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Integrated systems analysis reveals conserved gene networks underlying response to spinal cord injury
Spinal cord injury (SCI) is a devastating neurological condition for which there are currently no effective treatment options to restore function. A major obstacle to the development of new therapies is our fragmentary understanding of the coordinated pathophysiological processes triggered by damage...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6173583/ https://www.ncbi.nlm.nih.gov/pubmed/30277459 http://dx.doi.org/10.7554/eLife.39188 |
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author | Squair, Jordan W Tigchelaar, Seth Moon, Kyung-Mee Liu, Jie Tetzlaff, Wolfram Kwon, Brian K Krassioukov, Andrei V West, Christopher R Foster, Leonard J Skinnider, Michael A |
author_facet | Squair, Jordan W Tigchelaar, Seth Moon, Kyung-Mee Liu, Jie Tetzlaff, Wolfram Kwon, Brian K Krassioukov, Andrei V West, Christopher R Foster, Leonard J Skinnider, Michael A |
author_sort | Squair, Jordan W |
collection | PubMed |
description | Spinal cord injury (SCI) is a devastating neurological condition for which there are currently no effective treatment options to restore function. A major obstacle to the development of new therapies is our fragmentary understanding of the coordinated pathophysiological processes triggered by damage to the human spinal cord. Here, we describe a systems biology approach to integrate decades of small-scale experiments with unbiased, genome-wide gene expression from the human spinal cord, revealing a gene regulatory network signature of the pathophysiological response to SCI. Our integrative analyses converge on an evolutionarily conserved gene subnetwork enriched for genes associated with the response to SCI by small-scale experiments, and whose expression is upregulated in a severity-dependent manner following injury and downregulated in functional recovery. We validate the severity-dependent upregulation of this subnetwork in rodents in primary transcriptomic and proteomic studies. Our analysis provides systems-level view of the coordinated molecular processes activated in response to SCI. |
format | Online Article Text |
id | pubmed-6173583 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-61735832018-10-11 Integrated systems analysis reveals conserved gene networks underlying response to spinal cord injury Squair, Jordan W Tigchelaar, Seth Moon, Kyung-Mee Liu, Jie Tetzlaff, Wolfram Kwon, Brian K Krassioukov, Andrei V West, Christopher R Foster, Leonard J Skinnider, Michael A eLife Computational and Systems Biology Spinal cord injury (SCI) is a devastating neurological condition for which there are currently no effective treatment options to restore function. A major obstacle to the development of new therapies is our fragmentary understanding of the coordinated pathophysiological processes triggered by damage to the human spinal cord. Here, we describe a systems biology approach to integrate decades of small-scale experiments with unbiased, genome-wide gene expression from the human spinal cord, revealing a gene regulatory network signature of the pathophysiological response to SCI. Our integrative analyses converge on an evolutionarily conserved gene subnetwork enriched for genes associated with the response to SCI by small-scale experiments, and whose expression is upregulated in a severity-dependent manner following injury and downregulated in functional recovery. We validate the severity-dependent upregulation of this subnetwork in rodents in primary transcriptomic and proteomic studies. Our analysis provides systems-level view of the coordinated molecular processes activated in response to SCI. eLife Sciences Publications, Ltd 2018-10-02 /pmc/articles/PMC6173583/ /pubmed/30277459 http://dx.doi.org/10.7554/eLife.39188 Text en © 2018, Squair et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Computational and Systems Biology Squair, Jordan W Tigchelaar, Seth Moon, Kyung-Mee Liu, Jie Tetzlaff, Wolfram Kwon, Brian K Krassioukov, Andrei V West, Christopher R Foster, Leonard J Skinnider, Michael A Integrated systems analysis reveals conserved gene networks underlying response to spinal cord injury |
title | Integrated systems analysis reveals conserved gene networks underlying response to spinal cord injury |
title_full | Integrated systems analysis reveals conserved gene networks underlying response to spinal cord injury |
title_fullStr | Integrated systems analysis reveals conserved gene networks underlying response to spinal cord injury |
title_full_unstemmed | Integrated systems analysis reveals conserved gene networks underlying response to spinal cord injury |
title_short | Integrated systems analysis reveals conserved gene networks underlying response to spinal cord injury |
title_sort | integrated systems analysis reveals conserved gene networks underlying response to spinal cord injury |
topic | Computational and Systems Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6173583/ https://www.ncbi.nlm.nih.gov/pubmed/30277459 http://dx.doi.org/10.7554/eLife.39188 |
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