Use of genome-wide expression data to mine the "Gray Zone" of GWA studies leads to novel candidate obesity genes.

ABSTRACT: To get beyond the "low-hanging fruits" so far identified by genome-wide association (GWA) studies, new methods must be developed in order to discover the numerous remaining genes that estimates of heritability indicate should be contributing to complex human phenotypes, such as obesity. Here we describe a novel integrative method for complex disease gene identification utilizing both genome-wide transcript profiling of adipose tissue samples and consequent analysis of genome-wide association data generated in large SNP scans. We infer causality of genes with obesity by employing a unique set of monozygotic twin pairs discordant for BMI (n = 13 pairs, age 24-28 years, 15.4 kg mean weight difference) and contrast the transcript profiles with those from a larger sample of non-related adult in

SUBMITTER: Naukkarinen J 

PROVIDER: S-EPMC2880558 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature