Evidence map›Paper›PMID 39350328›Full record

ArticleCNS neuroscience & therapeutics2024

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

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 and 4 more

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Article in CNS neuroscience & therapeutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Di WangDepartment of Molecular Pathology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.ORCID 0000-0003-2059-7054
Xin-Yi LiuDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Qi-Fang HeDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Fu-Ze ZhengDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Long ChenDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Ying ZhengDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Ming-Hui ZengDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Yu-Hua LinDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Xin LinDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Hai-Zhu ChenDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Min-Ting LinDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Ning WangDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Zhi-Qiang WangDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.
Feng LinDepartment of Neurology and Institute of Neurology of First Affiliated Hospital, Institute of Neuroscience, and Fujian Key Laboratory of Molecular Neurology, Fujian Medical University, Fuzhou, China.ORCID 0000-0002-6211-4017

Funding

National Natural Science Foundation of China 81701242National Natural Science Foundation of China 82101471Natural Science Foundation of Fujian Province 2023J01620The Joint Funds for the Innovation of Science and Technology 2020Y9122
6 · The paper itself

Abstract

aimsPrevious 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.

methodsWe 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.

resultsA 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.

conclusionsThrough 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.

Indexed as

BiomarkersDisease ProgressionMuscle, SkeletalMuscular Dystrophies, Limb-GirdleProteomicsAdolescentAdultChildChild, PreschoolDysferlinFemaleHumansMaleMiddle AgedMuscle ProteinsProtein Interaction MapsBiomarkersDysferlinDYSF protein, humanMuscle Proteinsannexinsdysferlinopathyinflammationpathological progressionpotential biomarkersproteomicstherapeutic targets

Identifiers

PMID39350328
PMCPMC11442333

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