Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes
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...
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doaj-08ec52ff99894952b62a77f9b6ca48d02020-11-24T21:06:34ZengMDPI AGInternational Journal of Molecular Sciences1422-00672016-06-01177100810.3390/ijms17071008ijms17071008Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 DiabetesValerio Costa0Antonio Federico1Carla Pollastro2Carmela Ziviello3Simona Cataldi4Pietro Formisano5Alfredo Ciccodicola6Institute of Genetics and Biophysics “Adriano Buzzati-Traverso”, National Research Council, Via Pietro Castellino 111, 80131 Naples, ItalyInstitute of Genetics and Biophysics “Adriano Buzzati-Traverso”, National Research Council, Via Pietro Castellino 111, 80131 Naples, ItalyInstitute of Genetics and Biophysics “Adriano Buzzati-Traverso”, National Research Council, Via Pietro Castellino 111, 80131 Naples, ItalyInstitute of Genetics and Biophysics “Adriano Buzzati-Traverso”, National Research Council, Via Pietro Castellino 111, 80131 Naples, ItalyInstitute of Genetics and Biophysics “Adriano Buzzati-Traverso”, National Research Council, Via Pietro Castellino 111, 80131 Naples, ItalyDepartment of Translational Medical Sciences, University of Naples “Federico II”, 80131 Naples, ItalyInstitute of Genetics and Biophysics “Adriano Buzzati-Traverso”, National Research Council, Via Pietro Castellino 111, 80131 Naples, ItalyType 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.http://www.mdpi.com/1422-0067/17/7/1008type 2 diabetesdrug responsivenesscomputational predictionspharmacogenomicspersonalized medicineRNA-sequencing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Valerio Costa Antonio Federico Carla Pollastro Carmela Ziviello Simona Cataldi Pietro Formisano Alfredo Ciccodicola |
spellingShingle |
Valerio Costa Antonio Federico Carla Pollastro Carmela Ziviello Simona Cataldi Pietro Formisano Alfredo Ciccodicola Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes International Journal of Molecular Sciences type 2 diabetes drug responsiveness computational predictions pharmacogenomics personalized medicine RNA-sequencing |
author_facet |
Valerio Costa Antonio Federico Carla Pollastro Carmela Ziviello Simona Cataldi Pietro Formisano Alfredo Ciccodicola |
author_sort |
Valerio Costa |
title |
Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes |
title_short |
Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes |
title_full |
Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes |
title_fullStr |
Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes |
title_full_unstemmed |
Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes |
title_sort |
computational analysis of single nucleotide polymorphisms associated with altered drug responsiveness in type 2 diabetes |
publisher |
MDPI AG |
series |
International Journal of Molecular Sciences |
issn |
1422-0067 |
publishDate |
2016-06-01 |
description |
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. |
topic |
type 2 diabetes drug responsiveness computational predictions pharmacogenomics personalized medicine RNA-sequencing |
url |
http://www.mdpi.com/1422-0067/17/7/1008 |
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