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Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases

INTRODUCTION: Neurodegenerative diseases share common pathologic features including neuroinflammation, mitochondrial dysfunction and protein aggregation, suggesting common underlying mechanisms of neurodegeneration. We undertook a meta-analysis of public gene expression data for neurodegenerative di...

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Autores principales: Li, Matthew D, Burns, Terry C, Morgan, Alexander A, Khatri, Purvesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4167139/
https://www.ncbi.nlm.nih.gov/pubmed/25187168
http://dx.doi.org/10.1186/s40478-014-0093-y
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author Li, Matthew D
Burns, Terry C
Morgan, Alexander A
Khatri, Purvesh
author_facet Li, Matthew D
Burns, Terry C
Morgan, Alexander A
Khatri, Purvesh
author_sort Li, Matthew D
collection PubMed
description INTRODUCTION: Neurodegenerative diseases share common pathologic features including neuroinflammation, mitochondrial dysfunction and protein aggregation, suggesting common underlying mechanisms of neurodegeneration. We undertook a meta-analysis of public gene expression data for neurodegenerative diseases to identify a common transcriptional signature of neurodegeneration. RESULTS: Using 1,270 post-mortem central nervous system tissue samples from 13 patient cohorts covering four neurodegenerative diseases, we identified 243 differentially expressed genes, which were similarly dysregulated in 15 additional patient cohorts of 205 samples including seven neurodegenerative diseases. This gene signature correlated with histologic disease severity. Metallothioneins featured prominently among differentially expressed genes, and functional pathway analysis identified specific convergent themes of dysregulation. MetaCore network analyses revealed various novel candidate hub genes (e.g. STAU2). Genes associated with M1-polarized macrophages and reactive astrocytes were strongly enriched in the meta-analysis data. Evaluation of genes enriched in neurons revealed 70 down-regulated genes, over half not previously associated with neurodegeneration. Comparison with aging brain data (3 patient cohorts, 221 samples) revealed 53 of these to be unique to neurodegenerative disease, many of which are strong candidates to be important in neuropathogenesis (e.g. NDN, NAP1L2). ENCODE ChIP-seq analysis predicted common upstream transcriptional regulators not associated with normal aging (REST, RBBP5, SIN3A, SP2, YY1, ZNF143, IKZF1). Finally, we removed genes common to neurodegeneration from disease-specific gene signatures, revealing uniquely robust immune response and JAK-STAT signaling in amyotrophic lateral sclerosis. CONCLUSIONS: Our results implicate pervasive bioenergetic deficits, M1-type microglial activation and gliosis as unifying themes of neurodegeneration, and identify numerous novel genes associated with neurodegenerative processes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40478-014-0093-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-41671392014-09-19 Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases Li, Matthew D Burns, Terry C Morgan, Alexander A Khatri, Purvesh Acta Neuropathol Commun Research INTRODUCTION: Neurodegenerative diseases share common pathologic features including neuroinflammation, mitochondrial dysfunction and protein aggregation, suggesting common underlying mechanisms of neurodegeneration. We undertook a meta-analysis of public gene expression data for neurodegenerative diseases to identify a common transcriptional signature of neurodegeneration. RESULTS: Using 1,270 post-mortem central nervous system tissue samples from 13 patient cohorts covering four neurodegenerative diseases, we identified 243 differentially expressed genes, which were similarly dysregulated in 15 additional patient cohorts of 205 samples including seven neurodegenerative diseases. This gene signature correlated with histologic disease severity. Metallothioneins featured prominently among differentially expressed genes, and functional pathway analysis identified specific convergent themes of dysregulation. MetaCore network analyses revealed various novel candidate hub genes (e.g. STAU2). Genes associated with M1-polarized macrophages and reactive astrocytes were strongly enriched in the meta-analysis data. Evaluation of genes enriched in neurons revealed 70 down-regulated genes, over half not previously associated with neurodegeneration. Comparison with aging brain data (3 patient cohorts, 221 samples) revealed 53 of these to be unique to neurodegenerative disease, many of which are strong candidates to be important in neuropathogenesis (e.g. NDN, NAP1L2). ENCODE ChIP-seq analysis predicted common upstream transcriptional regulators not associated with normal aging (REST, RBBP5, SIN3A, SP2, YY1, ZNF143, IKZF1). Finally, we removed genes common to neurodegeneration from disease-specific gene signatures, revealing uniquely robust immune response and JAK-STAT signaling in amyotrophic lateral sclerosis. CONCLUSIONS: Our results implicate pervasive bioenergetic deficits, M1-type microglial activation and gliosis as unifying themes of neurodegeneration, and identify numerous novel genes associated with neurodegenerative processes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40478-014-0093-y) contains supplementary material, which is available to authorized users. BioMed Central 2014-09-04 /pmc/articles/PMC4167139/ /pubmed/25187168 http://dx.doi.org/10.1186/s40478-014-0093-y Text en © Li et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Li, Matthew D
Burns, Terry C
Morgan, Alexander A
Khatri, Purvesh
Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases
title Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases
title_full Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases
title_fullStr Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases
title_full_unstemmed Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases
title_short Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases
title_sort integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4167139/
https://www.ncbi.nlm.nih.gov/pubmed/25187168
http://dx.doi.org/10.1186/s40478-014-0093-y
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