An intron SNP rs666088 in SLIT2 increases the risk of acute coronary syndrome in an Iranian population

Abstract Background The Slit guidance Ligand 2 (SLIT2) glycoprotein is of particular interest because of its role in modulating inflammation and the progression of diseases such as atherosclerosis. This study aimed to determine whether SLIT2 polymorphisms can serve as predictive markers for coronary artery disease (CAD) development by investigating its single-nucleotide polymorphisms (SNPs). Methods In this case-control study, a total of 321 participants including 217 patients with diagnosed CAD and 104 healthy controls were recruited. Patients were divided into acute coronary syndrome (ACS) (n = 153) and stable angina pectoris (SAP) (n = 64). Allele and genotype frequency of SLIT2 SNP variants rs666088 C > T and rs16869521 A > T were determined using Polymerase Chain Reaction with Sequence-Specific Primers (PCR-SSP). Odds ratios (ORs) were reported along with their 95% confidence intervals (CIs) and P-values. Crude estimates were initially presented, followed by adjusted ORs computed using logistic regression, controlling for potential confounders including age, gender, high-density lipoprotein (HDL) levels, fasting blood sugar (FBS), and smoking status. Results The frequencies of the T allele of rs666088 were significantly higher in ACS patients compared to healthy controls, and were associated with an increased risk of ACS both before (OR = 1.5, 95% CI = 1.1–2.2, P = 0.01) and after adjustment for confounding factors (OR = 1.3, 95% CI = 1.1–1.9, P = 0.02). Moreover, analysis of ACS subgroups—myocardial infarction (MI) and unstable angina pectoris (UAP), revealed consistent results. However, the allele and genotype frequencies of rs16869521 were not significantly different between patients and controls in any disease categories. Conclusions Our study revealed that genetic polymorphism of SLIT2 (rs666088) TT genotype and T allele is the potential host genetic risk factor for ACS. Therefore, SLIT2 (rs666088) genetic variation may be considered as a biomarker for early screening and diagnosis of the disease.