Evaluation of self-reported ethnicity in a case-control population: the stroke prevention in young women study

Abstract

Abstract Background Population-based association studies are used to identify common susceptibility variants for complex genetic traits. These studies are susceptible to confounding from unknown population substructure. Here we apply a model-based clustering approach to our case-control study of stroke among young women to examine if self-reported ethnicity can serve as a proxy for genetic ancestry. Findings A population-based case-control study of stroke among women aged 15-49 identified 361 cases of first ischemic stroke and 401 age-comparable control subjects. Thirty single nucleotide polymorphisms (SNPs) throughout the genome unrelated to stroke risk and with established ancestry-based allele frequency differences were genotyped in all participants. The Structure program was used to iteratively evaluate for K = 1 to 5 potential genetic-based subpopulations. Evaluating the population as a whole, the Structure output plateaued at K = 2 clusters. 98% of self-reported Caucasians had an estimated probability ≥50% of belonging to Cluster 1, while 94% of self-reported African-Americans had an estimated probability ≥50% of belonging to Cluster 2. Stratifying the participants by self-reported ethnicity and repeating the analyses revealed the presence of two clusters among Caucasians, suggesting that potential substructure may exist. Conclusions Among our combined sample of African-American and Caucasian participants there is no large unknown subpopulation and self-reported ethnicity can serve as a proxy for genetic ancestry. Ethnicity-specific analyses indicate that population substructure may exist among the Caucasian participants indicating that further studies are warranted.