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Identification of an early transcriptomic signature of insulin resistance and related diseases in lymphomonocytes of healthy subjects.
Matone, Alice; Derlindati, Eleonora; Marchetti, Luca; Spigoni, Valentina; Dei Cas, Alessandra; Montanini, Barbara; Ardigò, Diego; Zavaroni, Ivana; Priami, Corrado; Bonadonna, Riccardo C.
Afiliación
  • Matone A; The Microsoft Research-University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
  • Derlindati E; Department of Medicine and Surgery, University of Parma, Parma, Italy.
  • Marchetti L; The Microsoft Research-University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
  • Spigoni V; Department of Medicine and Surgery, University of Parma, Parma, Italy.
  • Dei Cas A; Department of Medicine and Surgery, University of Parma, Parma, Italy.
  • Montanini B; Division of Endocrinology and Metabolic Diseases, Azienda Ospedaliero-Universitaria of Parma, Parma, Italy.
  • Ardigò D; Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy.
  • Zavaroni I; Department of Medicine and Surgery, University of Parma, Parma, Italy.
  • Priami C; Department of Medicine and Surgery, University of Parma, Parma, Italy.
  • Bonadonna RC; Division of Endocrinology and Metabolic Diseases, Azienda Ospedaliero-Universitaria of Parma, Parma, Italy.
PLoS One ; 12(8): e0182559, 2017.
Article en En | MEDLINE | ID: mdl-28777829
ABSTRACT
Insulin resistance is considered to be a pathogenetic mechanism in several and diverse diseases (e.g. type 2 diabetes, atherosclerosis) often antedating them in apparently healthy subjects. The aim of this study is to investigate with a microarray based approach whether IR per se is characterized by a specific pattern of gene expression. For this purpose we analyzed the transcriptomic profile of peripheral blood mononuclear cells in two groups (10 subjects each) of healthy individuals, with extreme insulin resistance or sensitivity, matched for BMI, age and gender, selected within the MultiKnowledge Study cohort (n = 148). Data were analyzed with an ad-hoc rank-based classification method. 321 genes composed the gene set distinguishing the insulin resistant and sensitive groups, within which the "Adrenergic signaling in cardiomyocytes" KEGG pathway was significantly represented, suggesting a pattern of increased intracellular cAMP and Ca2+, and apoptosis in the IR group. The same pathway allowed to discriminate between insulin resistance and insulin sensitive subjects with BMI >25, supporting his role as a biomarker of IR. Moreover, ASCM pathway harbored biomarkers able to distinguish healthy and diseased subjects (from publicly available data sets) in IR-related diseases involving excitable cells type 2 diabetes, chronic heart failure, and Alzheimer's disease. The altered gene expression profile of the ASCM pathway is an early molecular signature of IR and could provide a common molecular pathogenetic platform for IR-related disorders, possibly representing an important aid in the efforts aiming at preventing, early detecting and optimally treating IR-related diseases.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Resistencia a la Insulina / Leucocitos Mononucleares / Biomarcadores / Diabetes Mellitus Tipo 2 / Enfermedad de Alzheimer / Transcriptoma / Insuficiencia Cardíaca Tipo de estudio: Diagnostic_studies / Observational_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2017 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Resistencia a la Insulina / Leucocitos Mononucleares / Biomarcadores / Diabetes Mellitus Tipo 2 / Enfermedad de Alzheimer / Transcriptoma / Insuficiencia Cardíaca Tipo de estudio: Diagnostic_studies / Observational_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2017 Tipo del documento: Article País de afiliación: Italia
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