Investigating the role of eight SNPs in CHRNA3 for COPD susceptibility in the Chinese elderly population

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality among the elderly in China. Genetic predisposition is a recognized risk factor for COPD, with CHRNA3 emerging as a promising candidate gene due to its involvement in smoking behavior and lung function. This study aimed to investigate the association between eight CHRNA3 SNPs and COPD susceptibility in the Chinese elderly population.

Methods: A total of 270 COPD patients and 271 healthy controls were included in the study. SNP genotyping was carried out using the Agena MassARRAY platform. Logistic regression analysis was employed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) to assess the association between the SNPs and COPD risk. Forest plots were generated using Sangerbox software to visually represent the association results. Additionally, haplotype blocks were constructed using Haploview 4.2 software to explore the potential impact of haplotypes on COPD risk.

Results: Our findings indicated that rs615470, rs660652, and rs472054 are associated with a reduced risk of COPD, while rs8040868 is associated with an increased risk. Linkage disequilibrium (LD) analysis identified a haplotype block encompassing rs76071148, rs615470, rs660652, rs472054 and rs578776. Notably, the haplotype TTAAG was associated with a reduced risk of COPD.

Conclusion: This study provides valuable insights into the genetic susceptibility of COPD among the elderly, particularly regarding the role of SNPs in CHRNA3. These findings contribute to a deeper understanding of the pathogenesis of COPD and may facilitate the discovery of novel therapeutic targets for COPD.

Keywords: CHRNA3; COPD; SNPs; elderly; genetic susceptibility.

Figure 1.

Detailed flowchart of the research process. Abbreviations: COPD: chronic obstructive pulmonary disease; QC: quality control.

Figure 2.

Forest plot of CHRNA3 SNPs associations with COPD under various genetic models. The allele model displays the OR and 95% CI for the effect of each allele. The additive model posits that the effect of the genetic variant is proportional to the number of copies of the effect allele an individual possesses. The HOM model compares the OR of individuals homozygous for the variant allele to those homozygous for the reference allele. The HET model compares the OR of heterozygous individuals to those homozygous for the reference allele. The dominant model’s OR compares individuals with at least one copy of the effect allele to those without it. The recessive model’s OR compares individuals homozygous for the effect allele to all other genotypes combined. Abbreviations: SNP: single nucleotide polymorphism; OR: odds ratio; CI: confidence interval; HOM: homozygous; HET: heterozygote. p < 0.05 was considered to be significant.

Figure 3.

The linkage disequilibrium patterns among SNPs in CHRNA3 and the haplotype blocks. This heatmap illustrates the LD among SNPs in the CHRNA3 gene, indicating how often certain alleles are inherited together. The matrix uses a color gradient to represent the strength of LD between SNPs, with deeper colors signifying higher LD and lighter colors indicating weaker LD. Defined regions within the genome are characterized by a high degree of LD among neighboring SNPs, suggesting they are less likely to be separated by recombination events. Numerical values/100 superimposed on the heatmap blocks are D’ values. Values close to 1 indicate a strong association between alleles, while values close to 0 suggest little to no association. Abbreviations: LD: Linkage disequilibrium.