Impact of GATA2 gene polymorphism (rs2335052 A > G) on coronary artery disease susceptibility

Abstract Background The transcription factor GATA binding protein 2 (GATA2) is essential for the gene expression profile in vascular endothelial cells. GATA2 located on 3q21, encodes a transcription factor essential for the production and differentiation of hematopoietic stem cells. Previous research revealed that GATA2 gene is a possible risk factor forearly-onset of CAD. The present study evaluated the possible role of GATA2 polymorphism as a risk determinant of CAD. Method A total of 300 angiographically recorded cases and 300 healthy controls were enrolled for the study. Serum lipid profile and polymorphism of GATA2 rs2335052 A > G in exon was monitored using PCR–RFLP technique. In silico study was done for wild and mutant to check the base pairing possibilities using the Muta RNA tool. Result The GATA 2 A > G variety was viewed as fundamentally connected with coronary artery disease ( p < 0.03). In addition to the above studies, we have also analyzed the association of serum lipid profile levels with GATA A > G genotype in patients and controls. The patients with (AG) genotype had elevated levels of Total Cholesterol and VLDL Cholesterol with respect to gene polymorphism. Further we have also analyzed the association of risk factors in relation to GATA A > G gene polymorphism and we observed that Hypertensive and alcoholics were found to be significantly associated with the gene polymorphism. To know the stability of GATA A > G gene polymorphism, In-silico analysis was performed for secondary structure prediction and it was found that rs 2,335,052 A allele has lesser entropy hence it is more stable than that of G allele further confirming its role in CAD patients. Here we found essentially a more prominent recurrence of GG genotype among patients with myocardial localized necrosis and this allele could be a hereditary risk for myocardial infarction in the population. In –silico analysis was performed for wild and mutant to check the base pairing probabilities using muta RNA tool ( http://rna.informatik.uni-freiburg.de/MutaRNA/Input.jsp ).The base pairing probabilities are depicted by using arc plots. The higher base pairing potential is indicated in deeper hues of the corresponding grey lines.