RARB genetic variants might contribute to the risk of chronic obstructive pulmonary disease based on a case-control study

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is a progressive respiratory disease that severely impairs patients' respiratory function and quality of life. RARB is involved in COPD progression by affecting inflammatory reactions, cell proliferation, and apoptosis. The impact of single nucleotide polymorphisms (SNPs) within RARB on COPD susceptibility remains unclear. Here, we aimed to evaluate the association between RARB SNPs and COPD risk.

Methods: A total of 270 COPD patients and 271 healthy controls were enrolled. The MassARRAY iPLEX platform tested the genotype of the SNPs. The association was analyzed using logistic regression analysis. The false-positive report probability (FPRP) analysis was performed to validate the significant findings. The relationship between SNPs and RARB expression was evaluated using the GTEx database.

Results: Our study found a significant association between rs6799734 and COPD susceptibility (OR 1.88, p = 0.008, p (FDR) = 0.047). The stratified analysis revealed that this association was particularly pronounced among individuals aged ≤ 71 years (OR 2.34, p = 0.011, p (FDR) = 0.045), males (OR 2.60, p = 0.002, p (FDR) = 0.013), those with a BMI ≥ 24 (OR 3.95, p = 0.018, p (FDR) = 0.108), and smokers (OR 2.48, p = 0.020, p (FDR) = 0.120). Additionally, rs1286641 and rs1881706 showed significant associations with COPD risk in females and smokers. These associations were further validated by FPRP analysis. Preliminary mechanism studies indicated that rs1286641 and rs1881706 were related to RARB expression.

Conclusion: Our findings suggest a potential role of RARB SNPs in influencing COPD risk.

Keywords: Chronic obstructive pulmonary disease; RARB; single nucleotide polymorphisms; susceptibility.

Figure 1.

The relationship between RARB polymorphisms and COPD susceptibility COPD, chronic obstructive pulmonary disease; SNP, single nucleotide polymorphisms; or, odds ratios; 95% CI, 95% confidence interval; FDR, false discovery rate. The p-value was calculated by logistic regression analysis with adjustment for age, gender, body mass index, and smoking. p < 0.05 represents statistically significant. The threshold value for FDR was 0.05.

Figure 2.

Tree diagram analysis of SNP interactions. The interaction model describes the percentage of the entropy (information gain) that is explained by each factor. Values inside nodes indicate information gain of individual attributes or main effects, whereas values between nodes show information gain of pairwise combinations of attributes or interaction effects. Positive entropy (plotted in orange) indicates interaction, which can be interpreted as a synergistic or nonadditive relationship; while negative entropy (plotted in green or blue) indicates independence or additivity (redundancy). Information gain is automatically calculated by the MDR software. The software evaluates information gain by comparing the accuracy of different genetic marker combinations in classifying disease status. Main effects refer to the independent impact of individual genetic markers on disease risk.

Figure 3.

GTEx Analysis for the association between rs6799734 (a), rs1286641 (B), and rs1881706 (C) and RARB gene expression.