Abstract
The MHC/HLA region has been consistently associated with a large number of complex traits, including but not limited to, most immune-mediated ones. Efforts to pinpoint drivers of this commonly encountered association peak at the short arm of chromosome 6, however, have been challenging, owing to the high density of genes and the long and extended linkage disequilibrium that are characteristic of this region.
The development of methods to impute classical HLA alleles and amino acids from SNP genotyping data has offered an important additional layer of information to the investigators seeking to fine map the signal in the region. As a result, imputation-aided association analyses are now typically employed to shed light on the relationship of this locus with disease susceptibility and response to drugs.
In this chapter we discuss how the signal in the HLA region can be interrogated in practice, from performing the imputation to understanding its output and to incorporating it into downstream analysis. In addition, we recount some of the analytical approaches that are commonly used and suggest ways in which the findings from such imputation-aided analyses can be interpreted.
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References
Trowsdale J, Knight JC (2013) Major histocompatibility complex genomics and human disease. Annu Rev Genomics Hum Genet 14:301–323. https://doi.org/10.1146/annurev-genom-091212-153455
Moon J, Kim TJ, Lim JA et al (2016) HLA-B*40:02 and DRB1*04:03 are risk factors for oxcarbazepine-induced maculopapular eruption. Epilepsia 57:1879. https://doi.org/10.1111/epi.13566
Sousa-Pinto B, Correia C, Gomes L et al (2016) HLA and delayed drug-induced hypersensitivity. Int Arch Allergy Immunol 170(3):163–179. https://doi.org/10.1159/000448217
Stamp LK, Day RO, Yun J (2016) Allopurinol hypersensitivity: investigating the cause and minimizing the risk. Nat Rev Rheumatol 12(4):235–242. https://doi.org/10.1038/nrrheum.2015.132
Voorter CE, Palusci F, Tilanus MG (2014) Sequence-based typing of HLA: an improved group-specific full-length gene sequencing approach. Methods Mol Biol 1109:101–114. https://doi.org/10.1007/978-1-4614-9437-9_7
Ehrenberg PK, Geretz A, Baldwin KM et al (2014) High-throughput multiplex HLA genotyping by next-generation sequencing using multi-locus individual tagging. BMC Genomics 15:864. https://doi.org/10.1186/1471-2164-15-864
Hosomichi K, Jinam TA, Mitsunaga S et al (2013) Phase-defined complete sequencing of the HLA genes by next-generation sequencing. BMC Genomics 14:355. https://doi.org/10.1186/1471-2164-14-355
de Bakker PI, McVean G, Sabeti PC et al (2006) A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC. Nat Genet 38(10):1166–1172. https://doi.org/10.1038/ng1885
Dilthey AT, Moutsianas L, Leslie S et al (2011) HLA*IMP – an integrated framework for imputing classical HLA alleles from SNP genotypes. Bioinformatics 27(7):968–972. https://doi.org/10.1093/bioinformatics/btr061
Dilthey A, Leslie S, Moutsianas L et al (2013) Multi-population classical HLA type imputation. PLoS Comput Biol 9(2):e1002877. https://doi.org/10.1371/journal.pcbi.1002877
Jia X, Han B, Onengut-Gumuscu S et al (2013) Imputing amino acid polymorphisms in human leukocyte antigens. PLoS One 8(6):e64683. https://doi.org/10.1371/journal.pone.0064683
Zheng X, Shen J, Cox C et al (2014) HIBAG – HLA genotype imputation with attribute bagging. Pharmacogenomics J 14(2):192–200. https://doi.org/10.1038/tpj.2013.18
Erlich RL, Jia X, Anderson S et al (2011) Next-generation sequencing for HLA typing of class I loci. BMC Genomics 12:42. https://doi.org/10.1186/1471-2164-12-42
