4 did, in addition to a trend distally at KCTD8 (rs4695718: Padj-agesex=0.096). Modelling of discovery and replication data support independent signals at GABRA4 (rs2055942: Padj-agesex-combined=3×10(-4)) and at KCTD8 (rs4695718: Padj-agesex-combined=2×10(-4)). Replication was observed for PRKD1 rs1953722 (proxy for rs10144903; Padj-agesex=0.031; Padj-agesex-combined=2×10(-4)). These genes may provide important functional leads in understanding disease pathogenesis in this population.
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Affiliation(s)
- Habiba S Al Safar
- Centre for Forensic Science, The University of Western Australia, Crawley, Western, Australia; Khalifa University of Science, Technology & Research, Biomedical Department, Abu Dhabi, United Arab Emirates
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Lu Y, Loos RJ. Obesity genomics: assessing the transferability of susceptibility loci across diverse populations. Genome Med 2013; 5:55. [PMID: 23806069 PMCID: PMC3706771 DOI: 10.1186/gm459] [Citation(s) in RCA: 75] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The prevalence of obesity has nearly doubled worldwide over the past three decades, but substantial differences exist between nations. Although these differences are partly due to the degree of westernization, genetic factors also contribute. To date, little is known about whether the same genes contribute to obesity-susceptibility in populations of different ancestry. We review the transferability of obesity-susceptibility loci (identified by genome-wide association studies) using both single nucleotide polymorphism (SNP) and locus-wide comparisons. SNPs in FTO and near MC4R, obesity-susceptibility loci first identified in Europeans, replicate widely across other ancestries. SNP-to-SNP comparisons suggest that more than half of the 36 body mass index-associated loci are shared across European and East Asian ancestry populations, whereas locus-wide analyses suggest that the transferability might be even more extensive. Furthermore, by taking advantage of differences in haplotype structure, populations of different ancestries can help to narrow down loci, thereby pinpointing causal genes for functional follow-up. Larger-scale genetic association studies in ancestrally diverse populations will be needed for in-depth and locus-wide analyses aimed at determining, with greater confidence, the transferability of loci and allowing fine-mapping. Understanding similarities and differences in genetic susceptibility across populations of diverse ancestries might eventually contribute to a more targeted prevention and customized treatment of obesity.
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Affiliation(s)
- Yingchang Lu
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA ; The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ruth Jf Loos
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA ; The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA ; The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA ; The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
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Monda KL, Chen GK, Taylor KC, Palmer C, Edwards TL, Lange LA, Ng MC, Adeyemo AA, Allison MA, Bielak LF, Chen G, Graff M, Irvin MR, Rhie SK, Li G, Liu Y, Liu Y, Lu Y, Nalls MA, Sun YV, Wojczynski MK, Yanek LR, Aldrich MC, Ademola A, Amos CI, Bandera EV, Bock CH, Britton A, Broeckel U, Cai Q, Caporaso NE, Carlson C, Carpten J, Casey G, Chen WM, Chen F, Chen YDI, Chiang CW, Coetzee GA, Demerath E, Deming-Halverson SL, Driver RW, Dubbert P, Feitosa MF, Freedman BI, Gillanders EM, Gottesman O, Guo X, Haritunians T, Harris T, Harris CC, Hennis AJM, Hernandez DG, McNeill LH, Howard TD, Howard BV, Howard VJ, Johnson KC, Kang SJ, Keating BJ, Kolb S, Kuller LH, Kutlar A, Langefeld CD, Lettre G, Lohman K, Lotay V, Lyon H, Manson JE, Maixner W, Meng YA, Monroe KR, Morhason-Bello I, Murphy AB, Mychaleckyj JC, Nadukuru R, Nathanson KL, Nayak U, N’Diaye A, Nemesure B, Wu SY, Leske MC, Neslund-Dudas C, Neuhouser M, Nyante S, Ochs-Balcom H, Ogunniyi A, Ogundiran TO, Ojengbede O, Olopade OI, Palmer JR, Ruiz-Narvaez EA, Palmer ND, Press MF, Rampersaud E, Rasmussen-Torvik LJ, Rodriguez-Gil JL, Salako B, Schadt EE, Schwartz AG, Shriner DA, Siscovick D, Smith SB, Wassertheil-Smoller S, Speliotes EK, Spitz MR, Sucheston L, Taylor H, Tayo BO, Tucker MA, Van Den Berg DJ, Velez Edwards DR, Wang Z, Wiencke JK, Winkler TW, Witte JS, Wrensch M, Wu X, Yang JJ, Levin AM, Young TR, Zakai NA, Cushman M, Zanetti KA, Zhao JH, Zhao W, Zheng Y, Zhou J, Ziegler RG, Zmuda JM, Fernandes JK, Gilkeson GS, Kamen DL, Hunt KJ, Spruill IJ, Ambrosone CB, Ambs S, Arnett DK, Atwood L, Becker DM, Berndt SI, Bernstein L, Blot WJ, Borecki IB, Bottinger EP, Bowden DW, Burke G, Chanock SJ, Cooper RS, Ding J, Duggan D, Evans MK, Fox C, Garvey WT, Bradfield JP, Hakonarson H, Grant SF, Hsing A, Chu L, Hu JJ, Huo D, Ingles SA, John EM, Jordan JM, Kabagambe EK, Kardia SL, Kittles RA, Goodman PJ, Klein EA, Kolonel LN, Le Marchand L, Liu S, McKnight B, Millikan RC, Mosley TH, Padhukasahasram B, Williams LK, Patel SR, Peters U, Pettaway CA, Peyser PA, Psaty BM, Redline S, Rotimi CN, Rybicki BA, Sale MM, Schreiner PJ, Signorello LB, Singleton AB, Stanford JL, Strom SS, Thun MJ, Vitolins M, Zheng W, Moore JH, Williams SM, Zhu X, Zonderman AB, Kooperberg C, Papanicolaou G, Henderson BE, Reiner AP, Hirschhorn JN, Loos RJF, North KE, Haiman CA. A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry. Nat Genet 2013; 45:690-6. [PMID: 23583978 PMCID: PMC3694490 DOI: 10.1038/ng.2608] [Citation(s) in RCA: 206] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2012] [Accepted: 03/18/2013] [Indexed: 11/08/2022]
