Evidence map›Paper›PMID 38702819›Full record

ArticleBiomarker research2024

Phenomic landscape and pharmacogenomic implications for HLA region in a Taiwan Han Chinese population.

Wan-Hsuan Chou, Lu-Chun Chen, Henry Sung-Ching Wong, Ching-Hsuan Chao, Hou-Wei Chu, Wei-Chiao Chang

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Article in Biomarker research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Shared trans-ancestry architecture of HLA-mediated disease risk in themedRxiv : the preprint server for health sciences · 2026
    Article
  4. Review
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Wan-Hsuan Chou *Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan.
Lu-Chun Chen *Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan.
Henry Sung-Ching WongDepartment of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan.
Ching-Hsuan ChaoDepartment of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan.
Hou-Wei ChuInstitute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.
Wei-Chiao ChangDepartment of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan. wcc@tmu.edu.tw.

Funding

Ministry of Education DP2-TMU-112-T-06National Science and Technology Council NSTC112-2320-B-038-026-MY3
6 · The paper itself

Abstract

backgroundThe human leukocyte antigen (HLA) genes, exhibiting significant genetic diversity, are associated with susceptibility to various clinical diseases and diverse in drug responses. High costs of HLA sequencing and the population-specific architecture of this genetic region necessitate the establishment of a population-specific HLA imputation reference panel. Moreover, there is a lack of understanding about the genetic and phenotypic landscape of HLA variations within the Taiwanese population.

methodsWe created models for a Taiwanese-specific HLA imputation reference panel. These models were trained with the array genotype data and HLA sequencing data from 845 Taiwanese subjects. HLA imputation was applied for 59,448 Taiwanese subjects to characterize the HLA allele and haplotype frequencies. Additionally, a phenome-wide association study (PheWAS) was conducted to identify the phenotypes associated with HLA variations. The association of the biallelic HLA variants with the binary and quantitative traits were evaluated with additive logistic and linear regression models, respectively. Furthermore, an omnibus test with likelihood-ratio test was applied for each HLA amino acid position in the multiallelic HLA amino acid polymorphisms to compare the difference between a fitted model and a null model following a χ2 distribution of n-1 degree of freedom at a position with n residues. Finally, we estimated the prevalence of adverse drug reactions (ADR)-related HLA alleles in the Taiwanese population.

resultsIn this study, the reference panel models displayed remarkable accuracy, with averages of 99.3%, 98.9%, and 99.1% for 2-, 4-, 6-digit alleles of the eight classical HLA genes, respectively. For PheWAS, a total of 18,136 significant associations with HLA variants across 26 phenotypes are identified (p < 5×10

conclusionsWe successfully delivered the HLA imputation for 59,448 Taiwanese subjects and characterized the genetic and phenotypic landscapes of the HLA variations. In addition, we quantified the estimated prevalence of the ADR-related HLA alleles in the Taiwanese population. The developed HLA imputation reference panel could be used for estimation of population HLA allele frequencies, which can facilitate further studies in the role of HLA variants in a wider range of phenotypes in the population.

Indexed as

HLAHuman Leukocyte AntigenMajor histocompatibility complexMHCPhenome-wide association study

Identifiers

PMID38702819
PMCPMC11067262

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