Background and aims: Gene expression profile (GEP) of peripheral blood mononuclear cells (PBMCs) is significantly affected by various diseases and may serve as biomarker of pathological changes occurring in other tissues. The aim of our study was to investigate whether insulin resistance (IR) per se is characterized by a specific pattern of GEP. Materials and methods: 150 healthy young adults, were recruited in a cardiovascular risk assessment study (Multi-Knowledge project).Two groups of 10 subjects with extreme HOMAIR indices (High HOMA:4.0±2.8; Low HOMA:0.5±0.1), but with normal, similar BMI (22.2±2.6 vs 22.5±2.2 kg/m2), and comparable age (33.9±6.2 vs 40.2± 11.3 years) and gender (7 M and 3 F in both groups) were selected. Standard anthropometric, hemodynamic, and metabolic variables were assessed. GEP of PBMCs from all subjects was evaluated using Agilent whole genome oligonucleotide mRNA microarrays. Data were analyzed with a novel ad-hoc rank-based classification method, optimized to extract a gene expression signature with highest power and statistical significance (p at least<0.005) to discriminate the two groups. Gene enrichment analysis was applied on the significant differentially expressed list of genes. All analyses were performed with R and Matlab. Results:We identified a set of 512 probes corresponding to 321 annotated genes which summarize the characteristics of each sample and allow distinguishing Low HOMA and High HOMA subjects with an accuracy of 100%, according to a 5-fold cross-validation approach. Gene enrichment analysis of the 321 genes showed significant enrichment for the KEGG pathway “Adrenergic signaling in cardiomyocytes”, in which differentially expressed genes were compatible with a cluster of alterations, including increased intracellular cAMP and Ca2+ and accelerated apoptosis in the High HOMA group. We hypothesized that this pathway should biomark chronic heart failure (CHF), of which IR is a known risk factor. In two publicly available gene expression data sets (GSE21125 and GSE9128) we investigated whether the genes in the pathway of interest could differentiate between patients with CHF and controls. Two biomarkers (length 41 and 22, respectively) were found with high discriminant accuracy (95%), at a significant p value (p<0.02), overlapping with the “adrenergic signaling in cardiomyocytes” pathway. Conclusion: GEP of the “adrenergic signaling pathway in cardiomyocytes” in lymphomocytes is a fingerprint of IR and is implicated also as a biomarker of patients with CHF. This may be a major molecular platform linking IR to CHF.
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