Construction of an Algorithm for the Prediction of Diabetic Nephropathy using a Computational Approach
Date: 8 April 2009 (Wednesday)
Time: 12:30pm - 2:00pm
Venue: 126, C N Yang Reading Room, Science Centre North Block
Speaker: Prof. TSUI Kwok Wing Stephen, Professor, Department of Biochemistry (Medicine), The Chinese University of Hong Kong
Abstract: Diabetic nephropathy (DN) is a common and serious complication of diabetes, affecting roughly 60% of Asian diabetic patients. It is also a major cause of diabetes-related death in Asian population. Development of DN has been known to result from complex interactions between multiple genetic and environmental factors. Although association studies between single nucleotide polymorphisms (SNPs) of candidate gene and DN have been led to identification of numerous susceptibility loci, however, the information of single SNP alone is insufficient to evaluate the risk of multifactorial DN. It remains a significant challenge for clinical researchers to understand the latent cross-link amongst multiple genetic markers and effectively use combined information from genetic and clinical markers to predict the risk of DN. Since DN and cardiovascular complications share common risk factors including hypertension, dyslipidemia and obesity, we have genotyped 106 SNPs of 64 candidate genes implicated in cardiovascular complication through dysregulation of lipid and homocysteine metabolism, endothelial function, thrombosis and coagulation, inflammation, stress responses and natriuresis in a consecutive cohort of Chinese Type 2 diabetic patients. The aim of the present study was to investigate a set of predictors of DN amongst these SNPs by using a computational data mining approach.
