Blood-borne small non-coding (sncRNAs) are among the prominent candidates for blood-based diagnostic tests. Often, high-throughput approaches are applied to discover biomarker signatures. These have to be validated in larger cohorts and evaluated by adequate statistical learning approaches. Previously, we published high-throughput sequencing based microRNA (miRNA) signatures in Alzheimer’s disease (AD) patients in the United States (US) and Germany. Here, we determined abundance levels of 21 known circulating miRNAs in 465 individuals encompassing AD patients and controls by RT-qPCR. We computed models to assess the relation between miRNA expression and phenotypes, gender, age, or disease severity (Mini-Mental State Examination; MMSE). Of the 21 miRNAs, expression levels of 20 miRNAs were consistently de-regulated in the US and German cohorts. 18 miRNAs were significantly correlated with neurodegeneration (Benjamini-Hochberg adjusted P?<?0.05) with highest significance for miR-532-5p (Benjamini-Hochberg adjusted P?=?4.8?×?10?30). Machine learning models reached an area under the curve (AUC) value of 87.6% in differentiating AD patients from controls. Further, ten miRNAs were significantly correlated with MMSE, in particular miR-26a/26b-5p (adjusted P?=?0.0002). Interestingly, the miRNAs with lower abundance in AD were enriched in monocytes and T-helper cells, while those up-regulated in AD were enriched in serum, exosomes, cytotoxic t-cells, and B-cells. Our study represents the next important step in translational research for a miRNA-based AD test.
血源性小非编码RNA（sncRNA）是用于抽血检验的主要候选检测标志物。通常情况下，疾病生物标志物的发现需要借助高通量测序方法，此外，这些标志物还需经过大群体样本的验证以及统计学习的评估。此前，该团队发表了一篇关于美国和德国阿尔兹海默症（AD）患者的小RNA表达量测序图谱的研究。在本文研究中，该团队通过RT-qPCR测定了共计465名AD以及对照组人员样本中的21个小RNA的表达丰度水平。该团队通过统计模型来评估小RNA表达量和表型（性别、年龄、患病程度）之间的关系。针对美国和德国患者及对照组样本的研究显示，在这21个小RNA中，20个小RNA在患者中表现出“去调节”的状态。18个小RNA与神经退行性疾病显著相关，其中显著性最高的是miR-532-5p。该团队通过机器学习方法对AD患者和对照组进行鉴别，AUC（分类效果评判指标）达到87.6%。此外，10个小RNA与患者患病程度显著相关。有趣的是，在AD患者中表达量下调的小RNA富集在单核细胞和T-辅助细胞，而表达量上调的小RNA则富集于血清、外泌体、细胞毒性T细胞和B细胞。本研究为基于小RNA的AD检测提供了更多借鉴和支持。





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