Cargando…

KCNJ11, ABCC8 and TCF7L2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment

BACKGROUND: Type 2 diabetes (T2D) is a worldwide epidemic with considerable health and economic consequences. Sulfonylureas are widely used drugs for the treatment of patients with T2D. KCNJ11 and ABCC8 encode the K(ir)6.2 (pore-forming subunit) and SUR1 (regulatory subunit that binds to sulfonylure...

Descripción completa

Detalles Bibliográficos
Autores principales: Song, Jingwen, Yang, Yunzhong, Mauvais-Jarvis, Franck, Wang, Yu-Ping, Niu, Tianhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5461698/
https://www.ncbi.nlm.nih.gov/pubmed/28587604
http://dx.doi.org/10.1186/s12881-017-0422-7
_version_ 1783242387416416256
author Song, Jingwen
Yang, Yunzhong
Mauvais-Jarvis, Franck
Wang, Yu-Ping
Niu, Tianhua
author_facet Song, Jingwen
Yang, Yunzhong
Mauvais-Jarvis, Franck
Wang, Yu-Ping
Niu, Tianhua
author_sort Song, Jingwen
collection PubMed
description BACKGROUND: Type 2 diabetes (T2D) is a worldwide epidemic with considerable health and economic consequences. Sulfonylureas are widely used drugs for the treatment of patients with T2D. KCNJ11 and ABCC8 encode the K(ir)6.2 (pore-forming subunit) and SUR1 (regulatory subunit that binds to sulfonylurea) of pancreatic β cell K(ATP) channel respectively with a critical role in insulin secretion and glucose homeostasis. TCF7L2 encodes a transcription factor expressed in pancreatic β cells that regulates insulin production and processing. Because mutations of these genes could affect insulin secretion stimulated by sulfonylureas, the aim of this study is to assess associations between molecular variants of KCNJ11, ABCC8 and TCF7L2 genes and response to sulfonylurea treatment and to predict their potential functional effects. METHODS: Based on a comprehensive literature search, we found 13 pharmacogenetic studies showing that single nucleotide polymorphisms (SNPs) located in KCNJ11: rs5219 (E23K), ABCC8: rs757110 (A1369S), rs1799854 (intron 15, exon 16 -3C/T), rs1799859 (R1273R), and TCF7L2: rs7903146 (intron 4) were significantly associated with responses to sulfonylureas. For in silico bioinformatics analysis, SIFT, PolyPhen-2, PANTHER, MutPred, and SNPs3D were applied for functional predictions of 36 coding (KCNJ11: 10, ABCC8: 24, and TCF7L2: 2; all are missense), and HaploReg v4.1, RegulomeDB, and Ensembl’s VEP were used to predict functions of 7 non-coding (KCNJ11: 1, ABCC8: 1, and TCF7L2: 5) SNPs, respectively. RESULTS: Based on various in silico tools, 8 KCNJ11 missense SNPs, 23 ABCC8 missense SNPs, and 2 TCF7L2 missense SNPs could affect protein functions. Of them, previous studies showed that mutant alleles of 4 KCNJ11 missense SNPs and 5 ABCC8 missense SNPs can be successfully rescued by sulfonylurea treatments. Further, 3 TCF7L2 non-coding SNPs (rs7903146, rs11196205 and rs12255372), can change motif(s) based on HaploReg v4.1 and are predicted as risk factors by Ensembl’s VEP. CONCLUSIONS: Our study indicates that a personalized medicine approach by tailoring sulfonylurea therapy of T2D patients according to their genotypes of KCNJ11, ABCC8, and TCF7L2 could attain an optimal treatment efficacy.
format Online
Article
Text
id pubmed-5461698