Abstract
Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.
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Affiliation(s)
- Keri L. Monda
- The Center for Observational Research, Amgen, Inc. Thousand Oaks, CA, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Gary K. Chen
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kira C. Taylor
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Epidemiology and Population Health, University of Louisville, Louisville, KY, USA
| | - Cameron Palmer
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Genetics, Children’s Hospital, Boston, MA, USA
- Division of Endocrinology, Children’s Hospital, Boston, MA, USA
| | - Todd L. Edwards
- Center for Human Genetics Research, Vanderbilt Epidemiology Center, Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | - Leslie A. Lange
- Department of Genetics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, 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
| | - Adebowale A. Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Matthew A. Allison
- Department of Family and Preventive Medicine, University of California San Diego, La Jolla, CA, USA
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Guanji Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Marguerite R. Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Suhn K. Rhie
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Guo Li
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Yongmei Liu
- Department of Epidemiology & Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Youfang Liu
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yingchang Lu
- The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Yan V. Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Mary K. Wojczynski
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Lisa R. Yanek
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Melinda C. Aldrich
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- The Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- Department of Thoracic Surgery, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Adeyinka Ademola
- Department of Surgery, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Christopher I. Amos
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Family and Community Medicine, Geissel School of Medicine, Dartmouth, Hanover, NH
| | | | - Cathryn H. Bock
- Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
| | - Angela Britton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Ulrich Broeckel
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Quiyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- The Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Neil E. Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Chris Carlson
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - John Carpten
- The Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Graham Casey
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Wei-Min Chen
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Fang Chen
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Yii-Der I. Chen
- Medical Genetics Institute, Cedars Sinai Medical Center, Los Angeles, CA, USA
| | | | - Gerhard A. Coetzee
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
- Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ellen Demerath
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Sandra L. Deming-Halverson
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- The Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Ryan W. Driver
- Epidemiology Research Program, American Cancer Society, Atlanta, GA, USA
| | - Patricia Dubbert
- South Central VA Mental Illness, Research, and Clinical Center, Little Rock, AR, USA
- VA Geriatric Research, Education, and Clinical Center, Little Rock, AR, USA
- Division of Health Services Research, Department of Psychiatry, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Mary F. Feitosa
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Barry I. Freedman
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Elizabeth M. Gillanders
- Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health Bethesda, MD, USA
| | - Omri Gottesman
- The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Xiuqing Guo
- Medical Genetics Institute, Cedars Sinai Medical Center, Los Angeles, CA, USA
| | - Talin Haritunians
- Medical Genetics Institute, Cedars Sinai Medical Center, Los Angeles, CA, USA
| | - Tamara Harris
- Laboratory of Epidemiology and Population Science, National Institutes on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Curtis C. Harris
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Anselm JM Hennis
- Department of Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
- Chronic Disease Research Centre, University of the West Indies, Bridgetown, Barbados
- Faculty of Medical Sciences, University of the West Indies, Bridgetown, Barbados
- Ministry of Health, Bridgetown, Barbados
| | - Dena G. Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Lorna H. McNeill
- Department of Health Disparities Research, Division of OVP, Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Center for Community-Engaged Translational Research, Duncan Family Institute, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Timothy D. Howard
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Barbara V. Howard
- MedStar Health Research Institute, Washington, DC, USA
- Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, DC, USA
| | - Virginia J. Howard
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Karen C. Johnson
