WHR Adjusted For BMI Research Articles

Adipose Tissue Gene Expression Associations Reveal Hundreds of Candidate Genes for Cardiometabolic Traits

Genome-wide association studies (GWASs) have identified thousands of genetic loci associated with cardiometabolic traits including type 2 diabetes (T2D), lipid levels, body fat distribution, and adiposity, although most causal genes remain unknown. We used subcutaneous adipose tissue RNA-seq data from 434 Finnish men from the METSIM study to identify 9,687 primary and 2,785 secondary cis-expression quantitative trait loci (eQTL; <1 Mb from TSS, FDR < 1%). Compared to primary eQTL signals, secondary eQTL signals were located further from transcription start sites, had smaller effect sizes, and were less enriched in adipose tissue regulatory elements compared to primary signals. Among 2,843 cardiometabolic GWAS signals, 262 colocalized by LD and conditional analysis with 318 transcripts as primary and conditionally distinct secondary cis-eQTLs, including some across ancestries. Of cardiometabolic traits examined for adipose tissue eQTL colocalizations, waist-hip ratio (WHR) and circulating lipid traits had the highest percentage of colocalized eQTLs (15% and 14%, respectively). Among alleles associated with increased cardiometabolic GWAS risk, approximately half (53%) were associated with decreased gene expression level. Mediation analyses of colocalized genes and cardiometabolic traits within the 434 individuals provided further evidence that gene expression influences variant-trait associations. These results identify hundreds of candidate genes that may act in adipose tissue to influence cardiometabolic traits.

Comprehensive identification of pleiotropic loci for body fat distribution using the NHGRI-EBI Catalog of published genome-wide association studies.

We conducted a hypothesis-free cross-trait analysis for waist-to-hip ratio adjusted for body mass index (WHRadjBMI ) loci derived through genome-wide association studies (GWAS). Summary statistics from published GWAS were used to capture all WHRadjBMI single-nucleotide polymorphisms (SNPs), and their proxy SNPs were identified. These SNPs were used to extract cross-trait associations between WHRadjBMI SNPs and other traits through the NHGRI-EBI GWAS Catalog. Pathway analysis was conducted for pleiotropic WHRadjBMI SNPs. We found 160 WHRadjBMI SNPs and 3675 proxy SNPs. Cross-trait analysis identified 239 associations, of which 100 were for obesity traits. The remaining 139 associations were filtered down to 101 unique linkage disequilibrium block associations, which were grouped into 13 categories: lipids, red blood cell traits, white blood cell counts, inflammatory markers and autoimmune diseases, type 2 diabetes-related traits, adiponectin, cancers, blood pressure, height, neuropsychiatric disorders, electrocardiography changes, urea measurement, and others. The highest number of cross-trait associations were found for triglycerides (n=10), high-density lipoprotein cholesterol (n=9), and reticulocyte counts (n=8). Pathway analysis for WHRadjBMI pleiotropic SNPs found immune function pathways as the top canonical pathways. Results from our original methodology indicate a novel genetic association between WHRadjBMI and reticulocyte counts and highlight the pleiotropy between abdominal obesity, immune pathways, and other traits.

Meta-analysis of genome-wide association studies for body fat distribution in 694649 individuals of European ancestry.

More than one in three adults worldwide is either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, are more informative for predicting risk of obesity sequelae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio (WHR) adjusted for body mass index (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.

A fine-mapping study of central obesity loci incorporating functional annotation and imputation.

A recent genome-wide association study (GWAS) of central obesity identified 27 loci, from sex-combined analysis, associated with waist-to-hip ratio adjusted for body-mass index (WHRadjBMI) in European-ancestry individuals. Nevertheless, the identified variants may not be the biological causal ones due to the presence of linkage disequilibrium (LD). To better understand the mechanisms underlying the identified loci from the GWAS meta-analysis, we first imputed summary statistics at GWAS loci to increase genetic resolution, and then we applied a Bayesian statistical fine-mapping method through PAINTOR, incorporating LD structure and functional annotations to select and prioritize the most plausible causal variants across WHRadjBMI-associated regions. Using adipose tissue- and cell-specific annotations that showed significant associations with WHRadjBMI, we identified 33 single-nucleotide polymorphisms (SNPs) from 27 sex-combined fine-mapping loci with posterior probability of causality greater than 0.9. Six of the selected 33 SNPs belong to at least one of the top five identified annotations. SNPs rs1440372 (SMAD6) and rs12608504 (JUND) are particularly important since they not only have associated functional annotations but are also GWA hits in the original study. Incorporation of functional annotations helps identify additional plausible causal variants, such as rs2213731 (DNM3-PIGC) and rs4531856 (JUND), that did not reach genome-wide significance in GWAS. Our results provide promising candidates for future functional validation experiments.

