Exploring the genetic characteristics of diverse populations to guide drug development for cardiometabolic and immune mediated diseases

Chronic inflammation manifested in the form of psoriasis, systemic lupus erythematosus and rheumatoid arthritis has been associated with accelerated development of cardiometabolic diseases. Diabetes, dyslipidemia and hypertension lead to a two-fold risk of developing future adverse cardiac events in populations of European ancestry, the risk increasing to up to seven-folds in ancestrally diverse populations, such as South-East Asians. Despite this discrepancy in disease risk, most of the studies that have successfully identified genetic loci associated with immune and cardiovascular diseases have been conducted in European populations, while ancestrally diverse populations are severely under-represented in genetic studies. Moreover, ancestrally diverse population are more likely to be unresponsive to currently available drugs prescribed for the treatment of cardiovascular and immune mediated diseases or experience severe adverse drug reactions.

This project aims to identify genetic loci associated with an increased risk of developing cardiometabolic and immune mediated diseases across ancestrally diverse populations and assess their potential as drug targets. The first part of the study focuses on identifying trans-ethic and ancestry specific loci across European, African and East Asian populations in the UK Biobank and Genes&Health cohorts from available summary statistics, genotyping and sequencing data using trans-ethic colocalization. Admixed populations from the UK Biobank will be deconvolved by local ancestry inference and included in population specific analysis based on their ancestral haplotype dosage. The second part of the study aims to explore the role of these novel loci as potential drug targets for the treatment of cardiometabolic and immune mediated diseases. Drug target mendelian randomization will be performed to assess whether modification of drug targets at transcript or protein expression level can reduce disease risk across ancestries, using expression quantitative trait loci (eQTL) from eQTLGen and GTEx databases and protein expression quantitative trait (pQTL) data from Interval and SCALLOP Consortium, as well as ancestry specific quantitative trait loci available in the literature. Finally, this project will explore the repurposing opportunities and potential side effects of licensed drugs, failed compounds and pre-clinical candidates across ancestries.