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Open AccessCommunication
Int. J. Mol. Sci. 2016, 17(7), 1008; doi:10.3390/ijms17071008

Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes

1
Institute of Genetics and Biophysics “Adriano Buzzati-Traverso”, National Research Council, Via Pietro Castellino 111, 80131 Naples, Italy
2
DiST, Department of Science and Technology, University of Naples “Parthenope”, 80134 Naples, Italy
3
Department of Translational Medical Sciences, University of Naples “Federico II”, 80131 Naples, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Lu Cai
Received: 3 May 2016 / Revised: 7 June 2016 / Accepted: 14 June 2016 / Published: 25 June 2016
(This article belongs to the Special Issue Diabetic Complications: Pathophysiology, Mechanisms, and Therapies)
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Abstract

Type 2 diabetes (T2D) is one of the most frequent mortality causes in western countries, with rapidly increasing prevalence. Anti-diabetic drugs are the first therapeutic approach, although many patients develop drug resistance. Most drug responsiveness variability can be explained by genetic causes. Inter-individual variability is principally due to single nucleotide polymorphisms, and differential drug responsiveness has been correlated to alteration in genes involved in drug metabolism (CYP2C9) or insulin signaling (IRS1, ABCC8, KCNJ11 and PPARG). However, most genome-wide association studies did not provide clues about the contribution of DNA variations to impaired drug responsiveness. Thus, characterizing T2D drug responsiveness variants is needed to guide clinicians toward tailored therapeutic approaches. Here, we extensively investigated polymorphisms associated with altered drug response in T2D, predicting their effects in silico. Combining different computational approaches, we focused on the expression pattern of genes correlated to drug resistance and inferred evolutionary conservation of polymorphic residues, computationally predicting the biochemical properties of polymorphic proteins. Using RNA-Sequencing followed by targeted validation, we identified and experimentally confirmed that two nucleotide variations in the CAPN10 gene—currently annotated as intronic—fall within two new transcripts in this locus. Additionally, we found that a Single Nucleotide Polymorphism (SNP), currently reported as intergenic, maps to the intron of a new transcript, harboring CAPN10 and GPR35 genes, which undergoes non-sense mediated decay. Finally, we analyzed variants that fall into non-coding regulatory regions of yet underestimated functional significance, predicting that some of them can potentially affect gene expression and/or post-transcriptional regulation of mRNAs affecting the splicing. View Full-Text
Keywords: type 2 diabetes; drug responsiveness; computational predictions; pharmacogenomics; personalized medicine; RNA-sequencing type 2 diabetes; drug responsiveness; computational predictions; pharmacogenomics; personalized medicine; RNA-sequencing
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MDPI and ACS Style

Costa, V.; Federico, A.; Pollastro, C.; Ziviello, C.; Cataldi, S.; Formisano, P.; Ciccodicola, A. Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes. Int. J. Mol. Sci. 2016, 17, 1008.

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