Network analysis identifies circulating miR-155 as predictive biomarker of type 2 diabetes mellitus development in obese patients: a pilot study

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Giuseppina Catanzaro
Federica Conte
Sofia Trocchianesi
Elena Splendiani
Viviana Maria Bimonte
Edoardo Mocini
Tiziana Filardi
Agnese Po
Zein Mersini Besharat
Maria Cristina Gentile
Paola Paci
Susanna Morano
Silvia Migliaccio
Elisabetta Ferretti
机构
[1] Sapienza University of Rome,Department of Experimental Medicine
[2] National Research Council (CNR),Institute for Systems Analysis and Computer Science “A. Ruberti” (IASI)
[3] University of Foro Italico,Department of Movement, Human and Health Sciences
[4] Sapienza University,Department of Molecular Medicine
[5] Sapienza University,Department of Computer, Control and Management Engineering
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Obesity is the main risk factor for many non-communicable diseases. In clinical practice, unspecific markers are used for the determination of metabolic alterations and inflammation, without allowing the characterization of subjects at higher risk of complications. Circulating microRNAs represent an attractive approach for early screening to identify subjects affected by obesity more at risk of developing connected pathologies. The aim of this study was the identification of circulating free and extracellular vesicles (EVs)-embedded microRNAs able to identify obese patients at higher risk of type 2 diabetes (DM2). The expression data of circulating microRNAs derived from obese patients (OB), with DM2 (OBDM) and healthy donors were combined with clinical data, through network-based methodology implemented by weighted gene co-expression network analysis. The six circulating microRNAs overexpressed in OBDM patients were evaluated in a second group of patients, confirming the overexpression of miR-155-5p in OBDM patients. Interestingly, the combination of miR-155-5p with serum levels of IL-8, Leptin and RAGE was useful to identify OB patients most at risk of developing DM2. These results suggest that miR-155-5p is a potential circulating biomarker for DM2 and that the combination of this microRNA with other inflammatory markers in OB patients can predict the risk of developing DM2.
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