CpG single nucleotide polymorphisms of the insulin signaling pathway associated with the risk of prediabetic status/type 2 diabetes in Chinese population

Abstract Aims: Cytosine-phosphate-guanine single nucleotide polymorphisms (CpG SNPs) have been identified as new markers in human diseases. We aimed to evaluate the contribution of 29 CpG SNPs in the insulin signaling pathways to the risk of prediabetes and type 2 diabetes (T2D) in Han Chinese. Materials and methods: We recruited 708 T2D subjects, 253 prediabetes subjects and 575 healthy controls from 16 community health service centers (CHSC) in Shenzhen Nanshan district. Detailed clinical information and DNA samples were collected. A total of 29 CpG SNPs of the insulin signaling pathways were sequenced using the MassARRAY platform. Binary logistic regression was applied to evaluate the association between these 29 CpG SNPs with prediabetes and T2D after adjusted the relevant confounding factors. The potential interactions among the 29 CpG SNPs were conducted by the generalized multifactor dimensionality reduction (GMDR). Results: Significant associations are found between KRAS rs7311692 [Padjusted = 0.009, OR = 0.562(0.363-0.868) by allele] and CBLC rs2965143 [Padjusted = 0.008, OR = 1.591(1.128-2.242) under the dominant model] with prediabetes. A further breakdown analysis by gender identify a significant association between MAPK9 rs1363513 and T2D risk in males [Padjusted = 0.004, OR = 0.57(0.399-0.836) by allele], while FLOT2 rs4795473 is associated with prediabetes in females (P = 0.007 by genotype). However, no significant effect of potential interaction is observed among the 29 CpG SNPs. Conclusion: These results indicated that KRAS rs7311692, CBLC rs2965143 and FLOT2 rs4795473 are related with prediabetes, while MAPK9 rs1363513 was associated with male T2D.