Leslie S, Donnelly P, McVean G (2008) A statistical method for predicting classical HLA alleles from SNP data. Am J Hum Genet 82(1):48–56. https://doi.org/10.1016/j.ajhg.2007.09.001
Li N, Stephens M (2003) Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data. Genetics 165(4):2213–2233
Okada Y, Momozawa Y, Ashikawa K et al (2015) Construction of a population-specific HLA imputation reference panel and its application to Graves' disease risk in Japanese. Nat Genet 47(7):798–802. https://doi.org/10.1038/ng.3310
Zhou F, Cao H, Zuo X et al (2016) Deep sequencing of the MHC region in the Chinese population contributes to studies of complex disease. Nat Genet 48(7):740–746. https://doi.org/10.1038/ng.3576
Kim K, Bang SY, Lee HS et al (2014) Construction and application of a Korean reference panel for imputing classical alleles and amino acids of human leukocyte antigen genes. PLoS One 9(11):e112546. https://doi.org/10.1371/journal.pone.0112546
Marsh SG, Albert ED, Bodmer WF et al (2010) Nomenclature for factors of the HLA system, 2010. Tissue Antigens 75(4):291–455. https://doi.org/10.1111/j.1399-0039.2010.01466.x
Robinson J, Soormally AR, Hayhurst JD et al (2016) The IPD-IMGT/HLA database - new developments in reporting HLA variation. Hum Immunol 77(3):233–237. https://doi.org/10.1016/j.humimm.2016.01.020
Anderson CA, Pettersson FH, Clarke GM et al (2010) Data quality control in genetic case-control association studies. Nat Protoc 5(9):1564–1573. https://doi.org/10.1038/nprot.2010.116
Moutsianas L, Jostins L, Beecham AH et al (2015) Class II HLA interactions modulate genetic risk for multiple sclerosis. Nat Genet 47(10):1107–1113. https://doi.org/10.1038/ng.3395
Marchini J, Howie B (2010) Genotype imputation for genome-wide association studies. Nat Rev Genet 11(7):499–511. https://doi.org/10.1038/nrg2796
Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447(7145):661–678. https://doi.org/10.1038/nature05911
Chang CC, Chow CC, Tellier LC et al (2015) Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4:7. https://doi.org/10.1186/s13742-015-0047-8
Evans DM, Spencer CC, Pointon JJ et al (2011) Interaction between ERAP1 and HLA-B27 in ankylosing spondylitis implicates peptide handling in the mechanism for HLA-B27 in disease susceptibility. Nat Genet 43(8):761–767. https://doi.org/10.1038/ng.873
Genetic Analysis of Psoriasis Consortium and the Wellcome Trust Case Control Consortium, Strange A, Capon F et al (2010) A genome-wide association study identifies new psoriasis susceptibility loci and an interaction between HLA-C and ERAP1. Nat Genet 42(11):985–990. https://doi.org/10.1038/ng.694
Todd JA, Bell JI, McDevitt HO (1987) HLA-DQ beta gene contributes to susceptibility and resistance to insulin-dependent diabetes mellitus. Nature 329(6140):599–604. https://doi.org/10.1038/329599a0
Gutierrez-Achury J, Zhernakova A, Pulit SL et al (2015) Fine mapping in the MHC region accounts for 18% additional genetic risk for celiac disease. Nat Genet 47(6):577–578. https://doi.org/10.1038/ng.3268
Patsopoulos NA, Barcellos LF, Hintzen RQ et al (2013) Fine-mapping the genetic association of the major histocompatibility complex in multiple sclerosis: HLA and non-HLA effects. PLoS Genet 9(11):e1003926. https://doi.org/10.1371/journal.pgen.1003926
McMahon G, Ring SM, Davey-Smith G et al (2015) Genome-wide association study identifies SNPs in the MHC class II loci that are associated with self-reported history of whooping cough. Hum Mol Genet 24(20):5930–5939. https://doi.org/10.1093/hmg/ddv293
