Comprehensive Proteomic Analysis of Dysferlinopathy Unveiling Molecular Mechanisms and Biomarkers Linked to Pathological Progression

IF 4.8 1区 医学 Q1 NEUROSCIENCES CNS Neuroscience & Therapeutics Pub Date : 2024-09-30 DOI:10.1111/cns.70065
Di Wang, Xin-yi Liu, Qi-Fang He, Fu-ze Zheng, Long Chen, Ying Zheng, Ming-hui Zeng, Yu-hua Lin, Xin Lin, Hai-zhu Chen, Min-ting Lin, Ning Wang, Zhi-qiang Wang, Feng Lin
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Abstract

Aims

Previous proteomics studies in dysferlinopathy muscle have been limited in scope, often utilizing 2D-electrophoresis and yielding only a small number of differential expression calls. To address this gap, this study aimed to employ high-resolution proteomics to explore the proteomic landscapes of dysferlinopathy and analyze the correlation between muscle pathological changes and alterations in protein expression in muscle biopsies.

Methods

We conducted a comprehensive approach to investigate the proteomic profile and disease-associated changes in the muscle tissue proteome from 15 patients with dysferlinopathy, exhibiting varying degrees of dystrophic pathology, alongside age-matched controls. Our methodology encompasses tandem mass tag (TMT)-labeled liquid chromatography-mass spectrometry (LC–MS/MS)-based proteomics, protein–protein interaction (PPI) network analysis, weighted gene co-expression network analysis, and differential expression analysis. Subsequently, we examined the correlation between the expression of key proteins and the clinical characteristics of the patients to identify pathogenic targets associated with DYSF mutations in dysferlinopathy.

Results

A total of 1600 differentially expressed proteins were identified, with 1321 showing high expression levels and 279 expressed at lower levels. Our investigation yields a molecular profile delineating the altered protein networks in dysferlinopathy-afflicted skeletal muscle, uncovering dysregulation across numerous cellular pathways and molecular processes, including mRNA metabolic processes, regulated exocytosis, immune response, muscle system processes, energy metabolic processes, and calcium transmembrane transport. Moreover, we observe significant associations between the protein expression of ANXA1, ANXA2, ANXA4, ANXA5, LMNA, PYGM, and the extent of histopathologic changes in muscle biopsies from patients with dysferlinopathy, validated through immunoblotting and immunofluorescence assays.

Conclusions

Through the aggregation of expression data from dysferlinopathy-impacted muscles exhibiting a range of pathological alterations, we identified multiple key proteins associated with the dystrophic pathology of patients with dysferlinopathy. These findings provide novel insights into the pathogenesis of dysferlinopathy and propose promising targets for future therapeutic endeavors.

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干扰素病的全面蛋白质组分析揭示了与病理进展相关的分子机制和生物标志物。
目的:以往对铁蛋白血症肌肉进行的蛋白质组学研究范围有限,通常采用二维电泳,只能获得少量差异表达调用。为了填补这一空白,本研究旨在利用高分辨率蛋白质组学探索铁蛋白异常病变的蛋白质组学图谱,并分析肌肉活检组织中肌肉病理变化与蛋白质表达改变之间的相关性:我们采用一种综合方法研究了15名表现出不同程度肌营养不良病理变化的铁蛋白障碍病患者以及年龄匹配对照组的肌肉组织蛋白质组的蛋白质组图谱和与疾病相关的变化。我们的研究方法包括基于串联质量标签(TMT)标记的液相色谱-质谱(LC-MS/MS)蛋白质组学、蛋白质-蛋白质相互作用(PPI)网络分析、加权基因共表达网络分析和差异表达分析。随后,我们研究了关键蛋白的表达与患者临床特征之间的相关性,以确定与DYSF突变相关的致病靶点:结果:共鉴定出1600种不同表达的蛋白质,其中1321种表达水平较高,279种表达水平较低。我们的研究得出了一个分子图谱,勾勒出了受铁蛋白血症影响的骨骼肌中发生改变的蛋白质网络,发现了许多细胞通路和分子过程的失调,包括mRNA代谢过程、受调控的外泌、免疫反应、肌肉系统过程、能量代谢过程和钙跨膜转运。此外,我们还观察到 ANXA1、ANXA2、ANXA4、ANXA5、LMNA、PYGM 的蛋白表达与干扰素病变患者肌肉活检组织病理学变化的程度之间存在明显关联,并通过免疫印迹和免疫荧光检测进行了验证:通过汇总受铁蛋白异常病影响的肌肉中表现出的一系列病理改变的表达数据,我们确定了与铁蛋白异常病患者肌营养不良病理相关的多个关键蛋白。这些发现为研究铁蛋白缺乏症的发病机制提供了新的视角,并为未来的治疗工作提出了有前景的目标。
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来源期刊
CNS Neuroscience & Therapeutics
CNS Neuroscience & Therapeutics 医学-神经科学
CiteScore
7.30
自引率
12.70%
发文量
240
审稿时长
2 months
期刊介绍: CNS Neuroscience & Therapeutics provides a medium for rapid publication of original clinical, experimental, and translational research papers, timely reviews and reports of novel findings of therapeutic relevance to the central nervous system, as well as papers related to clinical pharmacology, drug development and novel methodologies for drug evaluation. The journal focuses on neurological and psychiatric diseases such as stroke, Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, epilepsy, and drug abuse.
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