Imputation of KIR Types from SNP Variation Data.

Authors:
Damjan Vukcevic, James A Traherne, Sigrid Næss, Eva Ellinghaus, Yoichiro Kamatani, Alexander Dilthey, Mark Lathrop, Tom H Karlsen, Andre Franke, Miriam Moffatt, William Cookson, John Trowsdale, Gil McVean, Stephen Sawcer, Stephen Leslie
Year of publication:
2015
Volume:
97
Issue:
4
Issn:
0002-9297
Journal title abbreviated:
AM J HUM GENET
Journal title long:
American journal of human genetics
Impact factor:
10.794
Abstract:
Large population studies of immune system genes are essential for characterizing their role in diseases, including autoimmune conditions. Of key interest are a group of genes encoding the killer cell immunoglobulin-like receptors (KIRs), which have known and hypothesized roles in autoimmune diseases, resistance to viruses, reproductive conditions, and cancer. These genes are highly polymorphic, which makes typing expensive and time consuming. Consequently, despite their importance, KIRs have been little studied in large cohorts. Statistical imputation methods developed for other complex loci (e.g., human leukocyte antigen [HLA]) on the basis of SNP data provide an inexpensive high-throughput alternative to direct laboratory typing of these loci and have enabled important findings and insights for many diseases. We present KIR(∗)IMP, a method for imputation of KIR copy number. We show that KIR(∗)IMP is highly accurate and thus allows the study of KIRs in large cohorts and enables detailed investigation of the role of KIRs in human disease.