Melatonin receptor 1 B polymorphisms associated with the risk of gestational diabetes mellitus - Yang Jae-Hyug; Kim Moon-Young; Choi June; Chung Jin; Kim Min-Hyoung; Lee Si; Park Sunmin; Baik Sei; Park Byung-Lae; Cheong Hyun; Kim Jason Y; Cho Dong-Hee; et al. (BMC, 2011)
Abstract Backgrounds Two SNPs in melatonin receptor 1B gene, rs10830963 and rs1387153 showed significant associations with fasting plasma glucose levels and the risk of Type 2 Diabetes Mellitus (T2DM) in previous studies. Since T2DM and gestational diabetes mellitus (GDM) share similar characteristics, we suspected that the two genetic polymorphisms in MTNR1B may be associated with GDM, and conducted association studies between the polymorphisms and the disease. Furthermore, we also examined genetic effects of the two polymorphisms with various diabetes-related phenotypes. Methods A total of 1,918 subjects (928 GDM patients and 990 controls) were used for the study. Two MTNR1B polymorphisms were genotyped using TaqMan assay. The allele distributions of SNPs were evaluated by x2 models calculating odds ratios (ORs), 95% confidence intervals (CIs), and corresponding P values. Multiple regressions were used for association analyses of GDM-related traits. Finally, conditional analyses were also performed. Results We found significant associations between the two genetic variants and GDM, rs10830963, with a corrected P value of 0.0001, and rs1387153, with the corrected P value of 0.0008. In addition, we also found that the two SNPs were associated with various phenotypes such as homeostasis model assessment of beta-cell function and fasting glucose levels. Further conditional analyses results suggested that rs10830963 might be more likely functional in case/control analysis, although not clear in GDM-related phenotype analyses. Conclusion There have been studies that found associations between genetic variants of other genes and GDM, this is the first study that found significant associations between SNPs of MTNR1B and GDM. The genetic effects of two SNPs identified in this study would be helpful in understanding the insight of GDM and other diabetes-related disorders.