Journal Article

Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance

Peter J. Park, Sek Won Kong, Toma Tebaldi, Weil R. Lai, Simon Kasif and Isaac S. Kohane

in Bioinformatics

Volume 25, issue 23, pages 3121-3127
Published in print December 2009 | ISSN: 1367-4803
Published online September 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp559

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Motivation: Type 2 diabetes is a chronic metabolic disease that involves both environmental and genetic factors. To understand the genetics of type 2 diabetes and insulin resistance, the DIabetes Genome Anatomy Project (DGAP) was launched to profile gene expression in a variety of related animal models and human subjects. We asked whether these heterogeneous models can be integrated to provide consistent and robust biological insights into the biology of insulin resistance.

Results: We perform integrative analysis of the 16 DGAP data sets that span multiple tissues, conditions, array types, laboratories, species, genetic backgrounds and study designs. For each data set, we identify differentially expressed genes compared with control. Then, for the combined data, we rank genes according to the frequency with which they were found to be statistically significant across data sets. This analysis reveals RetSat as a widely shared component of mechanisms involved in insulin resistance and sensitivity and adds to the growing importance of the retinol pathway in diabetes, adipogenesis and insulin resistance. Top candidates obtained from our analysis have been confirmed in recent laboratory studies.

Contact: Isaac_kohane@harvard.edu

Journal Article.  4419 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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