Application of bioinformatical analysis to identify candidate genes associated with hereditary angioedema

Abstract

Primary immunodeficiencies (PID) are a heterogeneous group of hereditary diseases that lead to impaired immune defense. Often, the diagnosis cannot be made without identifying mutations that lead to the development of the disease. For many PIDs, there is no clear understanding of the etiology, pathogenesis, and genes involved. There is an obvious need to identify candidate genes potentially capable of leading to the development of PIDs.Hereditary angioedema (HAE) is a rare genetically determined disease, accompanied by recurrent edema of soft tissues and submucosal membranes, posing a threat to the life of patients. Diagnosis is based on the clinical presentation, family history, laboratory values of C1-esterase inhibitor, complement component 4, complement component 1q, antibodies to C1 and genetic testing for a number of mutations in the genes SERPING1, F12, PLG, ANGPT1, KNG1, MYOF, HS3ST6. However, pathogenesis may involve other genes in which the negative effect of mutations has not yet been studied. HAE is a non-monogenic disease that may involve an extensive network of genes. It seems important to determine the groups of the most probable candidate genes presumably involved in the development of pathology.Aim – to identify, using bioinformatics analysis, candidate genes for the development/pathogenesis of HAE and to reveal their biological context.The analysis was based on a group of genes, mutations in which are significantly associated with HAE: SERPING1, F12, PLG, ANGPT1, KNG1, MYOF, HS3ST6. To analised genetic and protein–protein networks and identify the biological context of the selected candidate genes, a number of web resources were used: HumanNetv3, GeneMania, FUMA GWAS in the GENE2FUNC mode.One hundred potential candidate genes in which mutations can be associated with HAE have been identified. The biological context of the identified genes was determined. The data of the biological context, genetic and protein-protein interactions made it possible to exclude a number of genes from the list of the most likely participants in pathogenesis and divide the remaining ones into groups with a greater or lesser potential for involvement. The group of the most likely HAO candidate genes includes PLAT, HRG, SERPINA1, SERPINF2, MASP2, GRB14, C1QBP, DOK2, KLKB1, F11, TEK, KLK10, KRT1, APOH, CPB2, F2.The results obtained can provide significant assistance in the study of the HAE molecular mechanism, as well as in the diagnosis and prognosis of the disease course. The identified candidate genes have the potential to serve as diagnostic biomarkers for patients with unexplained angioedema.The use of bioinformatic methods makes it possible to determine the list of candidate genes that are presumably involved in the disease pathogenesis or aggravate its course, and to obtain up-to-date information about the biological context of the identified genes. Understanding the genetic underpinnings and pathophysiology of PID may help define new diagnostic and therapeutic targets.

Keywords

• bioinformatical analysis
• primary immunodeficiencies
• hereditary angioedema
• candidate genes
• pathogenetically significant mutations
• in silico analysis