Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation

Chu, Audrey Y.; Deng, Xuan; Fisher, Virginia; Drong, Alexander W.; Zhang, Yang; Feitosa, Mary F.; Liu, Ching‐Ti; Weeks, Olivia; Choh, Audrey C.; Duan, Qing; Dyer, Thomas D.; Eicher, John D.; Guo, Xiuqing; Heard‐Costa, Nancy L.; Kacprowski, Tim; Kent, Jack W.; Lange, Leslie A.; Liu, Xinggang; Lohman, Kurt; Lu, Lingyi; Mahajan, Anubha; O’Connell, Jeffrey R.; Parihar, Ankita; Peralta, Juan M.; Smith, Albert V.; Zhang, Yi; Homuth, Georg; Kissebah, Ahmed H.; Kullberg, Joel; Laqua, René; Launer, Lenore J.; Nauck, Matthias; Olivier, Michael; Peyser, Patricia A.; Terry, James G.; Wojczynski, Mary K.; Yao, Jie; Bielak, Lawrence F.; Blangero, John; Borecki, Ingrid B.; Bowden, Donald W.; Carr, J. Jeffrey; Czerwinski, Stefan A.; Ding, Jingzhong; Friedrich, Nele; Gudnason, Vilmundur; Harris, Tamara B.; Ingelsson, Erik; Johnson, Andrew D.; Kardia, Sharon L.R.; Langefeld, Carl D.; Lind, Lars; Liu, Yongmei; Mitchell, Braxton D.; Morris, Andrew P.; Mosley, Thomas H.; Rotter, Jerome I.; Shuldiner, Alan R.; Towne, Bradford; Völzke, Henry; Wallaschofski, Henri; Wilson, James G.; Allison, Matthew A.; Lindgren, Cecilia M.; Goessling, Wolfram; Cupples, L. Adrienne; Steinhauser, Matthew L.; Fox, Caroline S.

doi:10.1038/ng.3738

Cited by 123 publications

(137 citation statements)

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“…We calculated Pearson's r correlations between z-scores in WHRadjBMI (calculated by dividing the SNP beta by the standard error) and SNP z-scores reported in Chu et al 20 We evaluated significance of the correlation by performing a t-test (implemented as cor.test() in R). Correlations were considered significant if P-value < 0.05/3 sample groups/9 phenotypes = 1.9 x 10 -3 .…”

Section: Comparison With Genome-wide Analysis Of Depot-specific Traitsmentioning

confidence: 99%

“…Finally, we tested the index SNPs from each of the meta-analyses (combined and sex-specific) in a recent GWAS of CT and MRI image based measures of ectopic and subcutaneous fat depots. 20 Adjusting for the three sample groups and the 8 depots examined in the imaging-based GWAS (p < 0.05/24 = 2.1 x 10 -3 ), the alleles associated with higher WHRadjBMI were collectively associated with lower measures of subcutaneous fat, and higher measures of visceral fat, including pericardial and visceral adipose tissue ( Supplementary Fig. 9).…”

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confidence: 99%

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Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry

Pulit

Stoneman

Morris

et al. 2018

Preprint

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1 One in four adults worldwide are either overweight or obese. Epidemiological studies indicate that the 2 location and distribution of excess fat, rather than general adiposity, is most informative for predicting risk of 3 obesity sequellae, including cardiometabolic disease and cancer. We performed a genome-wide association 4 study meta-analysis of body fat distribution, measured by waist-to-hip ratio adjusted for BMI 5 (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger 6 in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of 7 individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 8 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, 9 will inform the biology of body fat distribution and its relationship with disease. 10 11 Introduction 12One in four adults worldwide are either overweight or obese (1,2) and are at increased risk of metabolic disease. 13While higher adiposity increases morbidity and mortality (1,3), epidemiological studies indicate that the location 14 and distribution of excess fat within particular depots is more informative than general adiposity for predicting 15 disease risk. Independent of their overall body mass index (BMI), individuals with higher central adiposity have 16 increased risk of cardiometabolic diseases, including type 2 diabetes (T2D) and stroke (4,5); in contrast, individuals 17 with higher gluteal adiposity have lower risk of such outcomes.(5) Previous studies indicate that fat distribution, as 18 assessed by waist-to-hip ratio (WHR), is a trait with a strong heritable component, independent of overall adiposity 19 (measured by BMI), with twin-based heritability estimates ranging between 30-60% (5,6) and narrow-sense 20 heritability estimates have been estimated at ~50% in women and ~20% in men (5). The most recent genome-wide 21 association study in 224,459 samples implicated 49 loci associated with WHR adjusted for BMI (5), and recent 22Mendelian randomisation studies using known WHR-associated genetic variants showed putative causal effects of 23 higher WHR on T2D and coronary artery disease independently of BMI (7). 25 Results 26With the goal of pinpointing genetic variants associated to body shape and fat distribution and motivated by the 27 recent release of genetic data from half a million individuals (8), we performed a meta-analysis of WHR adjusted for 28 BMI (WHRadjBMI). WHRadjBMI is an easily-measured fat distribution phenotype that correlates well with 29 imaging-based fat distribution measures (9). We performed genome-wide association studies (GWAS) of 30 WHRadjBMI in the UK Biobank data set (8), a collection of 484,563 samples with densely-imputed genotype data, 31 using a linear mixed model (10) to account for relatedness and ancestral heterogeneity. We then combined the 32 results with publicly-available GWAS data generated by the GIANT consortium ...

