A Bioinformatics Study of Gene Biomarkers in Congenital Hyperinsulinism

Hyperinsulinism is a condition where insufficient sugar reaches the child's brain leading to lifelong and permanent damage. This state takes place when the beta cells in the pancreas produce large (excessive) values of insulin, leading to frequent drops in blood sugar in the infant. The study examined the gene biomarkers of this disease using bioinformatics methods. After determining candidate genes from in vivo, in vitro, and silico studies, their expression data was collected from bioinformatics databases. The expressive data obtained from each group was standardized compared to the control group. Then the communication network of expressive data of candidate genes in sick and healthy individuals was plotted separately in MATLAB software, and the structural parameters of communication networks of expression data were calculated and compared. Using Reactome and Disaesome databases, the correctness of these networks and the determined biomarkers were examined once more.  All statistical calculations in the study were done using R and MATLAB software. Essential genes were identified using five criteria of centrality - degree, proximity, radius, between, and the greatest degree of the neighborhood. There, 5 genes INS, AKT1, PRKACG, PRKACB, and PRKACA possessed the most iterations according to all the results of the above 5 central criteria methods. The study indicated that AKT1, PRKACG, PRKACB, PRKACA, and INS genes could be considered diagnostic biomarkers of Congenital Hyperinsulinism (CHI).