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Sun J. Kang
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, USA
| | - Brendan J. Keating
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Suzanne Kolb
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Lewis H. Kuller
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh PA, USA
| | - Abdullah Kutlar
- Sickle Cell Center, Department of Medicine, Georgia Health Sciences University, Augusta, GA, USA
| | - Carl D. Langefeld
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Guillaume Lettre
- Montreal Heart Institute, Université de Montréal, Montréal, Québec, Canada
| | - Kurt Lohman
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Vaneet Lotay
- The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Helen Lyon
- Program in Genomics and Endocrinology, Division of Genetics, Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - William Maixner
- Regional Center for Neurosensory Disorders, School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yan A. Meng
- Broad Institute of Harvard and MIT, Metabolic Disease Initiative, Cambridge, MA, USA
| | - Kristine R. Monroe
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Imran Morhason-Bello
- Center for Population and Reproductive Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Adam B. Murphy
- Department of Urology, Northwestern University, Chicago, IL, USA
| | - Josyf C. Mychaleckyj
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Rajiv Nadukuru
- The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Katherine L. Nathanson
- Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Uma Nayak
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Amidou N’Diaye
- Montreal Heart Institute, Université de Montréal, Montréal, Québec, Canada
| | - Barbara Nemesure
- Department of Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Suh-Yuh Wu
- Department of Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
| | - M. Cristina Leske
- Department of Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
| | | | - Marian Neuhouser
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Sarah Nyante
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - Heather Ochs-Balcom
- Department of Social and Preventive Medicine, University at Buffalo, Buffalo NY, USA
| | | | | | - Oladosu Ojengbede
- Center for Population and Reproductive Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | | | - Julie R. Palmer
- Slone Epidemiology Center at Boston University, Boston MA, USA
| | | | - Nicholette D. Palmer
- 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
| | - Michael F. Press
- Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Evandine Rampersaud
- Department of Human Genetics, Miller School of Medicine, University of Miami, FL, USA
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Jorge L. Rodriguez-Gil
- Department of Epidemiology and Public Health, University of Miami Miller School of Medicine, Miami, FL, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | | | - Eric E. Schadt
- Department of Genetics and Genomic Sciences, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Genomics and Multiscale Biology, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ann G. Schwartz
- Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
| | - Daniel A. Shriner
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - David Siscovick
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Shad B. Smith
- Regional Center for Neurosensory Disorders, School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Elizabeth K. Speliotes
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, MI, USA
- Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Division of Gastroenterology. Massachusetts General Hospital, Boston, MA, USA
- The Broad Institute, Cambridge, MA, USA
| | - Margaret R. Spitz
- Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Lara Sucheston
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Herman Taylor
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Bamidele O. Tayo
- Department of Preventive Medicine and Epidemiology, Loyola University Chicago Stritch School of Medicine, Maywood, IL, USA
| | - Margaret A. Tucker
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - David J. Van Den Berg
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Digna R. Velez Edwards
- Center for Human Genetics Research, Vanderbilt Epidemiology Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Epidemiology Center, Department of Obstetrics and Gynecology, Vanderbilt University, Nashville, TN, USA
| | - Zhaoming Wang
- Core Genotype Facility, SAIC-Frederick, Inc., National Cancer Institute-Frederick, Frederick, MD, USA
| | - John K. Wiencke
- Institute for Human Genetics, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Thomas W. Winkler
- The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - John S. Witte
- Institute for Human Genetics, Departments of Epidemiology and Biostatistics and Urology, University of California, San Francisco, San Francisco, CA, USA
| | - Margaret Wrensch
- Institute for Human Genetics, University of California San Francisco
- Department of Neurological Surgery, University of California San Francisco
| | - Xifeng Wu
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - James J. Yang
- Department of Public Health Sciences, Henry Ford Hospital, Detroit, MI, USA
| | - Albert M. Levin
- Department of Public Health Sciences, Henry Ford Hospital, Detroit, MI, USA
| | | | - Neil A. Zakai
- Department of Medicine, University of Vermont College of Medicine, Burlington, VT, USA
| | - Mary Cushman
- Department of Medicine, University of Vermont College of Medicine, Burlington, VT, USA