Genetically driven adiposity traits increase the risk of coronary artery disease independent of blood pressure, dyslipidaemia, glycaemic traits.

Adiposity has been associated with the risk of coronary artery disease (CAD) in observational studies, but their association may differ according to specific characteristics of studies. In Mendelian randomization (MR) analyses, genetic variants are used as instrumental variables (IVs) of exposures to examine causal effects to overcome confounding factors and reverse causation. We performed MR analyses for adiposity (n = 322,154) on risk of CAD (60,801 cases and 123,504 controls) based on the currently largest genome-wide association studies. The estimated associations between adiposity traits and CAD were calculated by an inverse-variance weighted method with and without excluding the IVs, which are associated with the well-known risk factors of CAD. Genetic variants are identified to be associated with the well-known risk factors of CAD by a cross-phenotype meta-analysis method. Our results furnished strong evidence for a causal role of adiposity in risk of CAD, with the odds ratios (ORs) for CAD being 1.53 (95% CI 1.36-1.72) for body mass index (BMI), 1.48 (1.20-1.96) for waist-hip ratio (WHR), and 1.34 (1.07-1.59) for WHR adjusted for BMI (WHRadjBMI), respectively. After excluding mediators-associated IVs from the MR analyses, the corresponding ORs were 1.46 (1.28-1.67) for BMI, 1.39 (1.01-1.93) for WHR, and 1.38 (1.04-1.84) for WHRadjBMI, respectively. Furthermore, our results suggested that central adiposity and general adiposity might pose a similar risk for CAD. In summary, our data supported that genetically driven adiposity traits imposed the risk of CAD independent of blood pressure, dyslipidaemia, glycaemic traits, and type 2 diabetes.

A joint view on genetic variants for adiposity differentiates subtypes with distinct metabolic implications

The problem of the genetics of related phenotypes is often addressed by analyzing adjusted-model traits, but such traits warrant cautious interpretation. Here, we adopt a joint view of adiposity traits in ~322,154 subjects (GIANT consortium). We classify 159 signals associated with body mass index (BMI), waist-to-hip ratio (WHR), or WHR adjusted for BMI (WHRadjBMI) at P < 5 × 10−8, into four classes based on the direction of their effects on BMI and WHR. Our classes help differentiate adiposity genetics with respect to anthropometry, fat depots, and metabolic health. Class-specific Mendelian randomization reveals that variants associated with both WHR-decrease and BMI increase are linked to metabolically rather favorable adiposity through beneficial hip fat. Class-specific enrichment analyses implicate digestive systems as a pathway in adiposity genetics. Our results demonstrate that WHRadjBMI variants capture relevant effects of “unexpected fat distribution given the BMI” and that a joint view of the genetics underlying related phenotypes can inform on important biology.

Genetic risk scores for body fat distribution attenuate weight loss in women during dietary intervention.

