The full text of this article hosted at iucr.org is unavailable due to technical difficulties.

ORIGINAL ARTICLE

Transethnic differences in GWAS signals: A simulation study

Daniela Zanetti

Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, CA, USA

Department of Animal Biology‐Anthropology, University of Barcelona, Barcelona, Spain

Search for more papers by this author
Michael E. Weale

Corresponding Author

E-mail address: m.weale@gmail.com

Department of Medical & Molecular Genetics, King's College London, London, UK

Correspondence

M. E. Weale, Genomics plc, Oxford OX1 1JD, UK.

Email: m.weale@gmail.com

Search for more papers by this author
First published: 07 May 2018
Cited by: 1

Funding information: Regione Autonoma della Sardegna (Master and Back Grant)

Abstract

Genome‐wide association studies (GWASs) have allowed researchers to identify thousands of single nucleotide polymorphisms (SNPs) and other variants associated with particular complex traits. Previous studies have reported differences in the strength and even the direction of GWAS signals across different populations. These differences could be due to a combination of (1) lack of power, (2) allele frequency differences, (3) linkage disequilibrium (LD) differences, and (4) true differences in causal variant effect sizes.

To determine whether properties (1)–(3) on their own might be sufficient to explain the patterns previously noted in strong GWAS signals, we simulated case–control data of European, Asian and African ancestry, applying realistic allele frequencies and LD from 1000 Genomes data but enforcing equal causal effect sizes across populations. Much of the observed differences in strong GWAS signals could indeed be accounted for by allele frequency and LD differences, enhanced by the Euro‐centric SNP bias and lower SNP coverage found in older GWAS panels. While we cannot rule out a role for true transethnic effect size differences, our results suggest that strong causal effects may be largely shared among human populations, motivating the use of transethnic data for fine‐mapping.

Number of times cited according to CrossRef: 1

  • , Genetic influences on susceptibility to rheumatoid arthritis in African-Americans, Human Molecular Genetics, 10.1093/hmg/ddy395, (2018).