| | - Krista A. Zanetti
- Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health Bethesda, MD, USA
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jing Hua Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, MI, USA
| | - Yonglan Zheng
- Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Jie Zhou
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Regina G. Ziegler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Joseph M. Zmuda
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh PA, USA
| | - Jyotika K. Fernandes
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Gary S. Gilkeson
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Diane L. Kamen
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Kelly J. Hunt
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Ida J. Spruill
- College of Nursing, Medical University of South Carolina, Charleston, SC, USA
| | - Christine B. Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Donna K. Arnett
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Larry Atwood
- Framingham Heart Study, Boston University School of Medicine, Boston, MA, USA
| | - Diane M. Becker
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sonja I. Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Leslie Bernstein
- Division of Cancer Etiology, Department of Population Science, Beckman Research Institute, City of Hope, Duarte. CA, USA
| | - William J. Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- The Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- International Epidemiology Institute, Rockville, MD, USA
| | - Ingrid B. Borecki
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Erwin P. Bottinger
- The Charles Bronfman Institute of Personalized Medicine, The 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 Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Gregory Burke
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Richard S. Cooper
- Department of Preventive Medicine and Epidemiology, Loyola University Chicago Stritch School of Medicine, Maywood, IL, USA
| | - Jingzhong Ding
- Section on Gerontology and Geriatric Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - David Duggan
- The Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Michele K. Evans
- Health Disparities Research Section, Laboratory of Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Caroline Fox
- National Heart, Lung and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
- National Heart, Lung and Blood Institute’s Center for Population Studies, Framingham, MA, USA
- Division of Endocrinology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - W. Timothy Garvey
- Department Nutrition Sciences, University of Alabama at Birmingham and the Birmingham VA Medical Center, Birmingham, AL, USA
| | - Jonathan P. Bradfield
- The Center for Applied Genomics, The Children’s Hospital of Philadelphia Research Institute, The Children’s Hospital of Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia Research Institute, The Children’s Hospital of Philadelphia, PA, USA
| | - Hakon Hakonarson
- The Center for Applied Genomics, The Children’s Hospital of Philadelphia Research Institute, The Children’s Hospital of Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia Research Institute, The Children’s Hospital of Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Philadelphia PA, USA
| | - Struan F.A. Grant
- The Center for Applied Genomics, The Children’s Hospital of Philadelphia Research Institute, The Children’s Hospital of Philadelphia, PA, USA
- Division of Human Genetics, The Children’s Hospital of Philadelphia Research Institute, The Children’s Hospital of Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Philadelphia PA, USA
| | - Ann Hsing
- Cancer Prevention Institute of California, Fremont, CA, USA
- Division of Epidemiology, Department of Health Research & Policy, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Lisa Chu
- Cancer Prevention Institute of California, Fremont, CA, USA
| | - Jennifer J. Hu
- Department of Epidemiology and Public Health, University of Miami Miller School of Medicine, Miami, FL, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Dezheng Huo
- Department of Health Studies, University of Chicago, IL, USA
| | - Sue A. Ingles
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Esther M. John
- Cancer Prevention Institute of California, Fremont, CA, USA
- Division of Epidemiology, Department of Health Research & Policy, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Joanne M. Jordan
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Edmond K. Kabagambe
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, MI, USA
| | - Rick A. Kittles
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | | | - Eric A. Klein
- Glickman Urologic and Kidney Institute, Cleveland Clinic, Cleveland, OH
| | | | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Simin Liu
- Department of Epidemiology, School of Public Health, University of California at Los Angeles, Los Angeles, CA, USA
| | - Barbara McKnight
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Robert C. Millikan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - Thomas H. Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Badri Padhukasahasram
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI
| | - L. Keoki Williams
- Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI
- Department of Internal Medicine, Henry Ford Health System, Detroit, MI
| | - Sanjay R. Patel
- Division of Sleep Medicine, Brigham and Women’s Hospital, Boston MA, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Curtis A. Pettaway
