Dataset Information

Predicting HLA genotypes using unphased and flanking single-nucleotide polymorphisms in Han Chinese population.

ABSTRACT: BACKGROUND: Genetic variation associated with human leukocyte antigen (HLA) genes has immunological functions and is associated with autoimmune diseases. To date, large-scale studies involving classical HLA genes have been limited by time-consuming and expensive HLA-typing technologies. To reduce these costs, single-nucleotide polymorphisms (SNPs) have been used to predict HLA-allele types. Although HLA allelic distributions differ among populations, most prediction model of HLA genes are based on Caucasian samples, with few reported studies involving non-Caucasians. RESULTS: Our sample consisted of 437 Han Chinese with Affymetrix 5.0 and Illumina 550 K SNPs, of whom 214 also had data on Affymetrix 6.0 SNPs. All individuals had HLA typings at a 4-digit resolution. Using these data, we have built prediction model of HLA genes that are specific for a Han Chinese population. To optimize our prediction model of HLA genes, we analyzed a number of critical parameters, including flanking-region size, genotyping platform, and imputation. Predictive accuracies generally increased both with sample size and SNP density. CONCLUSIONS: SNP data from the HapMap Project are about five times more dense than commercially available genotype chip data. Using chips to genotype our samples, however, only reduced the accuracy of our HLA predictions by only ~3%, while saving a great deal of time and expense. We demonstrated that classical HLA alleles can be predicted from SNP genotype data with a high level of accuracy (80.37% (HLA-B) ~95.79% (HLA-DQB1)) in a Han Chinese population. This finding offers new opportunities for researchers in obtaining HLA genotypes via prediction using their already existing chip datasets. Since the genetic variation structure (e.g. SNP, HLA, Linkage disequilibrium) is different between Han Chinese and Caucasians, and has strong impact in building prediction models for HLA genes, our findings emphasize the importance of building ethnic-specific models when analyzing human populations.

SUBMITTER: Hsieh AR

PROVIDER: S-EPMC3909910 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Predicting HLA genotypes using unphased and flanking single-nucleotide polymorphisms in Han Chinese population.

Hsieh Ai-Ru AR Chang Su-Wei SW Chen Pei-Lung PL Chu Chen-Chung CC Hsiao Ching-Lin CL Yang Wei-Shiung WS Chang Chien-Ching CC Wu Jer-Yuarn JY Chen Yuan-Tsong YT Chang Tien-Chun TC Fann Cathy Sj CS

BMC genomics 20140129

<h4>Background</h4>Genetic variation associated with human leukocyte antigen (HLA) genes has immunological functions and is associated with autoimmune diseases. To date, large-scale studies involving classical HLA genes have been limited by time-consuming and expensive HLA-typing technologies. To reduce these costs, single-nucleotide polymorphisms (SNPs) have been used to predict HLA-allele types. Although HLA allelic distributions differ among populations, most prediction model of HLA genes are ...[more]

PMID: 24476119

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Project description:BackgroundPolygonum multiflorum is one of the leading causes of herb-induced liver injury in China. HLA-B*35:01 is reported to be a potential biomarker of Polygonum multiflorum-induced liver injury (PM-DILI). However, little is known about the relationship between single-nucleotide polymorphisms (SNPs) and PM-DILI.AimTo identify SNPs that indicate susceptibility to PM-DILI.MethodsWe conducted a systematic study enrolling 382 participants from four independent hospitals, including 73 PM-DILI patients, 118 patients with other drug-induced liver injury (other-DILI) and 191 healthy controls. Whole-exome sequencing was performed for 8 PM-DILI patients and 8 healthy controls who were randomly selected from the above subjects. Nineteen SNPs that showed high frequencies in the 8 PM-DILI patients were selected as candidate SNPs and then screened in 65 PM-DILI patients, 118 other-DILI patients and 183 healthy controls using the MassARRAY system. HLA-B high-resolution genotyping was performed for the 73 PM-DILI and 118 other-DILI patients. The Han-MHC database was selected as a population control for HLA-B analysis. P < 6.25 × 10-3 after Bonferroni correction was considered significant.ResultsThe frequencies of rs111686806 in the HLA-A gene, rs1055348 in the HLA-B gene, and rs202047044 in the HLA-DRB1 gene were significantly higher in the PM-DILI group than in the control group [27.2% vs 11.6%, P = 1.72 × 10-5, odds ratio (OR) = 3.96, 95% confidence interval (CI): 2.21-7.14; 42.5% vs 8.6%, P = 1.72 × 10-19, OR = 13.62, 95%CI: 7.16-25.9; 22.9% vs 8.1%, P = 4.64 × 10-6, OR = 4.1, 95%CI: 2.25-7.47]. Only rs1055348 showed a significantly higher frequency in the PM-DILI group than in the other-DILI group (42.5% vs 13.6%, P = 1.84 × 10-10, OR = 10.06, 95%CI: 5.06-20.0), which suggested that it is a specific risk factor for PM-DILI. rs1055348 may become a tag for HLA-B*35:01 with 100% sensitivity and 97.7% specificity in the PM-DILI group and 100% sensitivity and 98.1% specificity in the other-DILI group. Furthermore, HLA-B*35:01 was confirmed to be associated with PM-DILI with a frequency of 41.1% in the PM-DILI group compared with 11.9% (P = 4.30 × 10-11, OR = 11.11, 95%CI: 5.57-22.19) in the other-DILI group and 2.7% (P = 6.22 × 10-166, OR = 62.62, 95%CI: 35.91-109.20) in the Han-MHC database.Conclusionrs111686806, rs1055348, and rs202047044 are associated with PM-DILI, of which, rs1055348 is specific to PM-DILI. As a tag for HLA-B*35:01, rs1055348 may become an alternative predictive biomarker of PM-DILI.

Dataset Information

Predicting HLA genotypes using unphased and flanking single-nucleotide polymorphisms in Han Chinese population.

Publications

Predicting HLA genotypes using unphased and flanking single-nucleotide polymorphisms in Han Chinese population.

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