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肌萎缩侧索硬化症成纤维细胞的诊断基因表达特征。

A Diagnostic Gene-Expression Signature in Fibroblasts of Amyotrophic Lateral Sclerosis.

机构信息

Institute for Biomedical Research and Innovation, National Research Council (CNR-IRIB), 95126 Catania, Italy.

ALS Clinical Research Center and Neurochemistry Laboratory, BiND, University of Palermo, 90133 Palermo, Italy.

出版信息

Cells. 2023 Jul 18;12(14):1884. doi: 10.3390/cells12141884.

Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal, progressive neurodegenerative disease with limited treatment options. Diagnosis can be difficult due to the heterogeneity and non-specific nature of the initial symptoms, resulting in delays that compromise prompt access to effective therapeutic strategies. Transcriptome profiling of patient-derived peripheral cells represents a valuable benchmark in overcoming such challenges, providing the opportunity to identify molecular diagnostic signatures. In this study, we characterized transcriptome changes in skin fibroblasts of sporadic ALS patients (sALS) and controls and evaluated their utility as a molecular classifier for ALS diagnosis. Our analysis identified 277 differentially expressed transcripts predominantly involved in transcriptional regulation, synaptic transmission, and the inflammatory response. A support vector machine classifier based on this 277-gene signature was developed to discriminate patients with sALS from controls, showing significant predictive power in both the discovery dataset and in six independent publicly available gene expression datasets obtained from different sALS tissue/cell samples. Taken together, our findings support the utility of transcriptional signatures in peripheral cells as valuable biomarkers for the diagnosis of ALS.

摘要

肌萎缩侧索硬化症(ALS)是一种致命的、进行性的神经退行性疾病,治疗选择有限。由于初始症状的异质性和非特异性,诊断可能很困难,导致延误,从而影响及时采用有效的治疗策略。从患者来源的外周细胞进行转录组谱分析代表了克服这些挑战的一个有价值的基准,为识别分子诊断特征提供了机会。在这项研究中,我们描述了散发性 ALS 患者(sALS)和对照者皮肤成纤维细胞的转录组变化,并评估了它们作为 ALS 诊断的分子分类器的效用。我们的分析确定了 277 个差异表达的转录本,主要涉及转录调控、突触传递和炎症反应。基于该 277 个基因特征的支持向量机分类器被开发出来,以区分 sALS 患者和对照者,在发现数据集和六个独立的、来自不同 sALS 组织/细胞样本的公开可用基因表达数据集上均显示出显著的预测能力。总之,我们的研究结果支持在外周细胞中转录组特征作为 ALS 诊断有价值的生物标志物的效用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bec9/10378077/c9129a55e120/cells-12-01884-g001.jpg

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