Whole Genome Sequencing Analysis of Body Mass Index Identifies Novel African Ancestry-Specific Risk Allele

Abstract

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P< 5 × 10-9). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) inMTMR3that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in thePOC5andDMDloci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.

Pan-UK Biobank GWAS improves discovery, analysis of genetic architecture, and resolution into ancestry-enriched effects

“…The -log10(p-value) is plotted along chromosomal position, with neighboring variants colored by sample-size weighted LD (with lead SNP) for ancestries included in meta-analysis (gray: LD not defined for at least one ancestry group). This variant has recently been identified in a larger study of BMI (Zhang et al 2023).…”