A 9-microRNA Signature in Serum Serves as a Noninvasive Biomarker in Early Diagnosis of Alzheimer’s Disease

生物标志物 小RNA 签名(拓扑) 医学 疾病 阿尔茨海默病 病理 基因 生物 遗传学 数学 几何学
作者
Rui Guo,Gang Fan,Jian Zhang,Chunxiao Wu,Yifeng Du,Hui Ye,Zhang Li,Lili Wang,Zhihui Zhang,Lu Zhang,Yueran Zhao,Zhiming Lu
出处
期刊:Journal of Alzheimer's Disease [IOS Press]
卷期号:60 (4): 1365-1377 被引量:102
标识
DOI:10.3233/jad-170343
摘要

Alzheimer's disease (AD) is the most common type of age-related neurodegenerative disorder; nevertheless, nowadays there are no reliable biomarkers or non-invasive techniques available for its early detection. Recent studies have indicated that the circulating level profiles of microRNAs (miRNAs) have the potential to be used as valuable biomarkers for diagnosis, staging, and progress monitoring of various diseases. Here we report a novel 9-miRNA signature (hsa-miR-26a-5p, hsa-miR-181c-3p, hsa-miR-126-5p, hsa-miR-22-3p, hsa-miR-148b-5p, hsa-miR-106b-3p, hsa-miR-6119-5p, hsa-miR-1246, and hsa-miR-660-5p) that can be utilized as biomarker for detecting AD. We respectively profiled the serum miRNAs from 19 AD patients and 9 healthy control (HC) participants using the Next-Generation Sequencing (NGS). The NGS results were validated by quantitative real-time polymerase chain reaction (qRT-PCR) on a larger cohort of 121 AD and 86 HC cases. All the patients were divided into three groups (mild, moderate, and severe AD) based on the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR). Our research indicates that abnormal expression of distinct serum miRNAs occurs at different stages of AD. The difference of the area under the receiver operator characteristics curve (AUC) between the AD and the HC is between 70% and 85%. Among the 9 miRNAs, hsa-miR-22-3p has the best sensitivity (81.8%) and specificity (70.9%). The miRNA-panel is more valuable for AD diagnosis. The data suggest that the differentially expressed serum miRNAs could be used as biomarkers to improve the diagnosis of AD, particularly at the early stage, and to classify its clinical stages.
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