Publication: Impact of KCNQ1, CDKN2A/2B, CDKAL1, HHEX, MTNR1B, SLC30A8, TCF7L2, and UBE2E2 on risk of developing type 2 diabetes in Thai population
Issued Date
2018-06-05
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14712350
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2-s2.0-85048088254
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Mahidol University
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SCOPUS
Bibliographic Citation
BMC Medical Genetics. Vol.19, No.1 (2018)
Suggested Citation
Nattachet Plengvidhya, Chutima Chanprasert, Nalinee Chongjaroen, Pa thai Yenchitsomanus, Mayuree Homsanit, Watip Tangjittipokin Impact of KCNQ1, CDKN2A/2B, CDKAL1, HHEX, MTNR1B, SLC30A8, TCF7L2, and UBE2E2 on risk of developing type 2 diabetes in Thai population. BMC Medical Genetics. Vol.19, No.1 (2018). doi:10.1186/s12881-018-0614-9 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/45133
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Title
Impact of KCNQ1, CDKN2A/2B, CDKAL1, HHEX, MTNR1B, SLC30A8, TCF7L2, and UBE2E2 on risk of developing type 2 diabetes in Thai population
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Abstract
© 2018 The Author(s). Background: Several type 2 diabetes (T2D) susceptibility loci identified via genome-wide association studies were found to be replicated among various populations. However, the influence of these loci on T2D in Thai population is unknown. The aim of this study was to investigate the influence of eight single nucleotide polymorphisms (SNPs) reported in GWA studies on T2D and related quantitative traits in Thai population. Methods: Eight SNPs in or near the KCNQ1, CDKN2A/2B, SLC30A8, HHEX, CDKAL1, TCF7L2, MTNR1B, and UBE2E2 genes were genotyped. A case-control association study comprising 500 Thai patients with T2D and 500 ethnically-matched control subjects was conducted. Associations between SNPs and T2D were examined by logistic regression analysis. The impact of these SNPs on quantitative traits was examined by linear regression among case and control subjects. Results: Five SNPs in KCNQ1 (rs2237892), CDK2A/2B (rs108116610, SLC30A8 (rs13266634), TCF7L2 (rs7903146) and MTNR1B (rs1387153) were found to be marginally associated with risk of developing T2D, with odds ratios ranging from 1.43 to 2.02 (p=0.047 to 3.0×10-4) with adjustments for age, sex, and body mass index. Interestingly, SNP rs13266634 of SLC30A8 gene reached statistical significance after correcting for multiple testing (p=0.0003) (p<0.006 after Bonferroni correction). However, no significant association was detected between HHEX (rs1111875), CDKAL1 (rs7756992), or UBE2E2 (rs7612463) and T2D. We also observed association between rs10811661 and both waist circumference and waist-hip ratio (p=0.007 and p=0.023, respectively). In addition, rs13266634 in SLC30A8 was associated with glycated hemoglobin (p=0.018), and rs7903146 in TCF7L2 was associated with high-density lipoprotein cholesterol level (p=0.023). Conclusion: Of the eight genes included in our analysis, significant association was observed between KCNQ1, CDKN2A/2B, SLC30A8, TCF7L2, and MTNR1B loci and T2D in our Thai study population. Of these, CDKN2A/2B, SLC30A8, and TCF7L2 genes were also significantly associated with anthropometric, glycemic and lipid characteristics. Larger cohort studies and meta-analyses are needed to further confirm the effect of these variants in Thai population.