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HLA*IMP--an integrated framework for imputing classical HLA alleles from SNP genotypes.

ABSTRACT: Genetic variation at classical HLA alleles influences many phenotypes, including susceptibility to autoimmune disease, resistance to pathogens and the risk of adverse drug reactions. However, classical HLA typing methods are often prohibitively expensive for large-scale studies. We previously described a method for imputing classical alleles from linked SNP genotype data. Here, we present a modification of the original algorithm implemented in a freely available software suite that combines local data preparation and QC with probabilistic imputation through a remote server.We introduce two modifications to the original algorithm. First, we present a novel SNP selection function that leads to pronounced increases (up by 40% in some scenarios) in call rate. Second, we develop a parallelized model building algorithm that allows us to process a reference set of over 2500 individuals. In a validation experiment, we show that our framework produces highly accurate HLA type imputations at class I and class II loci for independent datasets: at call rates of 95-99%, imputation accuracy is between 92% and 98% at the four-digit level and over 97% at the two-digit level. We demonstrate utility of the method through analysis of a genome-wide association study for psoriasis where there is a known classical HLA risk allele (HLA-C*06:02). We show that the imputed allele shows stronger association with disease than any single SNP within the region. The imputation framework, HLA*IMP, provides a powerful tool for dissecting the architecture of genetic risk within the HLA.HLA*IMP, implemented in C++ and Perl, is available from http://oxfordhla.well.ox.ac.uk and is free for academic use.

SUBMITTER: Dilthey AT

PROVIDER: S-EPMC3065693 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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HLA*IMP--an integrated framework for imputing classical HLA alleles from SNP genotypes.

Dilthey Alexander T AT Moutsianas Loukas L Leslie Stephen S McVean Gil G

Bioinformatics (Oxford, England) 20110207 7

<h4>Motivation</h4>Genetic variation at classical HLA alleles influences many phenotypes, including susceptibility to autoimmune disease, resistance to pathogens and the risk of adverse drug reactions. However, classical HLA typing methods are often prohibitively expensive for large-scale studies. We previously described a method for imputing classical alleles from linked SNP genotype data. Here, we present a modification of the original algorithm implemented in a freely available software suite ...[more]

PMID: 21300701

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Project description:BackgroundPersistent cervical high-risk human papillomavirus (hrHPV) infection is a necessary cause of cervical cancer. However, the host genetic factors underlying its risk are not well understood. We hypothesized that immunogenetic variation plays a role in hrHPV infection and persistence. Therefore, we conducted a study of classical HLA alleles and their association with hrHPV infection and persistence among women.MethodsWe characterized HPV infection using SPF10/LiPA25in Nigerian women at baseline and at 6 months follow-up visits in 2014. hrHPV infection was prevalent if at least one carcinogenic HPV genotype was detected at the baseline visit and persistent if at least one carcinogenic HPV genotype was detected at the baseline and follow-up visits. Classical HLA alleles were imputed from genotypes in the MHC region using the HLA genotype imputation with attribute bagging (HIBAG) algorithm. HLA association tests were conducted under additive genetic models.ResultsThe mean (±SD) age of the 517 study participants was 38 (±8) years, 48% were HIV negative, 24% were hrHPV positive at baseline and 10% had persistent hrHPV infections. In multivariate regression models adjusted for age, HIV status and the first principal component, DQA1*01:02 and DQA1*02:01 were positively associated with prevalent but not persistent hrHPV infections, while DQA1*05:01 was negatively associated with prevalent hrHPV but positively associated with persistent cervical hrHPV infections. Four haplotypes (A*30:01-DQA1*05:01, B*07:02-C*07:02, B*07:02-DQA1*05:01 and C*07:02-DQA1*05:01) were significantly associated with prevalent cervical hrHPV infections and several haplotypes that included the DQA1*05:01 allelic variant were significantly associated with persistent cervical hrHPV infections. Six amino acid positions on DQα1 were associated with prevalent but not persistent cervical hrHPV infections.ConclusionsIn this first study to investigate the association between HLA alleles and persistent hrHPV in African women, we identified important risk alleles that merit further investigation. Our findings provide new insights into risk factors for hrHPV infection in African ancestry women.

Project description:Multiple sclerosis (MS) susceptibility shows strong genetic associations with HLA alleles and haplotypes. We genotyped 11 HLA genes in 477 non-Hispanic European MS patients and their 954 unaffected parents using a validated next-generation sequencing (NGS) methodology. HLA haplotypes were assigned unequivocally by tracing HLA allele transmissions. We explored HLA haplotype/allele associations with MS using the genotypic transmission disequilibrium test (gTDT) and multiallelic TDT (mTDT). We also conducted a case-control (CC) study with all patients and 2029 healthy unrelated ethnically matched controls. We performed separate analyses of 54 extended multi-case families by reviewing transmission of haplotype blocks. The haplotype fragment including DRB5*01:01:01~DRB1*15:01:01:01 was significantly associated with predisposition (gTDT: p < 2.20e-16; mTDT: p =1.61e-07; CC: p < 2.22e-16) as reported previously. A second risk allele, DPB1*104:01 (gTDT: p = 3.69e-03; mTDT: p = 2.99e-03; CC: p = 1.00e-02), independent from the haplotype bearing DRB1*15:01 was newly identified. The allele DRB1*01:01:01 showed significant protection (gTDT: p = 8.68e-06; mTDT: p = 4.50e-03; CC: p = 1.96e-06). Two DQB1 alleles, DQB1*03:01 (gTDT: p = 2.86e-03; mTDT: p = 5.56e-02; CC: p = 4.08e-05) and DQB1*03:03 (gTDT: p = 1.17e-02; mTDT: p = 1.16e-02; CC: p = 1.21e-02), defined at two-field level also showed protective effects. The HLA class I block, A*02:01:01:01~C*03:04:01:01~B*40:01:02 (gTDT: p = 5.86e-03; mTDT: p = 3.65e-02; CC: p = 9.69e-03) and the alleles B*27:05 (gTDT: p = 6.28e-04; mTDT: p = 2.15e-03; CC: p = 1.47e-02) and B*38:01 (gTDT: p = 3.20e-03; mTDT: p = 6.14e-03; CC: p = 1.70e-02) showed moderately protective effects independently from each other and from the class II associated factors. By comparing statistical significance of 11 HLA loci and 19 haplotype segments with both untruncated and two-field allele names, we precisely mapped MS candidate alleles/haplotypes while eliminating false signals resulting from 'hitchhiking' alleles. We assessed genetic burden for the HLA allele/haplotype identified in this study. This family-based study including the highest-resolution of HLA alleles proved to be powerful and efficient for precise identification of HLA genotypes associated with both, susceptibility and protection to development of MS.

Dataset Information

HLA*IMP--an integrated framework for imputing classical HLA alleles from SNP genotypes.

Publications

HLA*IMP--an integrated framework for imputing classical HLA alleles from SNP genotypes.

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