Towards personalized management of myasthenia gravis phenotypes: From the role of multi-omics to the emerging biomarkers and therapeutic targets

IF 9.2 1区 医学 Q1 IMMUNOLOGY
Carmela Rita Balistreri , Claudia Vinciguerra , Daniele Magro , Vincenzo Di Stefano , Roberto Monastero
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Abstract

Predicting the onset, progression, and outcome of rare and chronic neurological diseases, i.e. neuromuscular diseases, is an important goal for both clinicians and researchers and should guide clinical decision-making and personalized treatment plans. A prime example is myasthenia gravis (MG), an antibody-mediated disease that affects multiple components of the postsynaptic membrane, impairing neuromuscular transmission and producing fatigable muscle weakness. MG is characterized by several clinical phenotypes, defined by a broad spectrum of factors, which have contributed to the current lack of consensus on the optimal management and treatments of this disease and its related phenotypes (subtypes). This represents a crucial challenge in MG and encourages a revolutionary change in diagnostic, prognostic and therapeutic guidelines. Emerging factors, such as demographic, clinical and pathophysiological factors, must also be considered. Consequently, the different MG phenotypes are characterized by precise biological signatures, which could represent appropriate biomarkers and targets. Here we describe and discuss these new concepts, highlighting that, thanks to multi-omics technologies, the identification of emerging diagnostic/prognostic biomarkers, such as miRNAs, and the subsequent development of new diagnostic/therapeutic algorithms could be facilitated. The latter, in turn, could facilitate the management of different MG phenotypes also in a personalized manner. Limitations and advantages are also reported.
实现重症肌无力表型的个性化管理:从多组学的作用到新兴的生物标记物和治疗靶点
预测罕见的慢性神经系统疾病(即神经肌肉疾病)的发病、进展和预后是临床医生和研究人员的重要目标,并应为临床决策和个性化治疗方案提供指导。一个典型的例子是重症肌无力(MG),这是一种抗体介导的疾病,会影响突触后膜的多种成分,损害神经肌肉传导并产生疲劳性肌无力。重症肌无力有多种临床表型,这些临床表型由多种因素决定,导致目前对这种疾病及其相关表型(亚型)的最佳管理和治疗方法缺乏共识。这是 MG 面临的一项重大挑战,也促使诊断、预后和治疗指南发生革命性的变化。人口、临床和病理生理学因素等新出现的因素也必须考虑在内。因此,不同的 MG 表型具有精确的生物学特征,这些特征可能代表适当的生物标记物和靶点。在此,我们将对这些新概念进行描述和讨论,并强调由于采用了多组学技术,可促进对新出现的诊断/预后生物标志物(如 miRNAs)的鉴定以及随后新诊断/治疗算法的开发。反过来,后者也有助于以个性化的方式管理不同的 MG 表型。此外,还报告了该研究的局限性和优势。
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来源期刊
Autoimmunity reviews
Autoimmunity reviews 医学-免疫学
CiteScore
24.70
自引率
4.40%
发文量
164
审稿时长
21 days
期刊介绍: Autoimmunity Reviews is a publication that features up-to-date, structured reviews on various topics in the field of autoimmunity. These reviews are written by renowned experts and include demonstrative illustrations and tables. Each article will have a clear "take-home" message for readers. The selection of articles is primarily done by the Editors-in-Chief, based on recommendations from the international Editorial Board. The topics covered in the articles span all areas of autoimmunology, aiming to bridge the gap between basic and clinical sciences. In terms of content, the contributions in basic sciences delve into the pathophysiology and mechanisms of autoimmune disorders, as well as genomics and proteomics. On the other hand, clinical contributions focus on diseases related to autoimmunity, novel therapies, and clinical associations. Autoimmunity Reviews is internationally recognized, and its articles are indexed and abstracted in prestigious databases such as PubMed/Medline, Science Citation Index Expanded, Biosciences Information Services, and Chemical Abstracts.
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