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The authors declare that they have no competing interests.
LZ carried out the experiments, performed the data analysis and drafted the manuscript. DC, JL, YH, SZ and YH conceived and designed the study and helped to draft the manuscript. JJ and YZ participated in the recruitment of subjects and acquisition of data. FD, ZL participated in the genotyping and interpretation of the data. All authors read and approved the final manuscript.
Myocardial infarction (MI) is a serious complication of Coronary Artery Disease (CAD). Previous studies have identified genetic variants on chromosome 9p21 and 6p24 that are associated with CAD, but further studies need to be conducted to investigate whether these genetic variants are associated with the pathogenesis of MI. We therefore performed this study to assess the association between the risk of MI and SNP rs10757274 on chromosome 9p21 and SNP rs6903956 on chromosome 6p24, and to explore the gene-environment interactions in a Chinese population.
A hospital-based case–control study, consisting of 502 MI patients and 308 controls, was conducted in a Chinese population. Demographic, behavioral information and clinical characteristics were collected, and genotyping of the two SNPs was performed using single base primer extension genotyping technology. The unconditional logistic regression (ULR) method was adopted to assess the association of the two SNPs with MI risk. Both generalized multifactor dimensionality reduction (GMDR) and ULR methods were applied to explore the effect of gene-environment interactions on the risk of MI.
After adjusting for covariates, it was observed that SNP rs10757274 on chromosome 9p21 was significantly associated with MI. Compared with subjects carrying the AA genotype, subjects carrying the GA or GG genotypes had a higher MI risk (ORa = 1.52, 95% CI:1.06–2.19, p a = 0.0227; ORa = 2.40, 95% CI:1.51–3.81, p a = 0.0002, respectively). Furthermore, a two-factor gene-environment interaction model of CDKN2A/B (rs10757274) and type 2 diabetes mellitus (T2DM) was identified to be the best model by GMDR (p = 0.0107), with a maximum prediction accuracy of 59.18%, and a maximum Cross-validation Consistency of 10/10. By using the ULR method, additive interaction analysis found that the combined effect resulted in T2DM-positive subjects with genotype GG/GA having an MI risk 4.38 times that of T2DM-negative subjects with genotype AA (ORadd = 4.38, 95% CI:2.56–7.47, p add < 0.0001).
These results show that gene polymorphism of CDKN2A/B (rs10757274) is associated with MI risk in a Chinese population. Furthermore, T2DM is likely to have an interaction with CDKN2A/B (rs10757274) that contributes to the risk of MI.