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首页 » 帕金森病 » J Parkinsons Dis.:科学家发现早期诊断帕金森氏病的血液生物标记物

J Parkinsons Dis.:科学家发现早期诊断帕金森氏病的血液生物标记物

来源:生物谷 2013-01-22 14:36

2013年1月21日讯 /生物谷BIOON/--帕金森氏病(PD)在一种渐进性疾病。现今常规诊断方式是出现运动障碍。然而需要开发更客观用于检测的生物标记物,在运动障碍之前就能诊断PD,进行早期诊断。研究人员发现并测试了血液中的小RNA(microRNA)可作为PD的生物标记物。相关报道发表在近期的Journal of Parkinson's Disease上。

全球有五百万PD患者,预计2030年这个数字将翻倍。PD最明显的症状是运动紊乱,如无意识震颤和肌肉僵直。进一步是认知行为出现问题并伴随外周神经系统疾病如胃肠功能紊乱等。尽管药物levodopa能够缓解PD症状,但是现今没有好的治疗手段。PD发病阶段的诊断主要是基于运动紊乱的程度。但是一旦患者出现运动障碍,该患者60-70%多巴胺神经元已经死亡。

美国Van Andel研究所的Sok Kean Khoo研究员称,生物标记物应该有一下性质微创,价格便宜,可计量,可重复,特异并且敏感。如血浆等的体液是一种很好的提取合适生物标记物的来源。然而,基于体液的临床诊断PD的方法目前还没建立。

已知不同细胞和组织的小RNA在血液中都能被检测到。早期试验通过小RNA芯片技术发现健康脑组织的4%的小RNA在血液中都能检测到。于是科研人员提出假设PD相关的小RNA在血液中同样能够被检测到。

试验初期,研究人员从32位PD患者和32位正常人血浆中获取了所有的小RNA,确定了九对PD早期小RNA和13对PD患者和正常人表达差异最大的小RNA作为可能的生物标记物。接着研究人员采用实时定量PCR技术在新一组42位PD病人和30位正常人中检测这些生物标记物的有效性。

研究人员发现多种生物标记物结合的方法能够达到最大的预测效果。研究人员承认这些生物标记物仍然有一定的风险,由于一些并发症问题造成预测不准确。然而Khoo博士称该研究从概念上证明了基于血浆小RNA预测PD的可行性。该研究为PD的诊断,预后,治疗开启了一个新的方向,同时对其他神经退行性疾病也有一定的启示作用。(生物谷Bioon.com)

Plasma-Based Circulating MicroRNA Biomarkers for Parkinson's Disease

Sok Kean Khoo, David Petillo, Un Jung Kang, James H. Resau, Brian Berryhill , Jan Linder, Lars Forsgren, Leslie A. Neuman, Aik Choon Tan

Background: 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. Objective: Here, we aimed to identify, develop, and validate plasma-based circulating microRNA (miRNAs) as biomarkers for PD. Methods: 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. Results: 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. Conclusions: 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.

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