A meta-analysis of gene expression profiles to discover obesity signatures in peripheral blood mononuclear cells

Abstract

Obesity is typically defined as a state that abnormal amount of body fat accumulation. Due to its association with various disease pathogenesis, revealing biological mechanisms and constructing a model of obesity becomes popular. Among the studies about the obesity, gene signatures within blood tissue were often proceeded because of its interrelation with fat tissues. However, previous studies between obese patients and controls had limitation about lack of sample number and high model-dependent variability. These problems made severe difficulty for the construction of general obesity model in blood. To overcome this drawback, we constructed meta-dataset by merging four blood transcriptome microarray datasets between obesity patients and control subjects. Next we introduced a statistical testing and several classification task based on a combination of random partitioning, t-test and SVM-RFE. We ensured a validity of our own selection method by cross-validation. As a consequence of our approach, 50 differential gene expression signatures appeared among 124 obesity patients has been obtained. Furthermore we demonstrated our finding was associated with key obesity mechanisms and some diseases caused by obesity. In conclusion, we revealed obesity signatures in blood tissues which can be applied to an effect of an obesity on the entire body and obesity-related disease pathogenesis studies.