Journal of asthma and allergy · 2023
The Assessment of TLR1 Gene Polymorphism Association with the Risk of Allergic Rhinitis in the Chinese Han Population from Northern China.
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Han Hui, Lian Penggang, Chen Haiyuan, Shamsi Bilal Haider, Liu Yonglin, Niu Yongliang
Аннотация
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.
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.