The well-established link between body fat distribution and metabolic health has been suggested to act through an impact on the remodeling capacity of the adipose tissue. Remodeling of the adipose tissue has been shown to affect body fat distribution and might affect the ability to lose weight. We aimed to study the effect of weighted genetic risk scores (GRSs) on weight loss based on single-nucleotide polymorphisms (SNPs) associated with waist-hip-ratio adjusted for body mass index (WHRadjBMI). We included 707 participants (533 women and 174 men) from the NUGENOB multi-center 10-week diet intervention study with weekly weight measurements. We created 3 GRSs, one including all reported WHRadjBMI SNPs (GRStotal), one including only SNPs with genome-wide significance in women or with significantly greater effect in women (GRSwomen), and one excluding SNPs in the GRSwomen (GRSmen). The data were analyzed in a mixed linear model framework. The GRStotal and GRSwomen attenuated weight loss in women. The effect was strongest for the GRSwomen with an effect of 2.21 g per risk allele per day (95% confidence intereval (CI) (0.90;3.52), P=0.0009). Adjustment for WHR, basal metabolic rate or diet compliance did not affect the result. The GRSs had no effect on weight loss in men. The VEGFA rs1358980-T strongly attenuated weight loss in both men and women (β=15.95 g per risk allele per day, (3.16;26.74), P=0.013) and (β=15.95 g per risk allele per day, (2.58;13.53), P=0.004), respectively). Our findings suggest that genetic variants influencing body fat distribution attenuate weight loss in women independently on the effect on WHR. The stronger effect of the GRSwomen implies heterogenic effects of the WHRadjBMI variants on weight loss. A strong effect of rs1358980-T in the VEGFA locus suggests that angiogenesis plays a role, but this needs confirmation from functional studies.

Genetic variants associated with type 2 diabetes and adiposity and risk of intracranial and abdominal aortic aneurysms.

Epidemiological studies show that type 2 diabetes (T2D) is inversely associated with intracranial aneurysms (IA) and abdominal aortic aneurysms (AAA). Although adiposity has not been considered a risk factor for IA, there have been inconsistent reports relating adiposity to AAA risk. We assessed whether these observations have a genetic, causal basis. To this end, we extracted genotypes of validated single-nucleotide polymorphisms associated with T2D (n=65), body mass index (BMI) (n=97) and waist-hip ratio adjusted for BMI (WHRadjBMI) (n=47) from genotype data collected in 717 IA cases and 1988 controls, and in 818 AAA cases and 3004 controls, all of Dutch descent. For each of these three traits, we computed genetic risk scores (GRS) for each individual in these case-control data sets by summing the number of risk alleles weighted by their published effect size, and tested whether these GRS were associated with risk of aneurysm. We divided the cohorts into GRS quartiles, and compared IA and AAA risk in the highest with the lowest GRS quartile using logistic regression. We found no evidence for association in IA or AAA risk between top and bottom quartiles for the genetic risk scores for T2D, BMI and WHRadjBMI. However, additional Mendelian randomization analyses suggested a trend to potentially causal associations between BMI and WHRadjBMI and risk of AAA. Overall, our results do not support epidemiological observations relating T2D to aneurysm risk, but may indicate a potential role of adiposity in AAA that requires further investigation.

Multivariate Analysis of Anthropometric Traits Using Summary Statistics of Genome-Wide Association Studies from GIANT Consortium.

Meta-analysis of single trait for multiple cohorts has been used for increasing statistical power in genome-wide association studies (GWASs). Although hundreds of variants have been identified by GWAS, these variants only explain a small fraction of phenotypic variation. Cross-phenotype association analysis (CPASSOC) can further improve statistical power by searching for variants that contribute to multiple traits, which is often relevant to pleiotropy. In this study, we performed CPASSOC analysis on the summary statistics from the Genetic Investigation of ANthropometric Traits (GIANT) consortium using a novel method recently developed by our group. Sex-specific meta-analysis data for height, body mass index (BMI), and waist-to-hip ratio adjusted for BMI (WHRadjBMI) from discovery phase of the GIANT consortium study were combined using CPASSOC for each trait as well as 3 traits together. The conventional meta-analysis results from the discovery phase data of GIANT consortium studies were used to compare with that from CPASSOC analysis. The CPASSOC analysis was able to identify 17 loci associated with anthropometric traits that were missed by conventional meta-analysis. Among these loci, 16 have been reported in literature by including additional samples and 1 is novel. We also demonstrated that CPASSOC is able to detect pleiotropic effects when analyzing multiple traits.

