Matone Alice, Derlindati Eleonora, Marchetti Luca, Spigoni Valentina, Dei Cas Alessandra, Montanini Barbara, Ardigò Diego, Zavaroni Ivana, Priami Corrado, Bonadonna Riccardo C
The Microsoft Research-University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
Department of Medicine and Surgery, University of Parma, Parma, Italy.
PLoS One. 2017 Aug 4;12(8):e0182559. doi: 10.1371/journal.pone.0182559. eCollection 2017.
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.
胰岛素抵抗被认为是多种不同疾病（如2型糖尿病、动脉粥样硬化）的发病机制，在明显健康的个体中往往早于这些疾病出现。本研究的目的是采用基于微阵列的方法，研究胰岛素抵抗本身是否具有特定的基因表达模式。为此，我们在多知识研究队列（n = 148）中，分析了两组（每组10名受试者）健康个体外周血单核细胞的转录组谱，这两组个体的体重指数、年龄和性别相匹配，但胰岛素抵抗或敏感性极端不同。数据采用基于秩的特设分类方法进行分析。321个基因构成了区分胰岛素抵抗组和敏感组的基因集，其中“心肌细胞中的肾上腺素能信号传导”KEGG通路显著富集，提示胰岛素抵抗组细胞内cAMP和Ca2+增加以及细胞凋亡的模式。同样的通路能够区分体重指数>25的胰岛素抵抗和胰岛素敏感受试者，支持其作为胰岛素抵抗生物标志物的作用。此外，在涉及可兴奋细胞的胰岛素抵抗相关疾病（2型糖尿病、慢性心力衰竭和阿尔茨海默病）中，ASCM通路含有能够区分健康和患病受试者（来自公开可用数据集）的生物标志物。ASCM通路基因表达谱的改变是胰岛素抵抗的早期分子特征，可为胰岛素抵抗相关疾病提供一个共同的分子发病平台，可能对预防、早期检测和优化治疗胰岛素抵抗相关疾病的努力具有重要帮助。
