Normalization strategies differently affect circulating miRNA profile associated with the training status
Normalization strategies differently affect circulating miRNA profile associated with the training status
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DOI：
10.1038/s41598-019-38505-x
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发表时间：
2019-02-07
影响因子：
4.6
通讯作者：
Lombardi, Giovanni
中科院分区：
文献类型：
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作者：
Faraldi, Martina;Gomarasca, Marta;Lombardi, Giovanni
微RNA是全身适应性反应的良好调节器，但由于缺乏标准化的分析前和分析后程序，它们作为生物标志物的使用受到限制。本工作旨在比较不同的RT-qPCR数据分析标准化方法，以确定最可靠和最具重复性的方法来分析久坐和高训练受试者的循环miRNA表达谱。由于已知身体活动状态会影响miRNA的表达，它们可能是动态平衡反应的有效生物标志物。从血浆中提取RNA后，用RT-qPCR对179个miRNAs进行检测，并根据内源miRNAs和外源寡核苷酸应用不同的归一化策略进行定量。HSA-miR-320d被发现是降低实验复制之间的技术变异性，从而突出队列间差异的最合适的参考miRNA。我们的数据显示，身体活动状态与特定的骨骼肌和骨骼相关循环miRNAs谱之间存在关联，揭示了已建立的表观遗传修饰影响这些组织的基线生理状态。由于不同的归一化策略导致不同的输出，为了避免对数据的误导解释，我们强调了在每个实验设置中准确选择最可靠的归一化方法的重要性。
MicroRNAs are fine regulators of the whole-body adaptive response but their use as biomarkers is limited by the lack of standardized pre-and post-analytical procedures. This work aimed to compare different normalization approaches for RT-qPCR data analyses, in order to identify the most reliable and reproducible method to analyze circulating miRNA expression profiles in sedentary and highly-trained subjects. As the physically active status is known to affect miRNA expression, they could be effective biomarkers of the homeostatic response. Following RNA extraction from plasma, a panel of 179 miRNAs was assayed by RT-qPCR and quantified by applying different normalization strategies based on endogenous miRNAs and exogenous oligonucleotides. hsa-miR-320d was found as the most appropriate reference miRNA in reducing the technical variability among the experimental replicates and, hence, in highlighting the inter-cohorts differences. Our data showed an association between the physically active status and specific skeletal muscle-and bone-associated circulating miRNAs profiles, revealing that established epigenetic modifications affect the baseline physiological status of these tissues. Since different normalization strategies led to different outputs, in order to avoid misleading interpretation of data, we remark the importance of the accurate choice of the most reliable normalization method in every experimental setting.