Leveraging Hispanic/Latino diversity to map and characterize cardiovascular disease loci

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SUMMARY Cardiovascular disease (CVD) is a leading cause of morbidity and mortality among US Hispanic or Latino (H/L) populations. H/Ls are a relatively young population and experience heightened disparities in risk for most CVD risk factors, including obesity, type 2 diabetes (T2D), dyslipidemia, and hypertension; therefore, their absolute CVD burden is expected to increase. The major public health and clinical challenge imposed by CVD has motivated large efforts to understand underlying biologic mechanisms–a critical barrier to treatment, risk stratification, and ultimately, disease prevention. Thousands of genetic loci for coronary heart disease (CHD) and CVD risk factors have been mapped influencing risk of CHD via perturbations of lipid metabolism, blood pressure regulation, inflammation, and platelet function, as well as through mechanisms that remain unknown. Yet, genome-wide association studies (GWAS) for CHD and stroke in H/L populations have been scarce. Indeed, despite previous work on the genetics of CVD risk factors in H/L (several by our group), no stand- alone GWAS for CHD and stroke in H/L has been published. Thus, for CHD, stroke, and CVD risk factors, the knowledge gap between genomics, public health, and medicine could be improved by enriching the genomic translational pipeline, which includes discovering new loci for CVD related traits and their underlying causal variants; elucidating the biological and/or pathophysiological mechanisms; and establishing evidence for clinical utility and/or impact on health outcomes. We propose to leverage extant data on H/L individuals from large epidemiologic and clinical biobank studies and to generate new eQTL data to discover and characterize the genetic architecture of CVD risk and events in H/L populations. Our specific aims are to (1) discover and characterize the genetic architecture of CVD related traits in Hispanic/Latinos through meta-analysis of studies ascertaining more than 159,622 H/L participants in total; (2) derive the first ever H/L-specific eQTL map to build H/L-relevant gene expression prediction models and apply these models to our study samples with genotyping data (discovery sample less the participants with measured RNA: n~146,822) and conduct transcriptome-wide association studies (TWAS) analyses in each individual study followed by meta-analysis for each trait of interest; and (3) perform colocalization and to sample Mendelian Randomization (MR) analyses to identify causal genes amongst H/L CVD risk loci, and use electronic health record (EHR)-linked biobanks to characterize the broader clinical impact of loci via phenome wide association studies (PheWAS) for H/L CVD risk loci. Our study is high impact as the burden of CVD is rapidly growing in Hispanic/Latino populations and demographic trends suggest that the H/L population will constitute ~35% of the US population by 2050. Our research will ensure diverse populations are not the last to benefit from the new era of precision medicine at the same time it develops expedited strategies for translating genomics to function and clinical utility.