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Section: Comparison With Genome-wide Analysis Of Depot-specific Traitsmentioning

confidence: 99%

mentioning

confidence: 99%

Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry

Pulit

Stoneman

Morris

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Over the past decade, GWAS have led to the identification of thousands of genetic loci robustly associated with a wide range of diseases and traits , including >500 genetic loci associated with adiposity traits , mainly with BMI (as a proxy of overall obesity) and waist‐to‐hip ratio (WHR; proxy of fat distribution) , but also with more refined adiposity traits, such as body fat percentage (BF%) , circulating leptin levels , specific fat depots, such as visceral and subcutaneous adipose tissue (VAT, SAT) , and extreme and early‐onset obesity . In addition, GWAS have also identified hundreds of loci associated with cardiometabolic traits, including glycemic traits , circulating lipid levels , blood pressure , coronary artery disease (CAD) and type 2 diabetes .…”

Section: Using Human Genetics To Identify New Pathways and Mechanismsmentioning

confidence: 99%

Genes that make you fat, but keep you healthy

Loos

Kilpeläinen

2018

J Intern Med

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Obesity prevalence continues to rise worldwide, posing a substantial burden on people's health. However, up to 45% of obese individuals do not suffer from cardiometabolic complications, also called the metabolically healthy obese (MHO). Concurrently, up to 30% of normal-weight individuals demonstrate cardiometabolic risk factors that are generally observed in obese individuals, the metabolically obese normal weight (MONW). Besides lifestyle, environmental factors and demographic factors, innate biological mechanisms are known to contribute to the aetiology of the MHO and MONW phenotypes, as well. Experimental studies in animal models have shown that adipose tissue expandability, fat distribution, adipogenesis, adipose tissue vascularization, inflammation and fibrosis, and mitochondrial function are the main mechanisms that uncouple adiposity from its cardiometabolic comorbidities. We reviewed current genetic association studies to expand insights into the biology of MHO/MONW phenotypes. At least four genetic loci were identified through genome-wide association studies for body fat percentage (BF%) of which the BF%-increasing allele was associated with a protective effect on glycemic and lipid outcomes. For some, this association was mediated through favourable effects on body fat distribution. Other studies that characterized the genetic susceptibility of insulin resistance found that a higher susceptibility was associated with lower overall adiposity due to less fat accumulation at hips and legs, suggesting that an impaired capacity to store fat subcutaneously or a preferential storage in the intra-abdominal cavity may be metabolically harmful. Clearly, more work remains to be done in this field, first through gene discovery and subsequently through functional follow-up of identified genes.

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“…Additional birth weight and length GWAS summary statistics were obtained from the Early Growth Genetics Consortium (EGG) consortium (27,28). GWAS results for visceral and subcutaneous adipose tissue were available from VATGen consortium (29), as well as results for percent body fat (30) and heart rate (31). Finally serum laboratory values were available for the following traits: lipid levels (HDL cholesterol, LDL cholesterol, total cholesterol, triglycerides) (32), leptin with and without BMI adjustment (33), adiponectin adjusted for BMI (34), urate (35), N3-fatty acids (36), N6-fatty acids (37), plasma phospholipid fatty acids in the de novo lipogenesis pathway (38), and very long-chain saturated fatty acids (39).…”

Section: Variant and Trait Selectionmentioning

confidence: 99%

Clustering of Type 2 Diabetes Genetic Loci by Multi-Trait Associations Identifies Disease Mechanisms and Subtypes

Udler

Kim

Grotthuss

et al. 2018

Preprint

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Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation

Cited by 123 publications

References 43 publications

Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry

Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry

Genes that make you fat, but keep you healthy

Clustering of Type 2 Diabetes Genetic Loci by Multi-Trait Associations Identifies Disease Mechanisms and Subtypes

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