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Oxford University Press, Human Molecular Genetics, 17(23), p. 4738-4744, 2014

DOI: 10.1093/hmg/ddu183

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Multi-ethnic Fine-mapping of 14 Central Adiposity Loci.

Journal article published in 2014 by L. Xue, Chen Wm, Sun Yv, Chen Yd, W. Zhao, J. Zhou, T. Workalemahu, J. Yang, S. van Wingerden, S. Wassertheil Smoller, Thomas W. Winkler, S. Vedantam, E. Wheeler, H.-E. Wichmann, V. Vitart and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

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.