Ospedale Pediatrico Bambino Gesù, Gene Expression-Microarrays Laboratory, V.le di San Paolo 15, 00146, Rome, Italy.
Rheumatology Unit, Department of Internal Medicine and Medical Specialities, Sapienza University of Rome, Rome, Italy.
Mol Neurobiol. 2017 Nov;54(9):7129-7136. doi: 10.1007/s12035-016-0235-2. Epub 2016 Oct 29.
This work was aimed at investigating the circulating microRNA (miRNA) profiles in serum and saliva of patients affected by fibromyalgia syndrome (FM), correlating their expression values with clinical and clinimetric parameters and to suggest a mathematical model for the diagnosis of FM. A number of 14 FM patients and sex- and age-matched controls were enrolled in our study. The expression of a panel of 179 miRNAs was evaluated by qPCR. Statistical analyses were performed in order to obtain a mathematical linear model, which could be employed as a supporting tool in the diagnosis of FM. Bioinformatics analysis on miRNA targets were performed to obtain the relevant biological processes related to FM syndrome and to characterize in details the disease. Six miRNAs were found downregulated in FM patients compared to controls. Five of these miRNAs have been included in a linear predictive model that reached a very high sensitivity (100 %) and a high specificity (83.3 %). Moreover, miR-320b displayed a significant negative correlation (r = -0.608 and p = 0.036) with ZSDS score. Finally, several biological processes related to brain function/development and muscular functions were found potentially implicated in FM syndrome. Our study suggests that the study of circulating miRNA profiles coupled to statistical and bioinformatics analyses is a useful tool to better characterize the FM syndrome and to propose a preliminary model for its diagnosis.
这项工作旨在研究纤维肌痛综合征 (FM) 患者血清和唾液中循环 microRNA (miRNA) 的谱,将其表达值与临床和临床计量学参数相关联,并提出用于 FM 诊断的数学模型。我们的研究纳入了 14 名 FM 患者和性别及年龄匹配的对照组。通过 qPCR 评估了一组 179 个 miRNA 的表达。为了获得一个可以作为 FM 诊断辅助工具的数学线性模型,进行了统计分析。对 miRNA 靶标的生物信息学分析获得了与 FM 综合征相关的相关生物学过程,并详细描述了该疾病。与对照组相比,在 FM 患者中发现 6 个 miRNA 下调。其中 5 个 miRNA 已包含在一个线性预测模型中,该模型达到了非常高的灵敏度 (100%) 和高特异性 (83.3%)。此外,miR-320b 与 ZSDS 评分呈显著负相关 (r = -0.608,p = 0.036)。最后,发现与脑功能/发育和肌肉功能相关的几个生物学过程可能与 FM 综合征有关。我们的研究表明,循环 miRNA 谱的研究与统计和生物信息学分析相结合是更好地描述 FM 综合征并提出其诊断初步模型的有用工具。