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

BMC Med Genet. 2017 Jun 6;18(1):64. doi: 10.1186/s12881-017-0422-7.

Abstract

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 Kir6.2 (pore-forming subunit) and SUR1 (regulatory subunit that binds to sulfonylurea) of pancreatic β cell KATP 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.

Keywords: ABCC8; Bioinformatics; In silico; KCNJ11; Pharmacogenetics; Single nucleotide polymorphism; Sulfonylurea; TCF7L2; Type 2 diabetes.

MeSH terms

  • Alleles
  • Computational Biology
  • Diabetes Mellitus, Type 2 / drug therapy
  • Diabetes Mellitus, Type 2 / genetics*
  • Exons
  • Genotype
  • Humans
  • Insulin / metabolism
  • Insulin Secretion
  • Insulin-Secreting Cells
  • Mutation, Missense
  • Observational Studies as Topic
  • Polymorphism, Single Nucleotide
  • Potassium Channels, Inwardly Rectifying / genetics*
  • Precision Medicine
  • Randomized Controlled Trials as Topic
  • Sulfonylurea Compounds / therapeutic use*
  • Sulfonylurea Receptors / genetics*
  • Transcription Factor 7-Like 2 Protein / genetics*

Substances

  • ABCC8 protein, human
  • Insulin
  • Kir6.2 channel
  • Potassium Channels, Inwardly Rectifying
  • Sulfonylurea Compounds
  • Sulfonylurea Receptors
  • TCF7L2 protein, human
  • Transcription Factor 7-Like 2 Protein