Single nucleotide polymorphisms of SCN5A and SCN10A genes increase the risk of ventricular arrhythmias during myocardial infarction

Abstract

Background. Coronary artery disease (CAD) and its ultimate consequence − myocardial infarction (MI) − are major causes of sudden cardiac death (SCD). Previous studies have demonstrated the role of genetic polymorphisms in the risk of SCD and ventricular arrhythmia (VA) during MI. Objectives. To investigate the association between single nucleotide polymorphisms (SNPs) of genes implicated in congenital cardiac arrhythmias and the risk of developing VA in the context of MI. Material and methods. We performed a case-control study in which we genotyped 4 SNPs (rs11708996, rs10428132, rs9388451, and rs2200733) in 469 subjects using amplification refractory mutation system (ARMS) and a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). These SNPs are located in the SCN5A, SCN10A, HEY2, and PITX2 genes, respectively. We first compared 70 patients who had developed VA in the context of MI with 141 healthy controls; next, we compared VA patients with 258 MI patients who did not develop VA during a 1-year follow up. The statistical analyses were adjusted for sex and age. Results. Compared to the controls, 2 polymorphisms were significantly associated with the development of VA during MI, located in SCN5A rs11708996 (p = 0.001) and SCN10A rs10428132 (p = 0.001). Similar results were found when comparing VA cases with patients without VA. No associations of HEY2 and PITX2 polymorphisms were observed. Conclusions. Our results suggest that the rs11708996 and rs10428132 polymorphisms of the SCN5A and SCN10A genes may contribute to an elevated risk of developing VA in the context of MI. The associated alleles or genotypes may be used to predict the risk, and thus prevent eventual SCD.

Patient-specific induced pluripotent stem cell properties implicate Ca 2+ -homeostasis in clinical arrhythmia associated with combined heterozygous RYR2 and SCN10A variants

“…However, it could still permit extra-cardiac effects or enhancer–promotor interactions between SCN10A and SCN5A loci [ 39 ]. Furthermore, other studies did detect SCN10A mRNA in murine atrial and ventricular mouse myocardium although at much lower expression levels than SCN5A [ 40 ]. Na v 1.8 then influenced late rather than peak Na + currents, actions also detected in intracardiac neurons [ 17 ].…”

Characterization of global research trends and prospects on sudden coronary death: A literature visualization analysis

“…Plasma biomarkers, including not only traditional biomarkers like B type natriuretic peptide (BNP) [ 60 ] or troponin [ 18 ] but also inflammatory biomarkers as C -reactive protein (CRP) or high-sensitive CRP (hsCRP) [ 61 ], have improved CAD risk prediction. Moreover, researchers have investigated emerging biomarkers and further categories, such as inflammation (lpoprotein-associated phospholipase A2 [ 62 ], pentraxin-3 [ 63 ]), myocardial stress (soluble form of ST2 (18)), plaque stability (matrix metalloproteinase [ 64 ], transcription factor 3 [ 65 ], complement component 7 [ 66 ], OX40L and ICAM-1 [ 67 ]), myocardial fibrosis [ 68 , 69 ], RNA (circRNA [ [70] , [71] , [72] ], miRNA [ 73 , 74 ], mRNA [ 75 ]), and DNA (SNP[ 9 , 76 , 77 ], insertion/deletion [ 78 ]). We find that the significance of serum predictive biomarkers for sudden coronary death has been established in these studies.…”

Identification and Interaction Analysis of Molecular Markers in Myocardial Infarction by Integrated Bioinformatics Analysis

“…PLA2G2A [61], CCL23 [62], CD53 [63], TREML4 [64], TREM2 [65], CD180 [66], HPSE (heparanase) [67], CELA2A [68], TNFRSF4 [69], AMBP (alpha-1-microglobulin/bikunin precursor) [70], SOX18 [71], PANX2 [72], RSPO2 [73], COMP (cartilage oligomeric matrix protein) [74], ASGR1 [75] and NOXA1 [76] are involved in progression of atherosclerosis. A previous study reported that S100A9 [77], ADORA3 [78], IL1R2 [79], FPR1 [80], CCL20 [81], CD163 [82], S100A8 [83], TLR2 [84], HAS2 [85], PTX3 [86], TIMP4 [87], AREG (amphiregulin) [88], LBP (lipopolysaccharide binding protein) [89], IL18R1 [90], ALOX5AP [91], RETN (resistin) [92], F13A1 [93], FPR2 [94], SAA1 [95], FLT3 [96], AQP4 [97], FCER1G [98], CCL18 [99], HP (haptoglobin) [100], CDK1 [101], SLC7A11 [102], CFTR (CF transmembrane conductance regulator) [103], F8 [104], STC1[44], IL18RAP [90], TIMP3 [105], PDE4D [106], CYP4A11 [107], SCN10A [108], APOB (apolipoprotein B) [109], ACE (angiotensin I converting enzyme) [110], PENK (proenkephalin) [111], HSPB6 [112], TLR9 [113], EGR1 [114], CACNG8 [115], FOXD3 [116], DBH (dopamine beta-hydroxylase) [117], FOXP3 [118], GLP1R [119], IL34 [120], CCN1 [121], ADRA2A [122], BGN (biglycan) [123], NOS2 [124], AGRN (agrin) [125], DRD1 [126], GNB3 [127], EGR2 [128], MDK (midkine) [129], NOTCH3 [130], AZIN2 [131], NOTCH1 [132], LOX...…”