Harnessing tissue-specific genetic variation to dissect putative causal pathways between body mass index and cardiometabolic phenotypes

Body mass index (BMI) is a complex disease risk factor known to be influenced by genes acting via both metabolic pathways and appetite regulation. In this study, we aimed to gain insight into the phenotypic consequences of BMI associated genetic variants which may be mediated by their expression in different tissues. First, we harnessed meta-analysed gene expression datasets derived from subcutaneous adipose (n=1257) and brain (n=1194) tissue to identify 86 and 140 loci respectively which provided evidence of genetic colocalization with BMI. These two sets of tissue-partitioned loci had differential effects with respect to waist-to-hip ratio, suggesting that the way they influence fat distribution and anthropometric traits may vary despite them having very similar average magnitudes of effect on BMI itself (adipose=0.0148 and brain=0.0149 per 1-SD change in BMI). For instance, BMI colocalized with TBX15 expression in adipose tissue only, which likely influences BMI due to its role in skeletal development, whereas genes which colocalized using brain tissue may be more likely to influence BMI due to their role in energy balance (e.g NEGR1). Leveraging these tissue-partitioned variant sets using a multivariable Mendelian randomization framework provided strong evidence that the brain tissue derived variants are predominantly responsible for driving the genetically predicted effects of BMI on cardiovascular disease endpoints (e.g. coronary artery disease: OR:1.05, 95% CI:1.04-1.07, P=4.67x10-14). In contrast, our analyses suggested that the adipose tissue variants may predominantly be responsible for the underlying relationship between BMI and measures of cardiac function, such as left ventricular stroke volume (Beta: 0.21, 95% CI: 0.09-0.32, P=6.43x10-4).