Multi-ethnic fine-mapping of 14 central adiposity loci
The Genetic Investigation of Anthropometric Traits (GIANT) consortium identified 14 loci in European Ancestry (EA) individuals associated with waist-to-hip ratio (WHR) adjusted for body mass index. These loci are wide and narrowingthe signalsremains necessary. Twelve of 14 loci identified inGIANTEA samples retained strong associations with WHR in our joint EA/individuals of African Ancestry (AA) analysis (log-Bayes factor >6.1). Transethnic analysesatfiveloci (TBX15-WARS2, LYPLAL1, ADAMTS9, LY86andITPR2-SSPN)substantially narrowed the signals to smaller sets of variants, some of which are i... Mehr ...
The Genetic Investigation of Anthropometric Traits (GIANT) consortium identified 14 loci in European Ancestry (EA) individuals associated with waist-to-hip ratio (WHR) adjusted for body mass index. These loci are wide and narrowingthe signalsremains necessary. Twelve of 14 loci identified inGIANTEA samples retained strong associations with WHR in our joint EA/individuals of African Ancestry (AA) analysis (log-Bayes factor >6.1). Transethnic analysesatfiveloci (TBX15-WARS2, LYPLAL1, ADAMTS9, LY86andITPR2-SSPN)substantially narrowed the signals to smaller sets of variants, some of which are in regions that have evidence of regulatory activity. By leveraging varying linkage disequilibrium structures across different populations, single-nucleotide polymorphisms (SNPs) with strong signals and narrower credible sets from trans-ethnic meta-analysis of central obesity provide more precise localizations of potential functional variants and suggest a possible regulatory role. Meta-analysis results for WHR were obtained from 77 167 EA participants from GIANT and 23 564 AA participants from the AfricanAncestry Anthropometry Genetics Consortium. For fine mapping we interrogatedSNPs within ±250 kbflanking regionsof 14 previously reported indexSNPsfrom loci discovered in EApopulations by performing trans-ethnic meta-analysis of results from the EA and AA meta-analyses. We applied a Bayesian approach that leverages allelic heterogeneity across populations to combine meta-analysis results and aids in fine-mapping shared variants at these locations. We annotated variants using information from the ENCODE Consortium and Roadmap Epigenomics Project to prioritize variants for possible functionality. © The Author 2014. Published by Oxford University Press. All rights reserved.