Genetic Analysis Reveals Different Mechanisms of IL-5 Involved in the Development of CAD in a Chinese Han Population

Abstract

Background: Coronary artery disease (CAD) is a complex disease and the leading cause of death worldwide. It is caused by genetic and environmental factors or their interactions. Candidate gene association studies are an important genetic strategy for the study of complex diseases, and multiple variants of inflammatory cytokines have been found to be associated with CAD using this method. Interleukin-5 (IL-5) is an important inflammatory immune response factor that plays a role in a various inflammatory disease. Clinical tests and animal experiments indicated that IL-5 is involved in CAD development, but the exact mechanisms are unclear. This study investigated the genetic relationship between the single nucleotide polymorphisms (SNPs) in IL5 and CAD.

Materials and methods: Based on the Chinese Han population, we collected 1,824 patients with CAD and 1,920 control subjects and performed a two-stage case-control association analysis for three SNPs in IL5 (rs2057687, rs78546665, and rs2069812) using the high resolution melt (HRM) technology. Logistic regression analyses were applied to adjust for traditional risk factors for CAD and to perform haplotype and gene interaction analyses. Multiple linear regression analyses were used to study relationships between the selected SNPs and serum lipid levels.

Results: In this study, two-stage case-control association analysis revealed that the allele and genotype frequency distributions of the three IL5 SNPs were not statistically significant between the case and control groups. In addition, none of the IL5 haplotypes were associated with CAD. Further stratified analyses were conducted by sex, age, hypertension, and disease status, respectively, and the results revealed that the rs2057687 and rs2069812 of IL5 were associated with CAD in the male group (p _adj = 0.025, OR, 0.77 (95% CI, 0.62-0.97); p _adj = 0.016, OR, 0.82 (95% CI, 0.70-0.97), respectively); the rs2057687 and rs78546665 of IL5 were associated with late-onset CAD (p _adj = 0.039, OR, 0.78 (95% CI, 0.62-0.99); p _adj = 0.036, OR, 1.46 (95% CI, 1.02-1.53), respectively); the rs2069812 of IL5 was associated with CAD in the hypertension group (p _adj = 0.036, OR, 0.84 (95% CI, 0.71-0.99)); and none of the SNPs in IL5 were associated with different CAD states (anatomical CAD and clinical CAD). In addition, the association between SNPs and the serum lipid levels indicated that rs78546665 was positively correlated with triglyceride levels (p = 0.012). Finally, SNP-SNP interaction analyses revealed that interactions of rs2057687 and rs2069812 were associated with CAD (p _adj = 0.046, OR, 0.77 (95% CI, 0.13-4.68)).

Conclusion: This study suggested that the common variants of IL5 might play a role in CAD by affecting the risk factors for CAD and through SNP-SNP interactions, which provides a new target for specific treatment of CAD patients and a theoretical basis for personalized medicine.