Detection of multiplex exosomal miRNAs for clinically accurate diagnosis of Alzheimer’s disease using label-free plasmonic biosensor based on DNA-Assembled advanced plasmonic architecture

小RNA 生物传感器 等离子体子 多路复用 纳米技术 计算生物学 临床诊断 表面等离子共振 痴呆 材料科学 纳米颗粒 微泡 外体 生物 疾病 医学 生物信息学 病理 基因 生物化学 光电子学 临床心理学
作者
Sojin Song,Jong Uk Lee,Myeong Jin Jeon,Soohyun Kim,Sang Jun Sim
出处
期刊:Biosensors and Bioelectronics [Elsevier BV]
卷期号:199: 113864-113864 被引量:66
标识
DOI:10.1016/j.bios.2021.113864
摘要

Alzheimer's disease (AD), the most common neurologic disorder, is characterized by progressive cognitive impairment. However, the low clinical significance of the currently used core AD biomarkers amyloid-beta and tau proteins remains a challenge. Recently, exosomes, found in human biological fluids, are gaining increasing attention because of their clinical significance in diagnosing of various diseases. In particular, blood-derived exosomal miRNAs are not only stable but also provide information regarding the different characteristics according to AD progression. However, quantitative and qualitative detection is difficult due to their characteristics, such as small size, low abundance, and high homology. Here, we present a DNA-assembled advanced plasmonic architecture (DAPA)-based plasmonic biosensor to accurately detect exosomal miRNAs in human serum. The designed nanoarchitecture possesses two narrow nanogaps that induce plasmon coupling; this significantly enhances its optical energy density, resulting in a 1.66-fold higher refractive-index (RI) sensitivity than nanorods at localized surface plasmon resonance (LSPR). Thus, the proposed biosensor is ultrasensitive and capable of selective single-nucleotide detection of exosomal miRNAs at the attomolar level. Furthermore, it identified AD patients from healthy controls by measuring the levels of exosomal miRNA-125b, miRNA-15a, and miRNA-361 in clinical serum samples. In particular, the combination of exosomal miRNA-125b and miRNA-361 showed the best diagnostic performance with a sensitivity of 91.67%, selectivity of 95.00%, and accuracy of 99.52%. These results demonstrate that our sensor can be clinically applied for AD diagnosis and has great potential to revolutionize the field of dementia research and treatment in the future.
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