- Department of Urology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, MI, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology and Health Services, University of Washington, Seattle, WA, USA
- Group Health Research Institute, Group Health Cooperative, Seattle, WA
| | - Susan Redline
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Charles N. Rotimi
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | - Michèle M. Sale
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Medicine, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Pamela J. Schreiner
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Lisa B. Signorello
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
| | - Andrew B. Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Janet L. Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Sara S. Strom
- Department of Epidemiology, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Michael J. Thun
- Epidemiology Research Program, American Cancer Society, Atlanta, GA, USA
| | - Mara Vitolins
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- The Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Jason H. Moore
- Institute for Quantitative Biomedical Sciences, The Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
- Department of Genetics, The Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
- Department of Community and Family Medicine, The Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
| | - Scott M. Williams
- Institute for Quantitative Biomedical Sciences, The Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
- Department of Genetics, The Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Alan B. Zonderman
- Behavioral Epidemiology Section, Laboratory of Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | | | | | | | | | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - George Papanicolaou
- Division of Prevention and Population Sciences, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Brian E. Henderson
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Alex P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Joel N. Hirschhorn
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Genetics, Children’s Hospital, Boston, MA, USA
- Division of Endocrinology, Children’s Hospital, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Ruth JF Loos
- The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kari E. North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
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McCormack S, Grant SFA. Genetics of obesity and type 2 diabetes in African Americans. J Obes 2013; 2013:396416. [PMID: 23577239 PMCID: PMC3614120 DOI: 10.1155/2013/396416] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2012] [Accepted: 02/13/2013] [Indexed: 12/21/2022] Open
Abstract
Obesity and type 2 diabetes are highly prevalent and lead to significant morbidity and mortality. In the United States, the impact of these conditions may be worse on historically underserved minorities, particularly African Americans. Genetic ancestry and differences in physiology are unlikely to be the sole or primary determinants of these disparities. In addition, research in this area has the ethically problematic possibility of conflating race with biology. Despite these important considerations and the challenges of conducting this work, population-based approaches for investigating the etiology of obesity and T2D may yield useful information about the pathophysiology of disease, and have implications that extend to all affected individuals. The purpose of this paper is to describe what is understood about the genetic variation that underlies obesity and T2D in African Americans and other individuals of more recent African descent and to highlight several examples that illustrate how ensuring adequate minority representation in genetic research improves its quality. For a variety of reasons a number of unique insights have been possible as a result of these efforts.
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Affiliation(s)
- Shana McCormack
- Division of Endocrinology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Struan F. A. Grant
- Division of Human Genetics, The Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
- Center for Applied Genomics, The Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- *Struan F. A. Grant:
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Jacobsson JA, Schiöth HB, Fredriksson R. The impact of intronic single nucleotide polymorphisms and ethnic diversity for studies on the obesity gene FTO. Obes Rev 2012; 13:1096-109. [PMID: 22931202 DOI: 10.1111/j.1467-789x.2012.01025.x] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
In 2007, the first common genetic variants were identified, which undoubtedly affect our susceptibility to obesity. These variants are located in the fat mass and obesity-associated gene FTO. Since then, over 50 loci for common obesity have been identified. As the research on these loci is still at an early stage, there is a great need to review, for clarification purposes, the current research on FTO, as this is likely to influence future studies. Based on the current knowledge, FTO seems to be directly involved in the regulation of energy intake, but there is an urgent need for the identification of regulatory polymorphisms. Thus, herein, we discuss current knowledge and highlight putative functional regions in FTO based on published data and computer-based analysis.
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Affiliation(s)
- J A Jacobsson
- Department of Neuroscience, Unit of Functional Pharmacology, Uppsala University, Uppsala, Sweden.
