Han H, Lian P, Chen H, Shamsi BH, Liu Y, Niu Y. The Assessment of
TLR1 Gene Polymorphism Association with the Risk of Allergic Rhinitis in the Chinese Han Population from Northern China.
J Asthma Allergy 2023;
16:979-986. [PMID:
37745900 PMCID:
PMC10516186 DOI:
10.2147/jaa.s421939]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 09/07/2023] [Indexed: 09/26/2023] Open
Abstract
Background
Environmental factors and genetic predisposition can influence the occurrence and development of AR. Toll-like receptor 1 (TLR1) belongs to the TLR receptor family, which plays a fundamental role in the activation of innate immunity. This study aimed to explore the association between TLR1 genetic loci and AR susceptibility in the Han Chinese from northern China.
Methods
Genotyping of three SNPs in the TLR1 has proceeded using the Agena MassARRAY platform. Odds ratio (OR) and 95% confidence interval (CI) were used to assess the correlation between candidate SNPs and AR susceptibility. Using FPRP (false-positive report probability analysis) to detect whether the positive results are noteworthy findings. The SNP-SNP interactions were detected by multifactor dimensionality reduction (MDR).
Results
TLR1-rs72493538 (Allele "G": OR=0.77, p = 0.034) and -rs76600635 (Allele "G": OR=0.75, p = 0.024) were associated with reducing the risk of AR among Han Chinese in northern China. In addition, we found evidence that TLR1-rs72493538 (males, participants with aging > 43 years, or coming from the wind-blown sand region) and -rs76600635 (males, participants with BMI ≤ 24 kg/m2, or coming from the wind-blown sand region) were associated with AR risk in stratified analyses. FPRP showed that all positive results are noteworthy findings. MDR analysis showed that a two-loci genetic model composed of rs72493538 and rs76600635 can be chosen as the best genetic model to predict the risk of AR.
Conclusion
TLR1-rs72493538 and -rs76600635 have a close association with reducing the risk of AR.
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