<p>Long-term primary prevention of myocardial infarction faces challenges, but genetic risk assessment may change this dynamic. We sought for genetic risk loci influencing myocardial infarction and underlying pathomechanisms. AS-PCR used for mutation detection (<i>STAT4</i>_ rs3024839 and <i>IL22</i>_ rs2227483) and confirmed positives by sequencing and Digital PCR. <i>STAT4</i> and <i>IL22</i> mRNA levels and chromatin accessibility at SNP sites were evaluated. We assessed SNPs for association with myocardial underlying comorbidities as well as their predictive performance ability. The population flow-sorted CD4⁺ FOXP3⁺ Tregs and the level of <i>Foxp3</i> mRNA were measured and TGF-β1 quantified using ELISA and intracellular staining assay. Immunophenotyping used to identify p53 expression, pro-inflammatory monocytes and circulating endothelial cells. More than 99% samples were positive for mutations. Significant differences in the mutated allele and genotype frequencies were identified at a p value cutoff of 0.05. Analyses identified SNPs as risk factors for comorbid factors with the ability in distinguishing high and low-risk individuals (AUC &gt; 0.9). Differentially accessible chromatin regions influencing <i>STAT4</i> and <i>IL22</i> expression were found in risk loci. Lower circulating CD4⁺ FOXP3⁺Tregs, <i>Foxp3</i> expression decline, decreasing TGF-β1 level, increased p53 level, inflammatory state and endothelial dysfunction were further validated. Discovered genotypes open novel opportunities for MI prediction.</p>