Genetic polymorphisms of IFNG and IFNGR1 in association with the risk of pulmonary tuberculosis

• A large scale population-based case control study was carried out.
• Six tag SNPs in IFNG and IFNGR1 genes were genotyped.
• Three SNPs in IFNGR1 gene were individually associated with the altered risk of TB.
• Haplotypes rs2234711T–rs3799488C showed an increased risk of TB.

ObjectiveGenetic host factors play an important role in controlling individual's susceptibility to the pathogen. This study aims to explore the single and joint effect of genetic polymorphisms of interferon-gamma (IFNG) and its receptor (IFNGR1) in association with the pulmonary tuberculosis in a Chinese Han population.MethodsThis population-based case control study consisted of 1434 pulmonary tuberculosis patients and 1412 healthy controls. Six tag SNPs in IFNG/IFNGR1 were genotyped using TaqMan allelic discrimination technology. The logistic regression model was carried out to analyze the associations between the genotypes and haplotypes and the risk of tuberculosis by calculating the odds ratio (OR) and 95% confidence interval (CI).ResultsAfter the Bonferroni correction for multiple comparisons, three SNPs (rs2234711, rs1327475 and rs7749390) in IFNGR1 gene were observed to be significantly associated with the altered risks of tuberculosis. For the SNP rs2234711, individuals carrying C allele (vs. T) showed a decreased risk, with the adjusted OR(95% CI) of 0.82(0.76–0.91). The additive model revealed that each additional allele contributed about 14% decreased risk (OR: 0.86, 95% CI: 0.77–0.95). Moreover, we observed a strong linkage disequilibrium between rs2234711 and rs3799488. Compared with the common rs2234711C–rs3799488C haplotype, the haplotype rs2234711T–rs3799488C contributed to a significant increase in the risk of tuberculosis (adjusted OR: 1.24, 95% CI: 1.09–1.41).ConclusionsOur results suggest that genetic polymorphisms in IFNGR1 gene are involved in the risk of tuberculosis in the Chinese population. Future studies should include a comprehensive sequencing analysis to identify the specific causative sequence variants underlying the observed associations.