Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance.
BACKGROUND
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.
Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology, Center of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.
Peter J
PJ
Park
Sek Won
SW
Kong
Toma
T
Tebaldi
Weil R
WR
Lai
Simon
S
Kasif
Isaac S
IS
Kohane
D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics* / Q000378:metabolism; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D007333:Insulin Resistance / Q000235:genetics*; D014801:Vitamin A / Q000378:metabolism*
D014801:Vitamin A