Abstract
BackgroundObesity is reaching epidemic proportions and represents a significant risk factor for cardiovascular disease, diabetes, and cancer.MethodsTo explore the relationship between increased body mass and gene expression in blood, we conducted whole-genome expression profiling of whole blood from seventeen obese and seventeen well matched lean subjects. Gene expression data was analyzed at the individual gene and pathway level and a preliminary assessment of the predictive value of blood gene expression profiles in obesity was carried out.ResultsPrincipal components analysis of whole-blood gene expression data from obese and lean subjects led to efficient separation of the two cohorts. Pathway analysis by gene-set enrichment demonstrated increased transcript levels for genes belonging to the "ribosome", "apoptosis" and "oxidative phosphorylation" pathways in the obese cohort, consistent with an altered metabolic state including increased protein synthesis, enhanced cell death from proinflammatory or lipotoxic stimuli, and increased energy demands. A subset of pathway-specific genes acted as efficient predictors of obese or lean class membership when used in Naive Bayes or logistic regression based classifiers.ConclusionThis study provides a comprehensive characterization of the whole blood transcriptome in obesity and demonstrates that the investigation of gene expression profiles from whole blood can inform and illustrate the biological processes related to regulation of body mass. Additionally, the ability of pathway-related gene expression to predict class membership suggests the feasibility of a similar approach for identifying clinically useful blood-based predictors of weight loss success following dietary or surgical interventions.
Highlights
Obesity is reaching epidemic proportions and represents a significant risk factor for cardiovascular disease, diabetes, and cancer
Ascertainment of data quality We ascertained the overall quality of the whole genome expression profiling signals by comparing the Affymetrix microarray generated expression patterns of a subset of 61 genes to expression signals generated by real-time, quantitative PCR (Taqman)
Since gene expression measures were used as input for the PCA analysis, these results suggest that the differences in blood transcript levels between obese and lean subjects were significant and informative enough to cause a separation between the two classes
Summary
Obesity is reaching epidemic proportions and represents a significant risk factor for cardiovascular disease, diabetes, and cancer. In addition to DNA sequence variants, genetic influences are manifested through differences in gene transcription, leading to differential messenger RNA levels While such differences might be expected to occur in biologically relevant tissues (muscle and adipose tissue in obesity, for example), several recent studies have demonstrated an alteration in the peripheral blood transcriptome in diseases of non-hematologic origin. These findings raise the intriguing possibility that blood transcriptome profiles might provide a valid biological readout for otherwise hard to study disease processes in humans and generate information of high predictive and diagnostic content In line with this argument, we postulated that differences in transcript abundance might occur in blood from obese subjects compared to lean subjects, as a consequence of either pre-existing genetic variations, or as an adaptive response to obesity, independent of the genetic background. The identification of adiposity related gene expression differences in a clinically accessible tissue such as blood leads the way for the determination of biomarkers of weight regulation that could be implemented in a clinical setting
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