Genetic and clinical variables identify predictors for chronic kidney disease in type 2 diabetes.

Type 2 diabetes and chronic kidney disease (CKD) may share common risk factors. Here we used a 3-stage procedure to discover novel predictors of CKD by repeatedly applying a stepwise selection based on the Akaike information criterion to subsamples of a prospective complete-case cohort of 2755 patients. This cohort encompassed 25 clinical variables and 36 genetic variants associated with type 2 diabetes, obesity, or fasting plasma glucose. We compared the performance of the clinical, genetic, and clinico-genomic models and used net reclassification improvement to evaluate the impact of top selected genetic variants to the clinico-genomic model. Associations of selected genetic variants with CKD were validated in 2 independent cohorts followed by meta-analyses. Among the top 6 single-nucleotide polymorphisms selected from clinico-genomic data, three (rs478333 of G6PC2, rs7754840 and rs7756992 of CDKAL1) contributed toward the improvement of prediction performance. The variant rs478333 was associated with rapid decline (over 4% per year) in estimated glomerular filtration rate. In a meta-analysis of 2 replication cohorts, the variants rs478333 and rs7754840 showed significant associations with CKD after adjustment for conventional risk factors. Thus, this novel 3-stage approach to a clinico-genomic data set identified 3 novel genetic predictors of CKD in type 2 diabetes. This method can be applied to similar data sets containing clinical and genetic variables to select predictors for clinical outcomes.

Use of net reclassification improvement (NRI) method confirms the utility of combined genetic risk score to predict type 2 diabetes.

BACKGROUND: Recent genome-wide association studies (GWAS) identified more than 70 novel loci for type 2 diabetes (T2D), some of which have been widely replicated in Asian populations. In this study, we investigated their individual and combined effects on T2D in a Chinese population. METHODOLOGY: We selected 14 single nucleotide polymorphisms (SNPs) in T2D genes relating to beta-cell function validated in Asian populations and genotyped them in 5882 Chinese T2D patients and 2569 healthy controls. A combined genetic score (CGS) was calculated by summing up the number of risk alleles or weighted by the effect size for each SNP under an additive genetic model. We tested for associations by either logistic or linear regression analysis for T2D and quantitative traits, respectively. The contribution of the CGS for predicting T2D risk was evaluated by receiver operating characteristic (ROC) analysis and net reclassification improvement (NRI). RESULTS: We observed consistent and significant associations of IGF2BP2, WFS1, CDKAL1, SLC30A8, CDKN2A/B, HHEX, TCF7L2 and KCNQ1 (8.5×10(-18)

Association of the PPARG Pro12Ala polymorphism with type 2 diabetes and incident coronary heart disease in a Hong Kong Chinese population.

AIMS: We examined the risk association between single nucleotide polymorphisms (SNPs) in eleven candidate genes with type 2 diabetes (T2D). T2D-associated polymorphisms were also examined for prediction of incident CHD. METHODS: 113 tagging SNPs were genotyped in stage 1 (467 T2D cases, 290 controls), and 15 SNPs were analyzed in the final cohort (1462 T2D cases, 600 controls). Three T2D-associated SNPs were further tested for prediction of CHD within a subset of 1417 T2D cases free of CHD at enrolment. RESULTS: In the case-control analysis, PPARG rs1801282 (Pro12Ala) (OR=1.48 (1.02-2.16)), ADIPOQ rs1063539 (OR=1.17 (1.01-1.35)), and HNF4A rs1884614 (OR=1.16 (1.00-1.32) were associated with T2D (P(allelic)<0.05). Joint analysis of rs1801282-C, rs1063539-G, and rs1884614-T risk alleles showed an additive dosage effect (P for trend=0.001). Moreover, carriers with two PPARG rs1801282-C risk alleles were associated with an increased risk of incident CHD (HR=4.38 (1.03-18.57), P=0.045) in T2D patients in the prospective analysis. CONCLUSIONS: Genetic variants of PPARG, ADIPOQ and HNF4A were individually and jointly associated with T2D in Hong Kong Chinese. The PPARG Pro12 risk allele contributed to increased risk for both T2D and CHD.

Genetic variants of the protein kinase C-beta 1 gene and development of end-stage renal disease in patients with type 2 diabetes.

