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Network Analysis of the CSF Proteome Characterizes Convergent Pathways of Cellular Dysfunction in ALS

BACKGROUND: Amyotrophic lateral sclerosis is a clinical syndrome with complex biological determinants, but which in most cases is characterized by TDP-43 pathology. The identification in CSF of a protein signature of TDP-43 network dysfunction would have the potential to inform the identification of...

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Autores principales: Thompson, Alexander G., Gray, Elizabeth, Charles, Philip D., Hu, Michele T. M., Talbot, Kevin, Fischer, Roman, Kessler, Benedikt M., Turner, Martin R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010303/
https://www.ncbi.nlm.nih.gov/pubmed/33815045
http://dx.doi.org/10.3389/fnins.2021.642324
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author Thompson, Alexander G.
Gray, Elizabeth
Charles, Philip D.
Hu, Michele T. M.
Talbot, Kevin
Fischer, Roman
Kessler, Benedikt M.
Turner, Martin R.
author_facet Thompson, Alexander G.
Gray, Elizabeth
Charles, Philip D.
Hu, Michele T. M.
Talbot, Kevin
Fischer, Roman
Kessler, Benedikt M.
Turner, Martin R.
author_sort Thompson, Alexander G.
collection PubMed
description BACKGROUND: Amyotrophic lateral sclerosis is a clinical syndrome with complex biological determinants, but which in most cases is characterized by TDP-43 pathology. The identification in CSF of a protein signature of TDP-43 network dysfunction would have the potential to inform the identification of new biomarkers and therapeutic targets. METHODS: We compared CSF proteomic data from patients with ALS (n = 41), Parkinson’s disease (n = 19) and healthy control participants (n = 20). Weighted correlation network analysis was used to identify modules within the CSF protein network and combined with gene ontology enrichment analysis to functionally annotate module proteins. Analysis of module eigenproteins and differential correlation analysis of the CSF protein network was used to compare ALS and Parkinson’s disease protein co-correlation with healthy controls. In order to monitor temporal changes in the CSF proteome, we performed longitudinal analysis of the CSF proteome in a subset of ALS patients. RESULTS: Weighted correlation network analysis identified 10 modules, including those enriched for terms involved in gene expression including nucleic acid binding, RNA metabolism and translation; humoral immune system function, including complement pathways; membrane proteins, axonal outgrowth and adherence; and glutamatergic synapses. Immune system module eigenproteins were increased in ALS, whilst axonal module eigenproteins were decreased in ALS. The 19 altered protein correlations in ALS were enriched for gene expression (OR 3.05, p = 0.017) and membrane protein modules (OR 17.48, p = 0.011), including intramodular hub proteins previously identified as TDP-43 interactors. Proteins decreasing over longitudinal analysis ALS were enriched in glutamatergic synapse and axonal outgrowth modules. Protein correlation network disruptions in Parkinson’s disease showed no module enrichment. CONCLUSIONS: Alterations in the co-correlation network in CSF samples identified a set of pathways known to be associated with TDP-43 dysfunction in the pathogenesis of ALS, with important implications for therapeutic targeting and biomarker development.
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spelling pubmed-80103032021-04-01 Network Analysis of the CSF Proteome Characterizes Convergent Pathways of Cellular Dysfunction in ALS Thompson, Alexander G. Gray, Elizabeth Charles, Philip D. Hu, Michele T. M. Talbot, Kevin Fischer, Roman Kessler, Benedikt M. Turner, Martin R. Front Neurosci Neuroscience BACKGROUND: Amyotrophic lateral sclerosis is a clinical syndrome with complex biological determinants, but which in most cases is characterized by TDP-43 pathology. The identification in CSF of a protein signature of TDP-43 network dysfunction would have the potential to inform the identification of new biomarkers and therapeutic targets. METHODS: We compared CSF proteomic data from patients with ALS (n = 41), Parkinson’s disease (n = 19) and healthy control participants (n = 20). Weighted correlation network analysis was used to identify modules within the CSF protein network and combined with gene ontology enrichment analysis to functionally annotate module proteins. Analysis of module eigenproteins and differential correlation analysis of the CSF protein network was used to compare ALS and Parkinson’s disease protein co-correlation with healthy controls. In order to monitor temporal changes in the CSF proteome, we performed longitudinal analysis of the CSF proteome in a subset of ALS patients. RESULTS: Weighted correlation network analysis identified 10 modules, including those enriched for terms involved in gene expression including nucleic acid binding, RNA metabolism and translation; humoral immune system function, including complement pathways; membrane proteins, axonal outgrowth and adherence; and glutamatergic synapses. Immune system module eigenproteins were increased in ALS, whilst axonal module eigenproteins were decreased in ALS. The 19 altered protein correlations in ALS were enriched for gene expression (OR 3.05, p = 0.017) and membrane protein modules (OR 17.48, p = 0.011), including intramodular hub proteins previously identified as TDP-43 interactors. Proteins decreasing over longitudinal analysis ALS were enriched in glutamatergic synapse and axonal outgrowth modules. Protein correlation network disruptions in Parkinson’s disease showed no module enrichment. CONCLUSIONS: Alterations in the co-correlation network in CSF samples identified a set of pathways known to be associated with TDP-43 dysfunction in the pathogenesis of ALS, with important implications for therapeutic targeting and biomarker development. Frontiers Media S.A. 2021-03-17 /pmc/articles/PMC8010303/ /pubmed/33815045 http://dx.doi.org/10.3389/fnins.2021.642324 Text en Copyright © 2021 Thompson, Gray, Charles, Hu, Talbot, Fischer, Kessler and Turner. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Thompson, Alexander G.
Gray, Elizabeth
Charles, Philip D.
Hu, Michele T. M.
Talbot, Kevin
Fischer, Roman
Kessler, Benedikt M.
Turner, Martin R.
Network Analysis of the CSF Proteome Characterizes Convergent Pathways of Cellular Dysfunction in ALS
title Network Analysis of the CSF Proteome Characterizes Convergent Pathways of Cellular Dysfunction in ALS
title_full Network Analysis of the CSF Proteome Characterizes Convergent Pathways of Cellular Dysfunction in ALS
title_fullStr Network Analysis of the CSF Proteome Characterizes Convergent Pathways of Cellular Dysfunction in ALS
title_full_unstemmed Network Analysis of the CSF Proteome Characterizes Convergent Pathways of Cellular Dysfunction in ALS
title_short Network Analysis of the CSF Proteome Characterizes Convergent Pathways of Cellular Dysfunction in ALS
title_sort network analysis of the csf proteome characterizes convergent pathways of cellular dysfunction in als
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010303/
https://www.ncbi.nlm.nih.gov/pubmed/33815045
http://dx.doi.org/10.3389/fnins.2021.642324
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