Construction and benchmarking of a multi-ethnic reference panel for the imputation of HLA class I and II alleles. (26th December 2018)

• Record Type: Journal Article
• Authors: Degenhardt, Frauke; Wendorff, Mareike; Wittig, Michael; Ellinghaus, Eva; Datta, Lisa W; Schembri, John; Ng, Siew C; Rosati, Elisa; Hübenthal, Matthias; Ellinghaus, David; Jung, Eun Suk; Lieb, Wolfgang; Abedian, Shifteh; Malekzadeh, Reza; Cheon, Jae Hee; Ellul, Pierre; Sood, Ajit; Midha, Vandana; Thelma, B K; Wong, Sunny H; Schreiber, Stefan; Yamazaki, Keiko; Kubo, Michiaki; Boucher, Gabrielle; Rioux, John D; Lenz, Tobias L; Brant, Steven R; Franke, Andre
• Is Part Of: Human molecular genetics. Volume 28:Number 12(2019)
• Page Start: 2078
• Page End: 2092
• Publication Date: 2018-12-26
• Subjects: Human molecular genetics -- Periodicals; Human chromosome abnormalities -- Periodicals; 572.8
• DOI: 10.1093/hmg/ddy443
• Languages: English
• ISSNs: 0964-6906

Abstract

Abstract: Genotype imputation of the human leukocyte antigen (HLA) region is a cost-effective means to infer classical HLA alleles from inexpensive and dense SNP array data. In the research setting, imputation helps avoid costs for wet lab-based HLA typing and thus renders association analyses of the HLA in large cohorts feasible. Yet, most HLA imputation reference panels target Caucasian ethnicities and multi-ethnic panels are scarce. We compiled a high-quality multi-ethnic reference panel based on genotypes measured with Illumina's Immunochip genotyping array and HLA types established using a high-resolution next generation sequencing approach. Our reference panel includes more than 1, 300 samples from Germany, Malta, China, India, Iran, Japan and Korea and samples of African American ancestry for all classical HLA class I and II alleles including HLA-DRB3/4/5 . Applying extensive cross-validation, we benchmarked the imputation using the HLA imputation tool HIBAG, our multi-ethnic reference and an independent, previously published data set compiled of subpopulations of the 1000 Genomes project. We achieved average imputation accuracies higher than 0.924 for the commonly studied HLA-A, -B, -C, -DQB1 and -DRB1 genes across all ethnicities. We investigated allele-specific imputation challenges in regard to geographic origin of the samples using sensitivity and specificity measurements as well as allele frequencies and identified HLA alleles that are challenging to impute for each of the populations separately. In conclusion, our new multi-ethnic reference data set allows for high resolution HLA imputation of genotypes at all classical HLA class I and II genes including the HLA-DRB3/4/5 loci based on diverse ancestry populations.