Abstract
Type 2 diabetes mellitus is a complex disorder with a strong genetic component. Inherited complex disease susceptibility in humans is most commonly associated with single nucleotide polymorphisms. The mechanisms by which this occurs are still poorly understood. Here we focus on analyzing the effect of a set of disease-causing missense variations of the monogenetic form of Type 2 diabetes mellitus and a set of disease-associated nonsynonymous variations in comparison with that of nonsynonymous variations without any experimental evidence for association with any disease. Analysis of different properties such as evolutionary conservation status, solvent accessibility, secondary structure, etc. suggests that disease-causing variations are associated with extreme changes in the value of the parameters relating to evolutionary conservation and/or protein stability. Disease-associated variations are rather moderately conserved and have a milder effect on protein function and stability. The majority of the genes harboring these variations are clustered in or near the insulin signaling network. Most of these variations are identified as potential sites for post-translational modifications; certain predictions have already reported experimental evidence. Overall our results indicate that Type 2 diabetes mellitus may result from a large number of single nucleotide polymorphisms that impair modular domain function and post-translational modifications involved in signaling. Our emphasis is more on conserved corresponding residues than the variation alone. We believe that the approach of considering a stretch of peptide sequence involving a polymorphism would be a better method of defining the role of the polymorphism in the manifestation of this disease. Because most of the variations associated with the disease are rare, we hypothesize that this disease is a "mosaic model" of interaction between a large number of rare alleles and a small number of common alleles along with the environment, which is little contrary to the existing common disease common variant model.
Highlights
Type 2 diabetes mellitus is a complex disorder with a strong genetic component
Data Set Extraction—The data set considered for the study includes a set of 29 mutations shown to cause monogenetic Type 2 diabetes mellitus (T2DM) in families or maturity onset of diabetes in young (disease causing variations (DCVs)), 113 polymorphisms associated with the disease in various populations in a total of 76 different candidate genes, and 92 random nonsynonymous variations in 32 genes that do not have any experimental evidence of association with any disease as a control data set (Supplemental Table 1)
This provides us with the position-specific independent count (PSIC) score calculated from the overall similarity of the sequences that share the amino acid type at this position with the help of statistical concepts and predicts whether a nonsynonymous variation is damaging, i.e. is supposed to affect the protein function, or benign, i.e. most likely lacking a profound phenotypic effect
Summary
T2DM, Type 2 diabetes mellitus; SNP, single nucleotide polymorphism; DCV, disease-causing variation; DAV, disease-associated nonsynonymous variation; PSIC, position-specific independent count; CNV, control nonsynonymous variation; IRS1, insulin receptor substrate 1; PPAR␥, peroxisome proliferator-activated receptor ␥; G3PD, glyceraldehyde-3-phosphate dehydrogenase; PH, pleckstrin homology; PTB, phosphotyrosine binding; SH, Src homology. Functional Assessment of Type 2 Diabetes Mellitus Variations prise risk factors of having a specific phenotype more in a statistical sense This raises the question as to whether the associated SNPs are only of statistical significance. In the current study we extensively analyzed the effect of nonsynonymous variations on the structure and function of proteins and attempted to determine their possible role in the disease phenotype
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