The Association of Type 2 Diabetes Loci Identified in Genome-Wide Association Studies with Metabolic Syndrome and Its Components in a Chinese Population with Type 2 Diabetes

Abstract

Metabolic syndrome (MetS) is prevalent in type 2 diabetes (T2D) patients. The comorbidity of MetS and T2D increases the risk of cardiovascular complications. The aim of the present study was to determine the T2D-related genetic variants that contribute to MetS-related components in T2D patients of Chinese ancestry. We successfully genotyped 25 genome wide association study validated T2D-related single nucleotide polymorphisms (SNPs) among 5,169 T2D individuals and 4,560 normal glycemic controls recruited from the Chinese National Diabetes and Metabolic Disorders Study (DMS). We defined MetS in this population using the harmonized criteria (2009) combined with the Chinese criteria for abdominal obesity. The associations between SNPs and MetS-related components, as well as the associations between SNPs and risk for T2D with or without MetS, were subjected to logistic regression analysis adjusted for age and sex. Results showed that the T2D risk alleles of rs243021 located near BCL11A, rs10830963 in MTNR1B, and rs2237895 in KCNQ1 were related to a lower risk for abdominal obesity in T2D patients (rs243021: 0.92 (0.84, 1.00), P = 4.42 × 10−2; rs10830963: 0.92 (0.85, 1.00), P = 4.07 × 10−2; rs2237895: 0.89 (0.82, 0.98), P = 1.29 × 10−2). The T2D risk alleles of rs972283 near KLF14 contributed to a higher risk of elevated blood pressure (1.10 (1.00, 1.22), P = 4.48 × 10−2), while the T2D risk allele of rs7903146 in TCF7L2 was related to a lower risk for elevated blood pressure (0.74 (0.61, 0.90), P = 2.56 × 10−3). The T2D risk alleles of rs972283 near KLF14 and rs11634397 near ZFAND6 were associated with a higher risk for elevated triglycerides (rs972283: 1.11 (1.02, 1.24), P = 1.46 × 10−2; rs11634397: 1.14 (1.00, 1.29), P = 4.66 × 10−2), while the T2D risk alleles of rs780094 in GCKR and rs7903146 in TCF7L2 were related to a lower risk of elevated triglycerides (rs780094: 0.86 (0.80, 0.93), P = 1.35 × 10−4; rs7903146: 0.82 (0.69, 0.98), P = 3.18 × 10−2). The genotype risk score of the 25 T2D-related SNPs was related to a lower risk for abdominal obesity (P trend = 1.29 × 10−2) and lower waist circumference (P = 2.20 × 10−3). Genetic variants of WFS1, CDKAL1, CDKN2BAS, TCF7L2, HHEX, KCNQ1, TSPAN8/LGR5, FTO, and TCF2 were associated with the risk for T2D with MetS, as well as the risk for development of T2D with at least one of the MetS components (P < 0.05). In addition, genetic variants of BCL11A, GCKR, ADAMTS9, CDKAL1, KLF14, CDKN2BAS, TCF7L2, CDC123/CAMK1D, HHEX, MTNR1B, and KCNQ1 contributed to the risk for T2D without MetS (P < 0.05). In conclusion, these findings highlight the contribution of T2D-related genetic loci to MetS in a Chinese Han population. The study also provides insight into the pleotropic effects of genome-wide association loci of diabetes on metabolic regulation.

A Replication Study Identified Seven SNPs Associated with Quantitative Traits of Type 2 Diabetes among Chinese Population in A Cross-Sectional Study

“…HOMA-IR = FPG × FSIN/22.5, HOMA-β = FSIN × 20/(FPG − 3.5) (with serum insulin in mU/L and plasma glucose in mmol/L) [4].…”

“…The pathogenesis of T2D is complicated, although lifestyle is a great contributor to the T2D epidemic, genetic determinants can also affect the T2D susceptibility [3]. Individuals carrying risk alleles predisposed to T2D are mediated by insulin resistance or abnormal insulin secretion [4]. Insulin resistance [5] is one critical process to the development of T2D, which means the function of pancreatic β-cells is commonly normal and insulin secretion is sufficient, but the insulin receptors are insensitive to insulin levels and the ability to stimulate glucose utilization is decreasing, or impairments in insulin signal transduction, resulting in a compensatory hyperinsulinemia [6].…”

“…Birth weight-associated loci rs6931514 in gene CDKAL1 was associated with reduced insulin secretion in Europeans [15], which suggested that the genetic variation was affected differently among races and geographic areas [2]. Insulin resistance and insulin release were assessed by homeostasis model assessment (HOMA) in multiple studies based on fasting plasma glucose (FPG) and fasting serum insulin (FSIN) [4]. Thus, our aim was to replicate the relationship that has been confirmed in other ethnic groups, further, to explore novel loci that have never been clearly associated with T2D-related quantitative traits in the Chinese population, providing the pathogenesis of T2D.…”

<p>Type 2 Diabetes-Associated Genetic Polymorphisms as Potential Disease Predictors</p>

“…73 The expression of KvLQT1 repolarizes the action potential in cardiac muscles. 20 KCNQ1 is also expressed in other tissues such as adipose tissue, the pancreas, and the brain. 74 Mutations in KCN genes are associated with the development of diabetes.…”

Identification, expression and variation of theGNPDA2gene, and its association with body weight and fatness traits in chicken

“…The variations of GNPDA2 were also found to be associated with BMI or risk of obesity in children and old age population ( Elks et al , 2010 ; Mejía-Benítez et al , 2013 ; Murphy et al , 2013 ; Xi et al , 2013a ; Pillay et al , 2015 ). Furthermore, it also modulated the susceptibility of hypertension and type II diabetes ( Takeuchi et al , 2011 ; Robiou-du-Pont et al , 2013 ; Xi et al , 2013b ; Xi et al , 2014 ; Kong et al , 2015 ).…”