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

Abstract

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.

• Authors: Guozhi Jiang, Cheng Hu, Claudia H T Tam, Eric S H Lau, Ying Wang, Andrea O Y Luk, Xilin Yang, Alice P S Kong, Janice S K Ho, Vincent K L Lam, Heung Man Lee, Jie Wang, Rong Zhang, Stephen K W Tsui, Maggie C Y Ng, Cheuk-Chun Szeto, Weiping Jia, Xiaodan Fan, Wing Yee So, Juliana C N Chan, Ronald C W Ma
• Journal: Kidney international (Kidney Int) Vol. 89 Issue 2 Pg. 411-20 (Feb 2016) ISSN: 1523-1755 [Electronic] United States
• PMID: 26806836 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

Chemical References

• Blood Glucose

Topics

• Adult
• Aged
• Blood Glucose
• Diabetes Mellitus, Type 2 (complications, genetics)
• Diabetic Nephropathies (blood, genetics)
• Female
• Humans
• Male
• Middle Aged
• Obesity (complications)
• Prospective Studies
• Renal Insufficiency, Chronic (etiology)