Moutsianas L, Enciso-Mora V, Ma YP et al (2011) Multiple Hodgkin lymphoma-associated loci within the HLA region at chromosome 6p21.3. Blood 118(3):670–674. https://doi.org/10.1182/blood-2011-03-339630
Goyette P, Boucher G, Mallon D et al (2015) High-density mapping of the MHC identifies a shared role for HLA-DRB1*01:03 in inflammatory bowel diseases and heterozygous advantage in ulcerative colitis. Nat Genet 47(2):172–179. https://doi.org/10.1038/ng.3176
Oksenberg JR, Barcellos LF, Cree BA et al (2004) Mapping multiple sclerosis susceptibility to the HLA-DR locus in African Americans. Am J Hum Genet 74(1):160–167. https://doi.org/10.1086/380997
Han F, Lin L, Li J et al (2012) HLA-DQ association and allele competition in Chinese narcolepsy. Tissue Antigens 80(4):328–335. https://doi.org/10.1111/j.1399-0039.2012.01948.x
Mignot E, Kimura A, Lattermann A et al (1997) Extensive HLA class II studies in 58 non-DRB1*15 (DR2) narcoleptic patients with cataplexy. Tissue Antigens 49(4):329–341
Liu C, Yang X, Duffy B et al (2013) ATHLATES: accurate typing of human leukocyte antigen through exome sequencing. Nucleic Acids Res 41(14):e142. https://doi.org/10.1093/nar/gkt481
Szolek A, Schubert B, Mohr C et al (2014) OptiType: precision HLA typing from next-generation sequencing data. Bioinformatics 30(23):3310–3316. https://doi.org/10.1093/bioinformatics/btu548
Dilthey AT, Gourraud PA, Mentzer AJ et al (2016) High-accuracy HLA type inference from whole-genome sequencing data using population reference graphs. PLoS Comput Biol 12(10):e1005151. https://doi.org/10.1371/journal.pcbi.1005151
Boegel S, Scholtalbers J, Lower M et al (2015) In silico HLA typing using standard RNA-Seq sequence reads. Methods Mol Biol 1310:247–258. https://doi.org/10.1007/978-1-4939-2690-9_20
Browning BL, Browning SR (2009) A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am J Hum Genet 84(2):210–223. https://doi.org/10.1016/j.ajhg.2009.01.005
Wissemann WT, Hill-Burns EM, Zabetian CP et al (2013) Association of Parkinson disease with structural and regulatory variants in the HLA region. Am J Hum Genet 93(5):984–993. https://doi.org/10.1016/j.ajhg.2013.10.009
Chen D, Gaborieau V, Zhao Y et al (2015) A systematic investigation of the contribution of genetic variation within the MHC region to HPV seropositivity. Hum Mol Genet 24(9):2681–2688. https://doi.org/10.1093/hmg/ddv015
Hu X, Deutsch AJ, Lenz TL et al (2015) Additive and interaction effects at three amino acid positions in HLA-DQ and HLA-DR molecules drive type 1 diabetes risk. Nat Genet 47(8):898–905. https://doi.org/10.1038/ng.3353
Lenz TL, Deutsch AJ, Han B et al (2015) Widespread non-additive and interaction effects within HLA loci modulate the risk of autoimmune diseases. Nat Genet 47(9):1085–1090. https://doi.org/10.1038/ng.3379
Field J, Browning SR, Johnson LJ et al (2010) A polymorphism in the HLA-DPB1 gene is associated with susceptibility to multiple sclerosis. PLoS One 5(10):e13454. https://doi.org/10.1371/journal.pone.0013454
Sekar A, Bialas AR, de Rivera H et al (2016) Schizophrenia risk from complex variation of complement component 4. Nature 530(7589):177–183. https://doi.org/10.1038/nature16549
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Moutsianas, L., Gutierrez-Achury, J. (2018). Genetic Association in the HLA Region. In: Evangelou, E. (eds) Genetic Epidemiology. Methods in Molecular Biology, vol 1793. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7868-7_8
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DOI: https://doi.org/10.1007/978-1-4939-7868-7_8
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