Meta-analysis of GWAS in East Asian populations had established 10 loci that were associated with type 2 diabetes. Eight of them were with genome-wide significance and two with a border line association. Since these data have not been studied in an independent Han Chinese population, we aimed to investigate the association of these susceptibility loci with type 2 diabetes in an independent Han Chinese population. We executed a case-control study in 2 000 Chinese by the SNPscan method. Firstly, the repetitive sequences of 10 loci were assessed. Next, we investigated the association of 8 SNPs out of 10 with type 2 diabetes and constructed the GRS of those 8 SNPs. Finally, the relationship of the 8 loci and diabetes-related traits was analyzed. Based on the fact, that highly repetitive sequences were detected in 2 SNPs, we investigated the remaining 8 SNPs. With the exception of four SNPs (CMIP rs16955379, PEPD rs3786897, PSMD6 rs831571, ZFAND3 rs9470794), the other SNPs had the same direction of effect (odds ratio [OR]>1.0) as in the original reports, especially GLIS3 rs7041847 and KCNK16 rs1535500 were significantly associated with type 2 diabetes (rs1535500: p=0.005, OR=1.224, 95% CI 1.062–1.409; rs7041847: p=0.035, OR=1.118, 95% CI 1.070–1.388). The GRS constructed from the 8 SNPs was significantly associated with type 2 diabetes in the Chinese population (p=0.004, OR=1.065, 95% CI: 1.021–1.111). Among the participants with 24≤BMI<28 kg/m2 the 8 SNPs were significantly associated with type 2 diabetes (p=0.040, OR=1.079, 95% CI: 1.003–1.160). In quantitative trait analyses, WWOX rs17797882 was associated with decreased HOMA-β and increased level of TG and HDL-Ch, while PEPD rs3786897 and MAEA rs6815464 were associated with decreased fasting plasma glucose, and KCNK16 rs1535500 has shown a significant association with increased T-Ch and PSMD6 rs831571 had a significant association with decreased HDL-Ch. In Conclusion, with high probability the 8 loci identified in the East Asian GWAS meta-analysis are associated with type 2 diabetes in the Han Chinese population.

Papillary thyroid carcinoma (PTC) is the most common malignant tumor of endocrine systems. Chromosomal instability (CIN) is crucial to the clinical prognoses of tumor patients. DNA methylation plays an important role in the regulation of gene expression and CIN. Based on PTC samples from The Cancer Genome Atlas database, we used multiple regression analyses to identify methylation patterns of CpG sites with the strongest correlation with gene expression. A total of 4,997 genes were obtained through combining the CpG sites, which were represented as featured DNA methylation patterns. In order to identify CIN-related epigenetic markers of PTC survival, we developed a method to characterize CIN based on DNA methylation patterns of genes using the Student’s t statistics. We found that 1,239 genes were highly associated with CIN. With the use of the log-rank test, univariate Cox regression analyses, and the Kaplan-Meier method, DNA methylation patterns of UBAC2 and ELOVL2, highly correlated with CIN, provided potential prognostic values for PTC. The higher these two genes, risk scores were correlated with worse PTC patient prognoses. Moreover, the ELOVL2 risk score was significantly different in the four stages of PTC, suggesting that it was related to the progress of PTC. The DNA methylation pattern associated with CIN may therefore be a good predictor of PTC survival.

Two recent studies found that RBMS1 gene rs7593730 and BCAR1 gene rs7202877 are related to type 2 diabetes. However, the association of these loci with type 2 diabetes mellitus (T2DM) has not been examined in Chinese. We performed a replication study to investigate the association of the 2 susceptibility loci with T2DM in the Chinese population. We genotyped 1961 Chinese participants (991 with T2DM and 970 controls) for each of the 2 single nucleotide polymorphisms (SNPs) rs7593730 in RBMS1 and rs7202877 near BCAR1 using SNPscan and examined their association with T2DM using logistic regression analysis. We also analyzed the correlation of the SNP alleles and clinical phenotypes. In additive model, genotype association analysis of BCAR1 rs7202877 loci revealed that the homozygous of rs7202877 GG carriers had significantly decreased T2DM risk compared to homozygous carriers of TT (P=0.038, OR 0.44, 95% CI 0.20-0.96). In the recessive model, the GG genotype GG had significantly decreased T2DM risk compared to GT+TT (P=0.043, OR 0.67, 95% CI 0.46-0.99). Allele G was statistically significantly correlated with TC (mmol/L) (P=0.036) and LDL-C (mmol/L) (P=0.007). As for rs7593730, the carriers of CT and TT genotype had significantly decreased T2DM risk compared to the carriers of CC genotype (CT: CC P=0.038, OR 0.71, 95% CI 0.51-0.98; TT: CC P=0.010, OR 0.32, 95% CI 0.13-0.76). In a dominant model, TT+CT: CC (P=0.013, OR 0.673, 95% CI 0.49-0.92) and in a recessive model, TT: CT+CC (P=0.019, OR 0.59, 95% CI 0.39-0.92). The T allele carriers had significantly decreased T2DM risk compared to the carriers of C (P=0.002, OR 0.65, 95% CI 0.50-0.86). Allele T was statistically correlated with FINS (P=0.010). In conclusion, our study showed that RBMS1 gene rs7593730 and BCAR1 gene rs7202877 were significantly associated with type 2 diabetes in the Chinese population.