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多发性硬化症的生物标志物

Biomarkers for multiple sclerosis.

作者信息

Villoslada Pablo

机构信息

Department of Neurosciences, Institute of Biomedical Research August Pi Sunyer, Hospital Clinic of Barcelona, Barcelona, Spain.

出版信息

Drug News Perspect. 2010 Nov;23(9):585-95. doi: 10.1358/dnp.2010.23.9.1472300.

DOI:10.1358/dnp.2010.23.9.1472300
PMID:21152453
Abstract

The pursuit of personalized medicine requires the development of biomarkers to predict disease course, monitor disease evolution, stratify patient subgroups by disease activity and to predict and monitor response to therapies. Multiple sclerosis (MS) is a common neurological disease in young adults with an unpredictable course that may be associated with significant disability, diminishing the patient's quality of life. Currently, disease prognosis is based on clinical information (relapse rate and disability scales) and diagnostic tests (brain MRI or the presence of oligoclonal bands in the cerebrospinal fluid). However, the ability of neurologists to make an accurate prognosis is very limited based on such information, a situation perceived by patients as one of their biggest concerns. Although many recent studies have identified different molecules and imaging techniques associated with the course of MS, in most cases the diagnostic accuracy of such technologies has not been properly assessed. This shortcoming is partly due to the failure to validate such biomarkers, which impedes their application in clinical practice. However, the recent validation of anti-aquaporin-4 antibodies for Devic's disease and the development of optic coherent tomography for MS, are examples of the benefits that the development of MS biomarkers can offer. Indeed, it may currently be necessary to redress the bias in research towards clinical validation rather than discovery in order to promote translational research and improve patient's quality of life.

摘要

对个性化医疗的追求需要开发生物标志物,以预测疾病进程、监测疾病演变、根据疾病活动对患者亚组进行分层,以及预测和监测对治疗的反应。多发性硬化症(MS)是年轻人中常见的神经系统疾病,其病程不可预测,可能导致严重残疾,降低患者的生活质量。目前,疾病预后基于临床信息(复发率和残疾量表)和诊断测试(脑部磁共振成像或脑脊液中寡克隆带的存在)。然而,基于这些信息,神经科医生做出准确预后的能力非常有限,患者将这种情况视为他们最大的担忧之一。尽管最近许多研究已经确定了与MS病程相关的不同分子和成像技术,但在大多数情况下,这些技术的诊断准确性尚未得到适当评估。这一缺陷部分归因于未能验证此类生物标志物,这阻碍了它们在临床实践中的应用。然而,抗水通道蛋白4抗体用于视神经脊髓炎的近期验证以及用于MS的光学相干断层扫描技术的发展,都是MS生物标志物开发所能带来益处的例证。的确,为了促进转化研究并改善患者生活质量,目前可能有必要纠正研究中偏向临床验证而非发现的偏差。

相似文献

1
Biomarkers for multiple sclerosis.多发性硬化症的生物标志物
Drug News Perspect. 2010 Nov;23(9):585-95. doi: 10.1358/dnp.2010.23.9.1472300.
2
Data integration and systems biology approaches for biomarker discovery: challenges and opportunities for multiple sclerosis.数据集成和系统生物学方法在生物标志物发现中的应用:多发性硬化症的挑战与机遇。
J Neuroimmunol. 2012 Jul 15;248(1-2):58-65. doi: 10.1016/j.jneuroim.2012.01.001. Epub 2012 Jan 24.
3
Integrating the tools for an individualized prognosis in multiple sclerosis.整合多发性硬化症个体化预后的工具。
J Neurol Sci. 2013 Aug 15;331(1-2):10-3. doi: 10.1016/j.jns.2013.04.021. Epub 2013 May 19.
4
Prognostic factors in multiple sclerosis.多发性硬化症的预后因素。
Int Rev Neurobiol. 2007;79:423-47. doi: 10.1016/S0074-7742(07)79019-0.
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[Biomarkers in multiple sclerosis].
Rev Neurol. 2013 Apr 1;56(7):375-90.
6
Specificity and correlation with disease activity of cerebrospinal fluid osteopontin levels in patients with multiple sclerosis.多发性硬化症患者脑脊液骨桥蛋白水平的特异性及其与疾病活动的相关性
Arch Neurol. 2008 Feb;65(2):232-5. doi: 10.1001/archneurol.2007.33.
7
Clinical characteristics, course and prognosis of relapsing Devic's Neuromyelitis Optica.复发性视神经脊髓炎的临床特征、病程及预后
J Neurol. 2004 Jan;251(1):47-52. doi: 10.1007/s00415-004-0271-0.
8
Diagnostic accuracy of retinal abnormalities in predicting disease activity in MS.视网膜异常在预测多发性硬化症疾病活动方面的诊断准确性。
Neurology. 2007 May 1;68(18):1488-94. doi: 10.1212/01.wnl.0000260612.51849.ed.
9
Imaging biomarkers in multiple sclerosis.多发性硬化症的影像学标志物。
J Magn Reson Imaging. 2010 Apr;31(4):770-88. doi: 10.1002/jmri.22102.
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Biomarkers of disease activity in multiple sclerosis.多发性硬化症的疾病活动生物标志物。
J Neurol Sci. 2011 Jun 15;305(1-2):1-10. doi: 10.1016/j.jns.2011.03.026. Epub 2011 Apr 3.

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Neurol Neuroimmunol Neuroinflamm. 2017 Jan 27;4(2):e321. doi: 10.1212/NXI.0000000000000321. eCollection 2017 Mar.
2
A novel data mining system points out hidden relationships between immunological markers in multiple sclerosis.一种新的数据挖掘系统指出多发性硬化症中免疫标志物之间隐藏的关系。
Immun Ageing. 2013 Jan 10;10(1):1. doi: 10.1186/1742-4933-10-1.