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-54616982017-06-07 KCNJ11, ABCC8 and TCF7L2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment Song, Jingwen Yang, Yunzhong Mauvais-Jarvis, Franck Wang, Yu-Ping Niu, Tianhua BMC Med Genet Research Article BACKGROUND: Type 2 diabetes (T2D) is a worldwide epidemic with considerable health and economic consequences. Sulfonylureas are widely used drugs for the treatment of patients with T2D. KCNJ11 and ABCC8 encode the K(ir)6.2 (pore-forming subunit) and SUR1 (regulatory subunit that binds to sulfonylurea) of pancreatic β cell K(ATP) channel respectively with a critical role in insulin secretion and glucose homeostasis. TCF7L2 encodes a transcription factor expressed in pancreatic β cells that regulates insulin production and processing. Because mutations of these genes could affect insulin secretion stimulated by sulfonylureas, the aim of this study is to assess associations between molecular variants of KCNJ11, ABCC8 and TCF7L2 genes and response to sulfonylurea treatment and to predict their potential functional effects. METHODS: Based on a comprehensive literature search, we found 13 pharmacogenetic studies showing that single nucleotide polymorphisms (SNPs) located in KCNJ11: rs5219 (E23K), ABCC8: rs757110 (A1369S), rs1799854 (intron 15, exon 16 -3C/T), rs1799859 (R1273R), and TCF7L2: rs7903146 (intron 4) were significantly associated with responses to sulfonylureas. For in silico bioinformatics analysis, SIFT, PolyPhen-2, PANTHER, MutPred, and SNPs3D were applied for functional predictions of 36 coding (KCNJ11: 10, ABCC8: 24, and TCF7L2: 2; all are missense), and HaploReg v4.1, RegulomeDB, and Ensembl’s VEP were used to predict functions of 7 non-coding (KCNJ11: 1, ABCC8: 1, and TCF7L2: 5) SNPs, respectively. RESULTS: Based on various in silico tools, 8 KCNJ11 missense SNPs, 23 ABCC8 missense SNPs, and 2 TCF7L2 missense SNPs could affect protein functions. Of them, previous studies showed that mutant alleles of 4 KCNJ11 missense SNPs and 5 ABCC8 missense SNPs can be successfully rescued by sulfonylurea treatments. Further, 3 TCF7L2 non-coding SNPs (rs7903146, rs11196205 and rs12255372), can change motif(s) based on HaploReg v4.1 and are predicted as risk factors by Ensembl’s VEP. CONCLUSIONS: Our study indicates that a personalized medicine approach by tailoring sulfonylurea therapy of T2D patients according to their genotypes of KCNJ11, ABCC8, and TCF7L2 could attain an optimal treatment efficacy. BioMed Central 2017-06-06 /pmc/articles/PMC5461698/ /pubmed/28587604 http://dx.doi.org/10.1186/s12881-017-0422-7 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Song, Jingwen
Yang, Yunzhong
Mauvais-Jarvis, Franck
Wang, Yu-Ping
Niu, Tianhua
KCNJ11, ABCC8 and TCF7L2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment
title KCNJ11, ABCC8 and TCF7L2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment
title_full KCNJ11, ABCC8 and TCF7L2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment
title_fullStr KCNJ11, ABCC8 and TCF7L2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment
title_full_unstemmed KCNJ11, ABCC8 and TCF7L2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment
title_short KCNJ11, ABCC8 and TCF7L2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment
title_sort kcnj11, abcc8 and tcf7l2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5461698/
https://www.ncbi.nlm.nih.gov/pubmed/28587604
http://dx.doi.org/10.1186/s12881-017-0422-7
work_keys_str_mv AT songjingwen kcnj11abcc8andtcf7l2polymorphismsandtheresponsetosulfonylureatreatmentinpatientswithtype2diabetesabioinformaticsassessment
AT yangyunzhong kcnj11abcc8andtcf7l2polymorphismsandtheresponsetosulfonylureatreatmentinpatientswithtype2diabetesabioinformaticsassessment
AT mauvaisjarvisfranck kcnj11abcc8andtcf7l2polymorphismsandtheresponsetosulfonylureatreatmentinpatientswithtype2diabetesabioinformaticsassessment
AT wangyuping kcnj11abcc8andtcf7l2polymorphismsandtheresponsetosulfonylureatreatmentinpatientswithtype2diabetesabioinformaticsassessment
AT niutianhua kcnj11abcc8andtcf7l2polymorphismsandtheresponsetosulfonylureatreatmentinpatientswithtype2diabetesabioinformaticsassessment