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运动神经元病中的生物标志物:最新综述

Biomarkers in Motor Neuron Disease: A State of the Art Review.

作者信息

Verber Nick S, Shepheard Stephanie R, Sassani Matilde, McDonough Harry E, Moore Sophie A, Alix James J P, Wilkinson Iain D, Jenkins Tom M, Shaw Pamela J

机构信息

Department of Neuroscience, Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, United Kingdom.

出版信息

Front Neurol. 2019 Apr 3;10:291. doi: 10.3389/fneur.2019.00291. eCollection 2019.

Abstract

Motor neuron disease can be viewed as an umbrella term describing a heterogeneous group of conditions, all of which are relentlessly progressive and ultimately fatal. The average life expectancy is 2 years, but with a broad range of months to decades. Biomarker research deepens disease understanding through exploration of pathophysiological mechanisms which, in turn, highlights targets for novel therapies. It also allows differentiation of the disease population into sub-groups, which serves two general purposes: (a) provides clinicians with information to better guide their patients in terms of disease progression, and (b) guides clinical trial design so that an intervention may be shown to be effective if population variation is controlled for. Biomarkers also have the potential to provide monitoring during clinical trials to ensure target engagement. This review highlights biomarkers that have emerged from the fields of systemic measurements including biochemistry (blood, cerebrospinal fluid, and urine analysis); imaging and electrophysiology, and gives examples of how a combinatorial approach may yield the best results. We emphasize the importance of systematic sample collection and analysis, and the need to correlate biomarker findings with detailed phenotype and genotype data.

摘要

运动神经元病可被视为一个涵盖多种不同病症的统称,所有这些病症都呈持续进展且最终致命。平均预期寿命为2年,但范围从数月到数十年不等。生物标志物研究通过探索病理生理机制加深了对疾病的理解,这反过来又突出了新型疗法的靶点。它还能将疾病人群区分为不同亚组,这有两个主要目的:(a)为临床医生提供信息,以便在疾病进展方面更好地指导患者;(b)指导临床试验设计,以便在控制人群差异的情况下,证明某种干预措施是有效的。生物标志物还有望在临床试验期间提供监测,以确保靶点被作用。本综述重点介绍了来自包括生物化学(血液、脑脊液和尿液分析)在内的全身测量领域、成像和电生理学领域中出现的生物标志物,并举例说明了组合方法如何可能产生最佳结果。我们强调系统样本采集和分析的重要性,以及将生物标志物研究结果与详细的表型和基因型数据相关联的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c79/6456669/1eefc9d40625/fneur-10-00291-g0001.jpg

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