High trans-ethnic replicability of GWAS results implies common causal variants

PLoS Genet. 2013 Jun;9(6):e1003566. doi: 10.1371/journal.pgen.1003566. Epub 2013 Jun 13.

Abstract

Genome-wide association studies (GWAS) have detected many disease associations. However, the reported variants tend to explain small fractions of risk, and there are doubts about issues such as the portability of findings over different ethnic groups or the relative roles of rare versus common variants in the genetic architecture of complex disease. Studying the degree of sharing of disease-associated variants across populations can help in solving these issues. We present a comprehensive survey of GWAS replicability across 28 diseases. Most loci and SNPs discovered in Europeans for these conditions have been extensively replicated using peoples of European and East Asian ancestry, while the replication with individuals of African ancestry is much less common. We found a strong and significant correlation of Odds Ratios across Europeans and East Asians, indicating that underlying causal variants are common and shared between the two ancestries. Moreover, SNPs that failed to replicate in East Asians map into genomic regions where Linkage Disequilibrium patterns differ significantly between populations. Finally, we observed that GWAS with larger sample sizes have detected variants with weaker effects rather than with lower frequencies. Our results indicate that most GWAS results are due to common variants. In addition, the sharing of disease alleles and the high correlation in their effect sizes suggest that most of the underlying causal variants are shared between Europeans and East Asians and that they tend to map close to the associated marker SNPs.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alleles
  • Black People
  • Chromosome Mapping
  • Ethnicity / genetics*
  • Genome, Human
  • Genome-Wide Association Study*
  • Humans
  • Linkage Disequilibrium
  • Polymorphism, Single Nucleotide*
  • White People

Grants and funding

This work was supported by a PhD fellowship from the UPF to UMM and grants to AN from the Spanish Ministerio de Ciencia e Innovación (BFU2006-15413-C02-01, BFU2009-13409-C02-02; BFU2012-38236) and FEDER. The Spanish National Institute for Bioinformatics (www.inab.org) provided bioinformatics support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.