Molecular Characterization of Susceptibility Genes in Type II Diabetes and in-Silico Designing of Agonist for Therapeutic Interventions

Abstract

Diabetes mellitus (DM) is a worldwide metabolic disorder with high mortality and morbidity rate and type II diabetes mellitus (TIIDM) is its more prevalent form characterized by hyperglycemia. It is caused by the complex interaction between genetic and environmental factors including alcohol consumption, obesity, physical inactivity, diet, lifestyle, and smoking. Genetic factors increase the susceptibility of TIIDM and more than 318 genetic loci have been associated with TIIDM in a different population, mostly in Europeans. This study investigated the shared genetic basis of TIIDM amongst Pakistanis and Europeans. For that, a total 77 genome-wide significant (p < 5E-08) SNPs previously reported in Europeans and two TIIDM and Alzheimer's diseases (AD) shared SNPs were genotyped in Pakistani case-control samples (1,057 cases and 626 controls) by iPLEX® Gold or TaqMan® assays. Further expression analysis of significantly associated genes, FTO, TCF7L2, and PLEKHA1 was done in 35 TIIDM cases and 25 healthy controls. Under the logistic regression model, after controlling for false discovery rate, total 16 SNPs showed statistically significant (p < 0.05) associations. The top three significant SNPs were: TCF7L2/rs7903146 (p = 7.13E-05), GLIS3/rs7041847 (p = 1.008E-04) and CHCHD9/rs13292136 (p = 1.47E-03). In expression analysis, PLEKHA1 expression was significantly higher (p = 0.0039) in TIIDM cases than in controls. This study also identified high risk non-synonymous missense SNPs (nsSNPs) in CPE and GNAS through in-silico investigation and then validated them in Pakistani TIIDM case control samples through Next Generation Technology (NGS). The computational study reported 62 and 44 high-risk nsSNPs in CPE and GNAS genes respectively and 12 were clinically significant in GNAS. The high-risk and clinically significant nsSNPs were found to change the stability of the proteins, highly conserved amino acid residues and post-translational modification sites (PTMs) in proteins. Proteolytic cleavage was the most common PTMs, affected by nsSNPs, in CPE and GNAS proteins. These nsSNPs have no prominent structural effects on CPE and GNAS proteins and CPE mutant protein, D328G, structure was lightly changed. After in-silico identification, when 62 high-risk nsSNPs in CPE and 12 clinically significant nsSNPs in GNAS were validated xix in TIIDM through NGS, none of the nsSNPs were associated with TIIDM and all the targeted SNPs were wild type homozygous in both cases and controls. On the other hand, TIIDM is treated with multiple therapeutic approaches and 70-80% of the population in developing countries are using herbal medicines because of their fewer side effects. In-silico investigation plays a major role in the identification of bioactive compounds to be effectively used for treatment purposes. This study identified agonists against inositol 1,4,5-trisphosphate receptor type 3 (IP3R3) from antidiabetic bioactive compounds through molecular docking (AutoDock Vina), MD simulation (GROMACS) and ADMET analysis. The two bioactive compounds, Sanggenol-O and 3,4-Didehydroglabridin showed the highest binding affinity with IP3R3. The binding energy of Sanggenol-O was -6.9 Kcal/mol while 3,4-Didehydroglabridin showed -9.7 Kcal/mol. The 3,4-Didehydroglabridin showed light deviation from the ADMET score. In conclusion, the SNPs in selected genes can be used as a potential molecular marker for the diagnosis and personalized treatment of TIIDM. It will also be helpful in identifying the individuals with high risk of TIIDM. Similarly, the bioactive antidiabetic compounds may have the potential to be used for therapeutic purposes and Sanggenol-O can be used as a potent drug to increase insulin secretion in TIIDM.