Cargando…

Hierarchical cortical transcriptome disorganization in autism

BACKGROUND: Autism spectrum disorders (ASD) are etiologically heterogeneous and complex. Functional genomics work has begun to identify a diverse array of dysregulated transcriptomic programs (e.g., synaptic, immune, cell cycle, DNA damage, WNT signaling, cortical patterning and differentiation) pot...

Descripción completa

Detalles Bibliográficos
Autores principales: Lombardo, Michael V., Courchesne, Eric, Lewis, Nathan E., Pramparo, Tiziano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5480153/
https://www.ncbi.nlm.nih.gov/pubmed/28649314
http://dx.doi.org/10.1186/s13229-017-0147-7
_version_ 1783245247873024000
author Lombardo, Michael V.
Courchesne, Eric
Lewis, Nathan E.
Pramparo, Tiziano
author_facet Lombardo, Michael V.
Courchesne, Eric
Lewis, Nathan E.
Pramparo, Tiziano
author_sort Lombardo, Michael V.
collection PubMed
description BACKGROUND: Autism spectrum disorders (ASD) are etiologically heterogeneous and complex. Functional genomics work has begun to identify a diverse array of dysregulated transcriptomic programs (e.g., synaptic, immune, cell cycle, DNA damage, WNT signaling, cortical patterning and differentiation) potentially involved in ASD brain abnormalities during childhood and adulthood. However, it remains unclear whether such diverse dysregulated pathways are independent of each other or instead reflect coordinated hierarchical systems-level pathology. METHODS: Two ASD cortical transcriptome datasets were re-analyzed using consensus weighted gene co-expression network analysis (WGCNA) to identify common co-expression modules across datasets. Linear mixed-effect models and Bayesian replication statistics were used to identify replicable differentially expressed modules. Eigengene network analysis was then utilized to identify between-group differences in how co-expression modules interact and cluster into hierarchical meta-modular organization. Protein-protein interaction analyses were also used to determine whether dysregulated co-expression modules show enhanced interactions. RESULTS: We find replicable evidence for 10 gene co-expression modules that are differentially expressed in ASD cortex. Rather than being independent non-interacting sources of pathology, these dysregulated co-expression modules work in synergy and physically interact at the protein level. These systems-level transcriptional signals are characterized by downregulation of synaptic processes coordinated with upregulation of immune/inflammation, response to other organism, catabolism, viral processes, translation, protein targeting and localization, cell proliferation, and vasculature development. Hierarchical organization of meta-modules (clusters of highly correlated modules) is also highly affected in ASD. CONCLUSIONS: These findings highlight that dysregulation of the ASD cortical transcriptome is characterized by the dysregulation of multiple coordinated transcriptional programs producing synergistic systems-level effects that cannot be fully appreciated by studying the individual component biological processes in isolation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13229-017-0147-7) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-5480153
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-54801532017-06-23 Hierarchical cortical transcriptome disorganization in autism Lombardo, Michael V. Courchesne, Eric Lewis, Nathan E. Pramparo, Tiziano Mol Autism Research BACKGROUND: Autism spectrum disorders (ASD) are etiologically heterogeneous and complex. Functional genomics work has begun to identify a diverse array of dysregulated transcriptomic programs (e.g., synaptic, immune, cell cycle, DNA damage, WNT signaling, cortical patterning and differentiation) potentially involved in ASD brain abnormalities during childhood and adulthood. However, it remains unclear whether such diverse dysregulated pathways are independent of each other or instead reflect coordinated hierarchical systems-level pathology. METHODS: Two ASD cortical transcriptome datasets were re-analyzed using consensus weighted gene co-expression network analysis (WGCNA) to identify common co-expression modules across datasets. Linear mixed-effect models and Bayesian replication statistics were used to identify replicable differentially expressed modules. Eigengene network analysis was then utilized to identify between-group differences in how co-expression modules interact and cluster into hierarchical meta-modular organization. Protein-protein interaction analyses were also used to determine whether dysregulated co-expression modules show enhanced interactions. RESULTS: We find replicable evidence for 10 gene co-expression modules that are differentially expressed in ASD cortex. Rather than being independent non-interacting sources of pathology, these dysregulated co-expression modules work in synergy and physically interact at the protein level. These systems-level transcriptional signals are characterized by downregulation of synaptic processes coordinated with upregulation of immune/inflammation, response to other organism, catabolism, viral processes, translation, protein targeting and localization, cell proliferation, and vasculature development. Hierarchical organization of meta-modules (clusters of highly correlated modules) is also highly affected in ASD. CONCLUSIONS: These findings highlight that dysregulation of the ASD cortical transcriptome is characterized by the dysregulation of multiple coordinated transcriptional programs producing synergistic systems-level effects that cannot be fully appreciated by studying the individual component biological processes in isolation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13229-017-0147-7) contains supplementary material, which is available to authorized users. BioMed Central 2017-06-21 /pmc/articles/PMC5480153/ /pubmed/28649314 http://dx.doi.org/10.1186/s13229-017-0147-7 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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
Lombardo, Michael V.
Courchesne, Eric
Lewis, Nathan E.
Pramparo, Tiziano
Hierarchical cortical transcriptome disorganization in autism
title Hierarchical cortical transcriptome disorganization in autism
title_full Hierarchical cortical transcriptome disorganization in autism
title_fullStr Hierarchical cortical transcriptome disorganization in autism
title_full_unstemmed Hierarchical cortical transcriptome disorganization in autism
title_short Hierarchical cortical transcriptome disorganization in autism
title_sort hierarchical cortical transcriptome disorganization in autism
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5480153/
https://www.ncbi.nlm.nih.gov/pubmed/28649314
http://dx.doi.org/10.1186/s13229-017-0147-7
work_keys_str_mv AT lombardomichaelv hierarchicalcorticaltranscriptomedisorganizationinautism
AT courchesneeric hierarchicalcorticaltranscriptomedisorganizationinautism
AT lewisnathane hierarchicalcorticaltranscriptomedisorganizationinautism
AT pramparotiziano hierarchicalcorticaltranscriptomedisorganizationinautism