Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI 49503, USA.
J Parkinsons Dis. 2012;2(4):321-31. doi: 10.3233/JPD-012144.
The current "gold-standard" for Parkinson's disease (PD) diagnosis is based primarily on subjective clinical rating scales related with motor features. Molecular biomarkers that are objective and quantifiable remain attractive as clinical tools to detect PD prior to its motor onsets.
Here, we aimed to identify, develop, and validate plasma-based circulating microRNA (miRNAs) as biomarkers for PD.
Global miRNA expressions were acquired from a discovery set of 32 PD/32 controls using microarrays. k-Top Scoring Pairs (k-TSP) algorithm and significance analysis of microarrays (SAM) were applied to obtain comprehensive panels of PD-predictive biomarkers. TaqMan miRNA-specific real-time PCR assays were performed to validate the microarray data and to evaluate the biomarker performance using a new replication set of 42 PD/30 controls. Data was analyzed in a paired PD-control fashion. The validation set was composed of 30 PD, 5 progressive supranuclear palsy, and 4 multiple system atrophy samples from a new clinical site.
We identified 9 pairs of PD-predictive classifiers using k-TSP analysis and 13 most differentially-expressed miRNAs by SAM. A combination of both data sets produced a panel of PD-predictive biomarkers: k-TSP1 (miR-1826/miR-450b-3p), miR-626, and miR-505, and achieved the highest predictive power of 91% sensitivity, 100% specificity, 100% positive predicted value, and 88% negative predicted value in the replication set. However, low predictive values were shown in the validation set.
This proof-of-concept study demonstrates the feasibility of using plasma-based circulating miRNAs as biomarkers for neurodegenerative disorders such as PD and shows the challenges of molecular biomarker research using samples from multiple clinical sites.
目前帕金森病（PD）的“金标准”诊断主要基于与运动特征相关的主观临床评分量表。客观且可量化的分子生物标志物仍然是一种有吸引力的临床工具，可以在运动发作之前检测 PD。
本研究旨在确定、开发和验证基于血浆的循环 microRNA（miRNA）作为 PD 的生物标志物。
使用微阵列获取 32 例 PD/32 例对照的全基因组 miRNA 表达谱。采用 k-最佳评分对（k-Top Scoring Pairs，k-TSP）算法和显著微阵列分析（Significance Analysis of Microarrays，SAM）来获得全面的 PD 预测生物标志物谱。采用 TaqMan miRNA 特异性实时 PCR 检测来验证微阵列数据，并使用新的 42 例 PD/30 例对照的复制集来评估生物标志物性能。以配对 PD-对照的方式分析数据。验证集由来自新临床中心的 30 例 PD、5 例进行性核上性麻痹和 4 例多系统萎缩样本组成。
我们使用 k-TSP 分析鉴定了 9 对 PD 预测分类器，通过 SAM 分析鉴定了 13 个差异表达最显著的 miRNA。这两组数据的组合产生了一组 PD 预测生物标志物：k-TSP1（miR-1826/miR-450b-3p）、miR-626 和 miR-505，在复制集中达到了 91%的最高敏感性、100%的特异性、100%的阳性预测值和 88%的阴性预测值。然而，在验证集中，预测值较低。
本概念验证研究表明，使用基于血浆的循环 miRNA 作为 PD 等神经退行性疾病的生物标志物是可行的，并显示了使用来自多个临床中心的样本进行分子生物标志物研究的挑战。
