ReviewBrain sciences2024
A Systematic Review of Extracellular Matrix-Related Alterations in Parkinson's Disease.
Review in Brain sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Extracellular matrix remodeling therapeutic strategies to tackle central nervous system diseases.Neural regeneration research · 2026Article
- The potential and therapeutic advances of the integrin family in neurological disorders.Neural regeneration research · 2026Article
- Heparan sulfate and glycomimetics: Advances in synthesis and biological applications for post-stroke neurorepair.Neuroprotection (Chichester, England) · 2026Review
- Early Prediction of Parkinson's Disease Progression by Integrating Research Cohort and Real-World Data Using Knowledge-Anchored Graph Learning.medRxiv : the preprint server for health sciences · 2026Article
- Dysregulation of the Extracellular Matrix in the Synaptic Pathology of Parkinson's Disease: Molecular Mechanisms and Novel Therapeutic Approaches.Life (Basel, Switzerland) · 2026Review
- Article
- Neuronal plasticity and its role in Alzheimer's disease and Parkinson's disease.Neural regeneration research · 2026Article
- Stable Dopamine-Signaling mRNA Co-Expression in the Substantia Nigra Is Deregulated in Pathological Conditions, but Not in Dopamine Transporter Knockout Rats.Biomolecules · 2025Article
- Role of Long Non-Coding RNA X-Inactive-Specific Transcript (Non-coding RNA · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The role of the extracellular matrix (ECM) in Parkinson's disease (PD) is not well understood, even though it is critical for neuronal structure and signaling. This systematic review identified the top deregulated ECM-related pathways in studies that used gene set enrichment analyses (GSEA) to document transcriptomic, proteomic, or genomic alterations in PD. PubMed and Google scholar were searched for transcriptomics, proteomics, or genomics studies that employed GSEA on data from PD tissues or cells and reported ECM-related pathways among the top-10 most enriched versus controls. Twenty-seven studies were included, two of which used multiple omics analyses. Transcriptomics and proteomics studies were conducted on a variety of tissue and cell types. Of the 17 transcriptomics studies (16 data sets), 13 identified one or more adhesion pathways in the top-10 deregulated gene sets or pathways, primarily related to cell adhesion and focal adhesion. Among the 8 proteomics studies, 5 identified altered overarching ECM gene sets or pathways among the top 10. Among the 4 genomics studies, 3 identified focal adhesion pathways among the top 10. The findings summarized here suggest that ECM organization/structure and cell adhesion (particularly focal adhesion) are altered in PD and should be the focus of future studies.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.