High-accuracy imputation for HLA class I and II genes based on high-resolution SNP data of population-specific references

Khor, Seik‐Soon; Yang, Wanling; Kawashima, M.; Kamitsuji, Shigeo; Zheng, Xiuwen; Nishida, Nao; Sawai, Hiromi; Toyoda, Hiromi; Miyagawa, Taku; Honda, Masao; Kamatani, Naoyuki; Tokunaga, Katsushi

doi:10.1038/tpj.2015.4

Cited by 49 publications

(48 citation statements)

References 16 publications

(26 reference statements)

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“…However, by combining the SGVP and International HapMap Project 42 reference panels, they were able to markedly increase prediction performance for these two loci. Khor et al (2015) developed specific custom classifiers for the Japanese population, and applied these in HIBAG to achieve high IAfor high-risk class II haplotypes in Japenese narolepsy patients 43 . Similarly, Levin et al (2014) improved HIBAG IA, relative to that of HLA*IMP:02, in African Americans by applying models reflecting the African and European ancestry of this population 44 .…”

Section: Discussionmentioning

confidence: 99%

Significant variation between SNP-based HLA imputations in diverse populations: the last mile is the hardest

Pappas¹,

Lizée

Paunić

et al. 2017

Pharmacogenomics J

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Four SNP-based HLA imputation methods (e-HLA, HIBAG, HLA*IMP:02 and MAGPrediction) were trained using 1000 Genomes SNP and HLA genotypes and assessed for their ability to accurately impute molecular HLA-A, -B, -C, and –DRB1 genotypes in the Human Genome Diversity Project cell panel. Imputation concordance was high (> 89%) across all methods for both HLA-A and HLA-C, but HLA-B and HLA-DRB1 proved generally difficult to impute. Overall, less than 27.8% of subjects were correctly imputed for all HLA loci by any method. Concordance across all loci was not enhanced via the application of confidence thresholds; reliance on confidence scores across methods only led to noticeable improvement (+3.2%) for HLA-DRB1. As the HLA complex is highly relevant to the study of human health and disease, a standardized assessment of SNP-based HLA imputation methods is crucial for advancing genomic research. Considerable room remains for the improvement of HLA-B and especially HLA–DRB1 imputation methods, and no imputation method is as accurate as molecular genotyping. The application of large, ancestrally diverse HLA and SNP reference datasets and multiple imputation methods has the potential to make SNP-based HLA imputation methods a tractable option for determining HLA genotypes.

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Section: Discussionmentioning

confidence: 99%

Significant variation between SNP-based HLA imputations in diverse populations: the last mile is the hardest

Pappas¹,

Lizée

Paunić

et al. 2017

Pharmacogenomics J

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“…We conducted 2‐field HLA genotype imputation for four class II HLA genes using the HIBAG R package . For HLA‐DRB1 , DQA1 , DQB1 and DPB1 , our in‐house Japanese imputation reference was used for HLA genotype imputation . We applied post‐imputation quality control using call‐threshold (CT >0.5).…”

Section: Participants and Methodsmentioning

confidence: 99%

Key HLA‐DRB1‐DQB1 haplotypes and role of the BTNL2 gene for response to a hepatitis B vaccine

et al. 2018

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Approximately 5‐10% of individuals who are vaccinated with a hepatitis B (HB) vaccine designed based on the hepatitis B virus (HBV) genotype C fail to acquire protective levels of antibodies. Here, host genetic factors behind low immune response to this HB vaccine were investigated by a genome‐wide association study (GWAS) and Human Leukocyte Antigen (HLA) association tests. The GWAS and HLA association tests were carried out using a total of 1,193 Japanese individuals including 107 low responders, 351 intermediate responders, and 735 high responders. Classical HLA class II alleles were statistically imputed using the genome‐wide SNP typing data. The GWAS identified independent associations of HLA‐DRB1‐DQB1, HLA‐DPB1 and BTNL2 genes with immune response to a HB vaccine designed based on the HBV genotype C. Five HLA‐DRB1‐DQB1 haplotypes and two DPB1 alleles showed significant associations with response to the HB vaccine in a comparison of three groups of 1,193 HB vaccinated individuals. When frequencies of DRB1‐DQB1 haplotypes and DPB1 alleles were compared between low immune responders and HBV patients, significant associations were identified for three DRB1‐DQB1 haplotypes, and no association was identified for any of the DPB1 alleles. In contrast, no association was identified for DRB1‐DQB1 haplotypes and DPB1 alleles in a comparison between high immune responders and healthy individuals. Conclusion: The findings in this study clearly show the importance of HLA‐DR‐DQ (i.e., recognition of a vaccine related HB surface antigen (HBsAg) by specific DR‐DQ haplotypes) and BTNL2 molecules (i.e., high immune response to HB vaccine) for response to a HB vaccine designed based on the HBV genotype C. (Hepatology 2018).

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“…HLA classical haplotypes were imputed using HIBAG R-package. 27 28 Associations between classical HLA haplotypes and lichen planus were analysed using Fisher's exact test that compared each haplotype with all other haplotypes.…”

Section: Statisticsmentioning

confidence: 99%

Phenome-wide association study maps new diseases to the human major histocompatibility complex region

Liu

Mayer

et al. 2016

J Med Genet

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Background Over 160 disease phenotypes have been mapped to the major histocompatibility complex (MHC) region on chromosome 6 by genome-wide association study (GWAS), suggesting that the MHC region as a whole may be involved in the etiology of many phenotypes, including unstudied diseases. The phenome-wide association study (PheWAS), a powerful and complementary approach to GWAS, has demonstrated its ability to discover and rediscover genetic associations. The objective of this study is to comprehensively investigate the MHC region by PheWAS to identify new phenotypes mapped to this genetically important region. Methods In the current study, we systematically explored the MHC region using PheWAS to associate 2692 MHC-linked variants (minor allele frequency ≥ 0.01) with 6221 phenotypes in a cohort of 7481 subjects from the Marshfield Clinic Personalized Medicine Research Project. Results Findings showed that expected associations previously identified by GWAS could be identified by PheWAS (e.g. psoriasis, ankylosing spondylitis, type I diabetes, and celiac disease) with some having strong cross-phenotype associations potentially driven by pleiotropic effects. Importantly, novel associations with 8 diseases not previously assessed by GWAS (e.g., lichen planus) were also identified and replicated in an independent population. Many of these associated diseases appear to be immune-related disorders. Further assessment of these diseases in 16,484 Marshfield Clinic twins suggests that some of these diseases, including lichen planus, may have genetic etiologies. Conclusions These results demonstrate that the PheWAS approach is a powerful and novel method to discover SNP-disease associations, and is ideal when characterizing cross-phenotype associations, and further emphasizes the importance of the MHC region in human health and disease.

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High-accuracy imputation for HLA class I and II genes based on high-resolution SNP data of population-specific references

Cited by 49 publications

References 16 publications

Significant variation between SNP-based HLA imputations in diverse populations: the last mile is the hardest

Significant variation between SNP-based HLA imputations in diverse populations: the last mile is the hardest

Key HLA‐DRB1‐DQB1 haplotypes and role of the BTNL2 gene for response to a hepatitis B vaccine

Phenome-wide association study maps new diseases to the human major histocompatibility complex region

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