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Schjoldager KTBG, Clausen H. Site-specific protein O-glycosylation modulates proprotein processing - deciphering specific functions of the large polypeptide GalNAc-transferase gene family. BIOCHIMICA ET BIOPHYSICA ACTA 2012; 1820:2079-94. [PMID: 23022508 DOI: 10.1016/j.bbagen.2012.09.014] [Citation(s) in RCA: 149] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2012] [Revised: 09/17/2012] [Accepted: 09/19/2012] [Indexed: 01/18/2023]
Abstract
BACKGROUND Posttranslational modifications (PTMs) greatly expand the function and regulation of proteins, and glycosylation is the most abundant and diverse PTM. Of the many different types of protein glycosylation, one is quite unique; GalNAc-type (or mucin-type) O-glycosylation, where biosynthesis is initiated in the Golgi by up to twenty distinct UDP-N-acetyl-α-d-galactosamine:polypeptide N-acetylgalactosaminyltransferases (GalNAc-Ts). These GalNAc-Ts are differentially expressed in cells and have different (although partly overlapping) substrate specificities, which provide for both unique functions and considerable redundancy. Recently we have begun to uncover human diseases associated with deficiencies in GalNAc-T genes (GALNTs). Thus deficiencies in individual GALNTs produce cell and protein specific effects and subtle distinct phenotypes such as hyperphosphatemia with hyperostosis (GALNT3) and dysregulated lipid metabolism (GALNT2). These phenotypes appear to be caused by deficient site-specific O-glycosylation that co-regulates proprotein convertase (PC) processing of FGF23 and ANGPTL3, respectively. SCOPE OF REVIEW Here we summarize recent progress in uncovering the interplay between human O-glycosylation and protease regulated processing and describes other important functions of site-specific O-glycosylation in health and disease. MAJOR CONCLUSIONS Site-specific O-glycosylation modifies pro-protein processing and other proteolytic events such as ADAM processing and thus emerges as an important co-regulator of limited proteolytic processing events. GENERAL SIGNIFICANCE Our appreciation of this function may have been hampered by our sparse knowledge of the O-glycoproteome and in particular sites of O-glycosylation. New strategies for identification of O-glycoproteins have emerged and recently the concept of SimpleCells, i.e. human cell lines made deficient in O-glycan extension by zinc finger nuclease gene targeting, was introduced for broad O-glycoproteome analysis.
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Graff M, North KE, Mohlke KL, Lange LA, Luo J, Harris KM, Young KL, Richardson AS, Lange EM, Gordon-Larsen P. Estimation of genetic effects on BMI during adolescence in an ethnically diverse cohort: The National Longitudinal Study of Adolescent Health. Nutr Diabetes 2012; 2:e47. [PMID: 23168566 PMCID: PMC3461356 DOI: 10.1038/nutd.2012.20] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2012] [Accepted: 08/18/2012] [Indexed: 12/18/2022] Open
Abstract
OBJECTIVE The contribution of genetic variants to body mass index (BMI) during adolescence across multiethnic samples is largely unknown. We selected genetic loci associated with BMI or obesity in European-descent samples and examined them in a multiethnic adolescent sample. DESIGN AND SAMPLE In 5103 European American (EA), 1748 African American (AfA), 1304 Hispanic American (HA) and 439 Asian American (AsA) participants of the National Longitudinal Study of Adolescent Health (Add Health; ages 12-21 years, 47.5% male), we assessed the association between 41 established obesity-related single-nucleotide polymorphisms (SNPs) with BMI using additive genetic models, stratified by race/ethnicity, and in a pooled meta-analysis sample. We also compared the magnitude of effect for BMI-SNP associations in EA and AfA adolescents to comparable effect estimates from 11 861 EA and AfA adults in the Atherosclerosis Risk in Communities study (ages 45-64 years, 43.2% male). RESULTS Thirty-five of 41 BMI-SNP associations were directionally consistent with published studies in European populations, 18 achieved nominal significance (P<0.05; effect sizes from 0.19 to 0.71 kg m(-2) increase in BMI per effect allele), while 4 (FTO, TMEM18, TFAP2B, MC4R) remained significant after Bonferroni correction (P<0.0015). Of 41 BMI-SNP associations in AfA, HA and AsA adolescents, nine, three and five, respectively, were directionally consistent and nominally significant. In the pooled meta-analysis, 36 of 41 effect estimates were directionally consistent and 21 of 36 were nominally significant. In EA adolescents, BMI effect estimates were larger (P<0.05) for variants near TMEM18, PTER and MC4R and smaller for variants near MTIF3 and NRXN3 compared with EA adults. CONCLUSION Our findings suggest that obesity susceptibility loci may have a comparatively stronger role during adolescence than during adulthood, with variation across race/ethnic subpopulation.
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Affiliation(s)
- M Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
| | - K E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - K L Mohlke
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - L A Lange
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - J Luo
- Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - K M Harris
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
- Department of Sociology, University of North Carolina, Chapel Hill, NC, USA
| | - K L Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
| | - A S Richardson
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Nutrition, University of North Carolina, Chapel Hill, NC, USA
| | - E M Lange
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - P Gordon-Larsen
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Nutrition, University of North Carolina, Chapel Hill, NC, USA
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