, Volume 64, Issue 2, pp 97-109
Date: 07 Sep 2011

KIR genotypic diversity can track ancestries in heterogeneous populations: a potential confounder for disease association studies

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Killer cell immunoglobulin-like receptors (KIR) are encoded by highly polymorphic genes that regulate the activation of natural killer (NK) cells and other lymphocyte subsets and likely play key roles in innate and adaptive immunity. Association studies increasingly implicate KIR in disease predisposition and outcome but could be confounded by unknown KIR genetic structure in heterogeneous populations. To examine this, we characterized the diversity of 16 KIR genes in 712 Northern Californians (NC) stratified by self-assigned ethnicities and compared the profiles of KIR polymorphism with other US and global populations using a reference database. Sixty-eight distinct KIR genotypes were characterized: 58 in 457 Caucasians (NCC), 17 in 47 African Americans (NCAA), 21 in 80 Asians (NCA), 20 in 74 Hispanics (NCH), and 18 in 54 “other” ethnicities (NCO). KIR genotype patterns and frequencies in the 4 defined ethnicities were compared with each other and with 34 global populations by phylogenetic analysis. Although there were no population-specific genotypes, the KIR genotype frequency patterns faithfully traced the ancestry of NCC, NCAA, and NCA but not of NCH whose ancestries are known to be more heterogeneous. KIR genotype frequencies can therefore track ethnic ancestries in modern urban populations. Our data emphasize the importance of selecting ethnically matched controls in KIR-based studies to avert spurious associations.

The study was conducted in a multi-ethnic cohort from Northern California. Our analysis shows the potential of KIR genotype frequency polymorphism to trace populations to their native ancestries and to foil disease association studies if ethnicity is ignored. The present study focuses on the importance of defining underlying population structure in conducting KIR association studies and highlights KIR genotype polymorphism itself as a useful tool in population structure analysis. The work describes a new dataset and novel analysis. None of the material has been published or is under consideration for publication elsewhere.