Vukcevic Damjan, Traherne James A, Næss Sigrid, Ellinghaus Eva, Kamatani Yoichiro, Dilthey Alexander, Lathrop Mark, Karlsen Tom H, Franke Andre, Moffatt Miriam, Cookson William, Trowsdale John, McVean Gil, Sawcer Stephen, Leslie Stephen
Statistical Genetics, Murdoch Childrens Research Institute, Parkville, VIC 3052, Australia; School of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010, Australia.
Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, UK; Division of Immunology, Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK.
Am J Hum Genet. 2015 Oct 1;97(4):593-607. doi: 10.1016/j.ajhg.2015.09.005.
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.
对免疫系统基因进行大规模人群研究对于确定其在包括自身免疫性疾病在内的各种疾病中的作用至关重要。其中一组编码杀伤细胞免疫球蛋白样受体（KIR）的基因备受关注，这些基因在自身免疫性疾病、抗病毒能力、生殖状况和癌症中已明确具有作用且存在相关假设。这些基因具有高度多态性，这使得基因分型既昂贵又耗时。因此，尽管KIR很重要，但在大型队列研究中对其研究甚少。基于单核苷酸多态性（SNP）数据为其他复杂基因座（如人类白细胞抗原[HLA]）开发的统计推断方法，为这些基因座的直接实验室分型提供了一种廉价的高通量替代方法，并为许多疾病带来了重要发现和见解。我们提出了KIR∗IMP，一种用于推断KIR拷贝数的方法。我们表明KIR∗IMP具有高度准确性，因此能够在大型队列中对KIR进行研究，并能够详细调查KIR在人类疾病中的作用。