Interactions between genetic variants associated with adiposity traits and soft drinks in relation to longitudinal changes in body weight and waist circumference

Background: Intake of sugar-sweetened beverages is associated with obesity, and this association may be modified by a genetic predisposition to obesity.Objective: We examined the interactions between a molecular genetic predisposition to various aspects of obesity and the consumption of soft drinks, which are a major part of sugar-sweetened beverages, in relation to changes in adiposity measures.Design: A total of 4765 individuals were included in the study. On the basis of 50 obesity-associated single nucleotide polymorphisms that are associated with body mass index (BMI), waist circumference (WC), or the waist-to-hip ratio adjusted for BMI (WHRBMI), the following 4 genetic predisposition scores (GRSs) were constructed: a complete genetic predisposition score including all 50 single nucleotide polymorphisms (GRSComplete), a genetic predisposition score including BMI-associated single nucleotide polymorphisms (GRSBMI), a genetic predisposition score including waist circumference–associated single nucleotide polymorphisms (GRSWC), and a genetic predisposition score including the waist-to-hip ratio adjusted for BMI–associated single nucleotide polymorphisms (GRSWHR). Associations between soft drink intake and the annual change (Δ) in body weight (BW), WC, or waist circumference adjusted for BMI (WCBMI) and possible interactions with the GRSs were examined with the use of linear regression analyses and meta-analyses.Results: For each soft drink serving per day, soft drink consumption was significantly associated with a higher ΔBW of 0.07 kg/y (95% CI: 0.01, 0.13 kg/y; P = 0.020) but not with the ΔWC or ΔWCBMI. In analyses of the ΔBW, we showed an interaction only with the GRSWC (per risk allele for each soft drink serving per day: −0.06 kg/y; 95% CI: −0.10, −0.02 kg/y; P = 0.006). In analyses of the ΔWC, we showed interactions only with the GRSBMI and GRSComplete [per risk allele for each soft drink serving per day: 0.05 cm/y (95% CI: 0.02, 0.09 cm/y; P = 0.001) and 0.05 cm/y (95% CI: 0.02, 0.07 cm/y; P = 0.001), respectively]. Nearly identical results were observed in analyses of the ΔWCBMI.Conclusions: A genetic predisposition to a high WC may attenuate the association between soft drink intake and BW gain. A genetic predisposition to high BMI as well as a genetic predisposition to high BMI, WC, and WHRBMI combined may strengthen the association between soft drink intake and WC gain. However, the public health impact may be limited.

Effects of Genetic Loci Associated with Central Obesity on Adipocyte Lipolysis.

ObjectivesNumerous genetic loci have been associated with measures of central fat accumulation, such as waist-to-hip ratio adjusted for body mass index (WHRadjBMI). However the mechanisms by which genetic variations influence obesity remain largely elusive. Lipolysis is a key process for regulation of lipid storage in adipocytes, thus is implicated in obesity and its metabolic complications. Here, genetic variants at 36 WHRadjBMI-associated loci were examined for their influence on abdominal subcutaneous adipocyte lipolysis.Subjects and MethodsFasting subcutaneous adipose tissue biopsies were collected from 789 volunteers (587 women and 202 men, body mass index (BMI) range 17.7–62.3 kg/m2). We quantified subcutaneous adipocyte lipolysis, both spontaneous and stimulated by the catecholamine isoprenaline or a cyclic AMP analogue. DNA was extracted from peripheral blood mononuclear cells and genotyping of SNPs associated with WHRadjBMI conducted. The effects on adipocyte lipolysis measures were assessed for SNPs individually and combined in a SNP score.ResultsThe WHRadjBMI-associated loci CMIP, PLXND1, VEGFA and ZNRF3-KREMEN1 demonstrated nominal associations with spontaneous and/or stimulated lipolysis. Candidate genes in these loci have been reported to influence NFκB-signaling, fat cell size and Wnt signalling, all of which may influence lipolysis.SignificanceThis report provides evidence for specific WHRadjBMI-associated loci as candidates to modulate adipocyte lipolysis. Additionally, our data suggests that genetically increased central fat accumulation is unlikely to be a major cause of altered lipolysis in abdominal adipocytes.

