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Activity Number: 182
Type: Invited
Date/Time: Monday, August 7, 2006 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing
Abstract - #305175
Title: The Genetics of Insulin Resistance: Clusters and SNPs
Author(s): Richard A. Olshen*+
Companies: Stanford University
Address: Division of Biostatistics, Stanford, CA, 94305-5405,
Keywords: clustering ; quantization ; bootstrapping ; SNPS ; insulin ; resistance
Abstract:

This talk is in part about Gauss mixture vector quantization as it applies to clustering data from two-hour oral glucose tolerance tests, triglycerides, total cholesterol, HDL, and waist/hip ratio after removing the effects of age and body mass index. Subjects are 557 Chinese women in 285 sibships from the SAPPHIRe network of the NHLBI's Family Blood Pressure Program. Clustering enables precise definition of insulin resistance. There are concerns regarding how to eliminate the joint effect of age and BMI and of how to bootstrap appropriately from the dependent data. Results from SNP genotyping in genes that are candidates for hypertension are applied with other measures to classify individuals of unknown cluster membership into clusters. The work, which is in progress as this abstract is being written, is joint with Sangho Yoon, Alfred Lin, and the SAPPHIRe team.

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