Molecular Screening of Caveolin 1 (CAV1) Gene Polymorphisms in Patients with Type II Diabetes Mellitus

Abstract

Type II Diabetes Mellitus (T2DM) is one of the most frequently occurring heterogenous, multi-system disorders characterized by hyperglycemia, responsible for 90% of the 463 million diabetes cases around the world. Complex etiology, painful clinical manifestations, and associated comorbidities makes T2DM a disease of great concern. T2DM has a strong genetic basis and studies have elucidated the association of SNPs of different genes with its progression. SNPs form the basis for precision medicine as the analysis of SNPs can aid the tailoring of medical treatments to individual genetic profiles, enhancing the efficacy and safety of therapies. This personalized approach helps in predicting disease risk, optimizing drug dosages, and minimizing adverse drug reactions, ultimately leading to more precise and effective healthcare. The current study aims to investigate the association of rs369262127 and rs201966419 with the risk of T2DM using Gradient PCR. In-silico analysis was performed to identify pathogenic exonic missense SNPs of CAV1 gene. In order to identify damaging nsSNPs in the CAV1 gene, computational tools such as SIFT, SNPs&GO, SNAP2, and MutPred2 were used. MUPro and ConSurf predicted protein stability and conservation profiles, respectively. Phyre2 and I-TASSER designed the 3D structure of CAV1 mutants. Post-translational modifications were determined by GPS-MSP, NetPhos3.1, NetOglyc4.0, and NetNGlyc 1.0. GENEMania and STRING predicted the protein-protein interaction. We found six nsSNPs in the coding region to be highly damaging: rs369884333, rs372416448, rs200052661, rs369262127, rs151024969, and rs201966419. Most alterations in structure were caused by rs201966419. As a result, rs369262127 and rs201966419 were selected for invitro analysis as they were found to be clinically significant in ClinVar. Invitro analysis including gradient PCR and gel electrophoresis revealed no significant difference between the genotype and allele frequency of patients and healthy controls. So, it can be concluded that the risk alleles of the two SNPs were not associated with susceptibility to T2DM in our sample pool, but replication of this study with larger sample size is required for further validation of results.