CONTEXT: Protein kinase C-beta (PKC-beta) is a cell-signaling intermediate implicated in development of diabetic complications. OBJECTIVE: To examine the risk association of PKC-beta 1 gene (PRKCB1) polymorphisms and end-stage renal disease (ESRD) in an 8-year prospective cohort of Chinese patients with type 2 diabetes. DESIGN, SETTING, AND PARTICIPANTS: We genotyped 18 common tag single-nucleotide polymorphisms (SNPs) that span the PRKCB1 gene (r(2) = 0.80) in 1172 Chinese patients (recruited 1995-1998) without renal disease at baseline. A validation cohort included an additional 1049 patients with early-onset diabetes who were free of renal disease at baseline and were recruited after 1998. MAIN OUTCOME MEASURES: Associations of PRKCB1 polymorphisms under additive, dominant, and recessive genetic models with new onset of ESRD (defined as estimated glomerular filtration rate <15 mL/min/1.73 m(2) or dialysis or renal-related death) were assessed by Cox proportional hazard regression, adjusted for all conventional risk factors including use of medications. RESULTS: After a mean (SD) of 7.9 (1.9) years, 90 patients (7.7%) progressed to ESRD. Four common SNPs were associated with ESRD (P < .05). The closely linked T allele at rs3760106 and G allele rs2575390 (r(2) = 0.98) showed the strongest association with ESRD (hazard ratio [HR], 2.25; 95% confidence interval [CI], 1.31-3.87; P = .003, and HR, 2.26; 95% CI, 1.31-3.88; P = .003, respectively). Four common variants predicted ESRD in separate models. The HR for ESRD increased with increasing number of risk alleles (P < .001) in the joint effect analysis. The adjusted risk for ESRD was 6.04 (95% CI, 2.00-18.31) for patients with 4 risk alleles compared with patients with 0 or 1 risk allele. Incidence was 4.4 per 1000 person-years (95% CI, 0.5-8.2) among individuals with 0 or 1 risk allele compared with 20.0 per 1000 person-years (95% CI, 8.8-31.1) in those carrying 4 risk alleles (6.9% of the cohort). These results were validated in a separate prospective cohort of young-onset diabetic patients. Of 1049 patients in the validation cohort, 151 (14.3%) developed chronic kidney disease (CKD) during follow-up, and there were significant associations between both the T allele of rs3760106 and the G allele of rs2575390 and development of CKD (HR, 1.68; 95% CI, 1.10-2.57; P = .02, and HR, 1.62; 95% CI, 1.07-2.47; P = .02, respectively). CONCLUSION: Genetic variants in the PRKCB1 gene were independently associated with development of ESRD in Chinese patients with type 2 diabetes.

Implication of genetic variants near NEGR1, SEC16B, TMEM18, ETV5/DGKG, GNPDA2, LIN7C/BDNF, MTCH2, BCDIN3D/FAIM2, SH2B1, FTO, MC4R, and KCTD15 with obesity and type 2 diabetes in 7705 Chinese.

OBJECTIVE: Recent genome-wide association studies have identified multiple novel loci associated with obesity in Europeans. We hypothesized that these genetic variants may be associated with obesity and type 2 diabetes (T2D) in Chinese. RESEARCH DESIGN AND METHODS: We examined 14 associated single-nucleotide polymorphisms at 12 loci (NEGR1, SEC16B, TMEM18, ETV5/DGKG, GNPDA2, LIN7C/BDNF, MTCH2, BCDIN3D/FAIM2, SH2B1, FTO, MC4R, and KCTD15) in 605 healthy adults, 1087 healthy adolescents and 6013 T2D patients from Hong Kong. RESULTS: The European at-risk alleles at five loci including GNPDA2, BCDIN3D/FAIM2, SH2B1, FTO, and KCTD15 were significantly associated with increased body mass index (BMI), waist circumference (4.5 x 10(-8) < P < 0.024), and/or obesity risk (odds ratio 1.14-1.22, 2.0 x 10(-5) < P < 0.002) in our Chinese populations. The former four loci as well as LIN7C/BDNF were also modestly associated with T2D risk (odds ratio 1.09-1.22, 0.008 < P < 0.041), but the associations were lost after adjustment for BMI, suggesting their roles in T2D risk are mediated through modulation of adiposity. Joint effect analyses of the five adiposity loci revealed an increase of about 0.29 kg/m(2) in BMI with each additional copy of at-risk allele (P(trend) = 4.2 x 10(-12)). CONCLUSIONS: Our findings support the important contribution of GNPDA2, BCDIN3D/FAIM2, SH2B1, FTO, and KCTD15 in the regulation of adiposity, which in turn affects T2D risk in Chinese.