Genetic Association of Waist-to-Hip Ratio With Cardiometabolic Traits, Type 2 Diabetes, and Coronary Heart Disease

Emdin, Connor A.; Khera, Amit; Natarajan, Pradeep; Klarin, Derek; Zekavat, Seyedeh M.; Hsiao, Allan J.; Kathiresan, Sekar

doi:10.1001/jama.2016.21042

Cited by 333 publications

(361 citation statements)

References 35 publications

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“…As seen in humans , these traits were highly heritable. Also similar to that in humans , increased body weight in HS rats, particularly visceral fat pad weight (RetroFat and EpiFat), was significantly associated with several measures of metabolic health, indicating that genes underlying QTL for adiposity traits are likely to contribute to overall metabolic health in HS rats.…”

Section: Discussionsupporting

confidence: 56%

“…Two parallel approaches were used: bioinformatic analysis and protein modeling of known sequence variants and mediation analysis of expression levels. For , we used HS founder sequence (http://www.rgd.mcw.edu; genome build Rn6) to identify highly conserved, nonsynonymous coding variants within each QTL that were predicted to be damaging by PolyPhen (http://genetics.bwh.harvard.edu/pph/) and/or SIFT (http://www.sift.jcvi.org), focusing on variants in founder strains that showed haplotype effects at the locus.…”

Section: Methodsmentioning

confidence: 99%

“…Models were then assessed for likely impact on protein folding and/or function based on model confidence, phylogenetic sequence alignment, conservation, and whether or not the variant altered structural packing, molecular dynamic simulations, binding partners, linear motifs, or posttranslational modifications. For , transcript abundance levels of genes within HS liver were evaluated as potential causal mediators of the physiological QTL through mediation analysis (Supporting Information Methods).…”

Section: Methodsmentioning

confidence: 99%

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Genetic Fine‐Mapping and Identification of Candidate Genes and Variants for Adiposity Traits in Outbred Rats

Keele

Prokop

et al. 2017

Obesity

102

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ObjectiveObesity is a major risk factor for multiple diseases and is in part heritable, yet the majority of causative genetic variants that drive excessive adiposity remain unknown. Here, we used outbred heterogeneous stock (HS) rats in controlled environmental conditions to fine-map novel genetic modifiers of adiposity.MethodsBody weight and visceral fat pad weights were measured in male HS rats that were also genotyped genome-wide. Quantitative trait loci (QTL) were identified by genome-wide association of imputed single nucleotide polymorphism (SNP) genotypes using a linear mixed effect model that accounts for unequal relatedness between the HS rats. Candidate genes were assessed by protein modeling and mediation analysis of expression for coding and noncoding variants, respectively.ResultsHS rats exhibited large variation in adiposity traits, which were highly heritable and correlated with metabolic health. Fine-mapping of fat pad weight and body weight revealed three QTL and prioritized five candidate genes. Fat pad weight was associated with missense SNPs in Adcy3 and Prlhr and altered expression of Krtcap3 and Slc30a3, whereas Grid2 was identified as a candidate within the body weight locus.ConclusionsThese data demonstrate the power of HS rats for identification of known and novel heritable mediators of obesity traits.

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Section: Discussionsupporting

confidence: 56%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Genetic Fine‐Mapping and Identification of Candidate Genes and Variants for Adiposity Traits in Outbred Rats

Keele

Prokop

et al. 2017

Obesity

102

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“…For some variants, we found pleiotropy challenging the conventional MR approach for genes such as ABCA1 [17]. Instead of a single causal link [15], these results suggest two possible scenarios for genetic variants associated with multiple traits: (1) genetic variants influence cardiovascular RFs and AD independently, or (2) genetic variants influence AD through multiple cardiovascular RFs.…”

Section: Discussionmentioning

confidence: 97%

Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer’s disease

et al. 2018

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Cardiovascular (CV)- and lifestyle-associated risk factors (RFs) are increasingly recognized as important for Alzheimer’s disease (AD) pathogenesis. Beyond the ε4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV-associated genes also increase risk for AD. Using large genome-wide association studies and validated tools to quantify genetic overlap, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV-associated RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), triglycerides (TG), low-density (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TG, TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 90 SNPs on 19 different chromosomes that were jointly associated with AD and CV-associated outcomes. In meta-analyses across three independent cohorts, we found four novel loci within MBLAC1 (chromosome 7, meta-p = 1.44 × 10−9), MINK1 (chromosome 17, meta-p = 1.98 × 10−7) and two chromosome 11 SNPs within the MTCH2/SPI1 region (closest gene = DDB2, meta-p = 7.01 × 10−7 and closest gene = MYBPC3, meta-p = 5.62 × 10−8). In a large ‘AD-by-proxy’ cohort from the UK Biobank, we replicated three of the four novel AD/CV pleiotropic SNPs, namely variants within MINK1, MBLAC1, and DDB2. Expression of MBLAC1, SPI1, MINK1 and DDB2 was differentially altered within postmortem AD brains. Beyond APOE, we show that the polygenic component of AD is enriched for lipid-associated RFs. We pinpoint a subset of cardiovascular-associated genes that strongly increase the risk for AD. Our collective findings support a disease model in which cardiovascular biology is integral to the development of clinical AD in a subset of individuals.

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“…Several two-sample MR studies have used summary association data from GWAS that have estimated the effect of genetic variants on the trait of interest conditioned on heritable covariables (e.g. (12)(13)(14)(15)(16)). The use of such GWAS data might have biased the findings of these MR studies for the reasons outlined above.…”

Section: Introductionmentioning

confidence: 99%

Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations

Hartwig

Tilling

Davey-Smith

et al. 2019

Preprint

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Two-sample Mendelian randomization (MR) is increasingly used to strengthen causal inference using observational data. This method allows the use of freely accessible summary association results from genome-wide association studies (GWAS) for a range of traits. Some GWAS studies adjust for heritable covariables in an attempt to estimate direct effects of genetic variants on the trait of interest. One, both or neither of the genetic instrumental variables (IVs)-exposure association or genetic IVs-outcome association may have been adjusted for heritable covariables (referred to as GWAS covariables). However, it is unclear how this may affect two-sample MR analysis. We evaluated this in a simulation study comprising different scenarios that could motivate covariable adjustment in a GWAS. Our results indicate that the impact of covariable adjustment is highly dependent on the underlying causal structure. In the absence of residual confounding between exposure and covariable, between exposure and outcome, and between covariable and outcome, using covariable-adjusted summary associations for two-sample MR may eliminate bias due to horizontal pleiotropy. However, the presence of residual confounding (especially between the covariable and the outcome) leads to bias upon covariable adjustment, even in the absence of horizontal pleiotropy. Bias was lower when the true causal effect of the exposure on the outcome was zero compared to a non-zero causal effect. In an analysis using real data from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and UK Biobank, the direction of the causal effect estimate of waist circumference on blood pressure changed upon adjustment of waist circumference for body mass index. Our findings indicate that using covariable-adjusted summary associations in MR should generally be avoided. When that is not possible, careful consideration of the causal relationships underlying the data (including potentially unmeasured confounders) is required to direct sensitivity analyses and interpret results with appropriate caution. 3

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Genetic Association of Waist-to-Hip Ratio With Cardiometabolic Traits, Type 2 Diabetes, and Coronary Heart Disease

Cited by 333 publications

References 35 publications

Genetic Fine‐Mapping and Identification of Candidate Genes and Variants for Adiposity Traits in Outbred Rats

Genetic Fine‐Mapping and Identification of Candidate Genes and Variants for Adiposity Traits in Outbred Rats

Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer’s disease

Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations

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