A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.Peer reviewe

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.Peer reviewe

A comprehensive investigation of variants in genes encoding adiponectin (ADIPOQ) and its receptors (ADIPOR1/R2), and their association with serum adiponectin, type 2 diabetes, insulin resistance and the metabolic syndrome

Background: Low levels of serum adiponectin have been linked to central obesity, insulin resistance, metabolic syndrome, and type 2 diabetes. Variants in ADIPOQ, the gene encoding adiponectin, have been shown to influence serum adiponectin concentration, and along with variants in the adiponectin receptors (ADIPOR1 and ADIPOR2) have been implicated in metabolic syndrome and type 2 diabetes. This study aimed to comprehensively investigate the association of common variants in ADIPOQ, ADIPOR1 and ADIPOR2 with serum adiponectin and insulin resistance syndromes in a large cohort of European-Australian individuals.Methods: Sixty-four tagging single nucleotide polymorphisms in ADIPOQ, ADIPOR1 and ADIPOR2 were genotyped in two general population cohorts consisting of 2,355 subjects, and one cohort of 967 subjects with type 2 diabetes. The association of tagSNPs with outcomes were evaluated using linear or logistic modelling. Meta-analysis of the three cohorts was performed by random-effects modelling.Results: Meta-analysis revealed nine genotyped tagSNPs in ADIPOQ significantly associated with serum adiponectin across all cohorts after adjustment for age, gender and BMI, including rs10937273, rs12637534, rs1648707, rs16861209, rs822395, rs17366568, rs3774261, rs6444175 and rs17373414. The results of haplotype-based analyses were also consistent. Overall, the variants in the ADIPOQ gene explaine

Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function

Pulmonary function measures reflect respiratory health and are used in the diagnosis of chronic obstructive pulmonary disease. We tested genome-wide association with forced expiratory volume in 1 second and the ratio of forced expiratory volume in 1 second to forced vital capacity in 48,201 individuals of European ancestry with follow up of the top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P &lt; 5 x 10(-8)) with pulmonary function in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (also known as EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1 and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.</p

Pleiotropy of cardiometabolic syndrome with obesity-related anthropometric traits determined using empirically derived kinships from the Busselton Health Study

Over two billion adults are overweight or obese and therefore at an increased risk of cardiometabolic syndrome (CMS). Obesity-related anthropometric traits genetically correlated with CMS may provide insight into CMS aetiology. The aim of this study was to utilise an empirically derived genetic relatedness matrix to calculate heritabilities and genetic correlations between CMS and anthropometric traits to determine whether they share genetic risk factors (pleiotropy). We used genome-wide single nucleotide polymorphism (SNP) data on 4671 Busselton Health Study participants. Exploiting both known and unknown relatedness, empirical kinship probabilities were estimated using these SNP data. General linear mixed models implemented in SOLAR were used to estimate narrow-sense heritabilities (h 2 ) and genetic correlations (r g ) between 15 anthropometric and 9 CMS traits. Anthropometric traits were adjusted by body mass index (BMI) to determine whether the observed genetic correlation was independent of obesity. After adjustment for multiple testing, all CMS and anthropometric traits were significantly heritable (h 2 range 0.18–0.57). We identified 50 significant genetic correlations (r g range: - 0.37 to 0.75) between CMS and anthropometric traits. Five genetic correlations remained significant after adjustment for BMI [high density lipoprotein cholesterol (HDL-C) and waist–hip ratio; triglycerides and waist–hip ratio; triglycerides and waist–height ratio; non-HDL-C and waist–height ratio; insulin and iliac skinfold thickness]. This study provides evidence for the presence of potentially pleiotropic genes that affect both anthropometric and CMS traits, independently of obesity

Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci

Background Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. Methods We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. Results We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes. Conclusions Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer.Medicine, Faculty ofNon UBCPopulation and Public Health (SPPH), School ofReviewedFacultyResearche

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape

Gene-age interactions in blood pressure regulation: A large-scale investigation with the CHARGE, global BPgen, and ICBP consortia

Although age-dependent effects on blood pressure (BP) have been reported, they have not been systematically investigated in large-scale genome-wide association studies (GWASs). We leveraged the infrastructure of three well-established consortia (CHARGE, GBPgen, and ICBP) and a nonstandard approach (age stratification and metaregression) to conduct a genome-wide search of common variants with age-dependent effects on systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse (PP) pressure. In a two-staged design using 99,241 individuals of European ancestry, we identified 20 genome-wide significant (p≤ 5 10) loci by using joint tests of the SNP main effect and SNP-age interaction. Nine of the significant loci demonstrated nominal evidence of age-dependent effects on BP by tests of the interactions alone. Index SNPs in the EHBP1L1 (DBP and MAP), CASZ1 (SBP and MAP), and GOSR2 (PP) loci exhibited the largest age interactions, with opposite directions of effect in the young versus the old. The changes in the genetic effects over time were small but nonnegligible (up to 1.58 mm H