Genetic predictors of sick sinus syndrome.

Sick sinus syndrome (SSS) encompasses a group of conduction disorders characterized by the inability of sinoatrial node to perform its pacemaker function. Our aim was to identify genetic predictors of SSS in a prospective cohort of patients admitted to the clinic for pacemaker implantation using single-locus and multilocus approaches. We performed genotyping for polymorphic markers of CLCNKA (rs10927887), SCN10A (rs6795970), FNDC3B (rs9647379), MIR146A (rs2910164), SYT10 (rs7980799), MYH6 (rs365990), and KCNE1 (rs1805127) genes in the group of 284 patients with SSS and 243 healthy individuals. Associations between the studied loci and SSS were tested using logistic regression under recessive genetic model using sex and age as covariates. Multilocus analysis was performed using Markov chain Monte Carlo method implemented in the APSampler program. Correction for multiple testing was performed using Benjamini-Hochberg procedure. We detected an individual association between KCNE1 rs1805127A allele and SSS in the total study group (OR 0.43, P = 0.028) and in the subgroup of patients with 2nd or 3rd degree sinoatrial block (OR 0.17, P = 0.033), and identified seven allelic patterns associated with the disease. SCN10A rs6795970T and MIR146A rs2910164C alleles were present in all seven combinations associated with SSS. The highest risk of SSS was conferred by the combination SCN10A rs6795970T+FNDC3B rs9647379C+MIR146A rs2910164C+SYT10 rs7980799C+KCNE1 rs1805127G (OR 2.98, CI 1.77-5.00, P = 1.27 × 10, P = 0.022). Our findings suggest that KCNE1 rs1805127 polymorphism may play a role in susceptibility to sinoatrial node dysfunction, particularly presenting as 2nd or 3rd degree sinoatrial block, and the risk-modifying effect of other studied loci is better detected using multilocus approach.