Abstract MP79: Identification of Novel Loci Associated with Anthropometric Traits in African Ancestry Populations

Introduction: African Americans have the highest prevalence of obesity in the U.S. Our prior work on HapMap imputed genome-wide association studies (GWAS) from the African Ancestry Anthropometry Genetics Consortium (AAAGC) revealed seven genome-wide significant loci for body mass index (BMI). Hypothesis: In this study, we extended to use genome-wide imputation to the cosmopolitan 1000 Genomes Phase 1 reference panel to examine individuals of African ancestry for association with BMI (N=53,493), waist-to-hip ratio adjusted for BMI (WHRadjBMI) (N=23,692) and height (N=53,362) in the discovery and replication stages. Methods: In each study, traits were stratified by gender and transformed to normality and adjusted for age, study specific covariates and principal components for single variant association test under an additive model. In the discovery stage, meta-analyses using fixed-effects inverse variance weighted method were performed to combine association results in all and sex-stratified samples. Variants with P&lt;1E-4 were selected for subsequent replications in both individuals of African ancestry and European ancestry, the latter results were obtained by imputation of summary statistics from the GIANT consortium (N=322,154 for BMI, 210,062 for WHRadjBMI, and 253,252 for height). Results: For BMI, we observed genome-wide significant associations (P&lt;5E-8) at seven established loci (near SEC16B, TMEM18, GNPDA2, GALNT10, KLHL32, FTO and MC4R) in meta-analysis of all African ancestry individuals from the discovery and replication stages. Sex-stratified meta-analysis revealed two novel loci near IRX4-IRX2 in women, and near MLC1 in men, respectively. Meta-analysis of all individuals from African and European ancestry revealed an additional novel locus near ARAP1. For WHRadjBMI, we observed genome-wide significant associations at one established locus (ADAMTS9) in all African ancestry individuals, and three novel loci (near SSX2IP, RREB1 and PDE3B) in women. For height, we observed 29 established loci and three novel loci (near NCOA2, P4HA1 and TGFB3) in all African ancestry individuals, and three novel loci (near CRB1, MIR4268 and LINC00704) in women. Among 12 lead variants at novel loci associated with anthropometry traits, four variants are low frequencies in our African ancestry populations (0.005&lt;MAF &lt;0.05). On the contrary, all but one of the lead variants at established loci were common. Conclusions: We identified 12 novel loci associated with anthropometry traits in sex-combined and sex-stratified analyses of African ancestry populations and additional European populations. Our findings support that imputation to higher density reference panels such as 1000 Genomes improves the power to detect associations at low frequency variants, which is particularly useful for African ancestry populations with a low degree of linkage disequilibrium.

Interaction between genetic predisposition to adiposity and dietary protein in relation to subsequent change in body weight and waist circumference.

BackgroundGenetic predisposition to adiposity may interact with dietary protein in relation to changes of anthropometry.ObjectiveTo investigate the interaction between genetic predisposition to higher body mass index (BMI), waist circumference (WC) or waist-hip ratio adjusted for BMI (WHRBMI) and dietary protein in relation to subsequent change in body weight (ΔBW) or change in WC (ΔWC).DesignThree different Danish cohorts were used. In total 7,054 individuals constituted the study population with information on diet, 50 single-nucleotide polymorphisms (SNPs) associated with BMI, WC or WHRBMI, as well as potential confounders. Mean follow-up time was ∼5 years. Four genetic predisposition-scores were based on the SNPs; a complete-score including all selected adiposity- associated SNPs, and three scores including BMI, WC or WHRBMI associated polymorphisms, respectively. The association between protein intake and ΔBW or ΔWC were examined and interactions between SNP-score and protein were investigated. Analyses were based on linear regressions using macronutrient substitution models and meta-analyses.ResultsWhen protein replaced carbohydrate, meta-analyses showed no associations with ΔBW (41.0 gram/y/5 energy% protein, [95% CI: −32.3; 114.3]) or ΔWC (<−0.1 mm/y/5 energy % protein, [−1.1; 1.1]). Similarly, there were no interactions for any SNP-scores and protein for either ΔBW (complete SNP-score: 1.8 gram/y/5 energy% protein/risk allele, [−7.0; 10.6]) or ΔWC (complete SNP-score: <0.1 mm/y/5 energy% protein/risk allele, [−0.1; 0.1]). Similar results were seen when protein replaced fat.ConclusionThis study indicates that the genetic predisposition to general and abdominal adiposity, assessed by gene-scores, does not seem to modulate the influence of dietary protein on ΔBW or ΔWC.