Hierarchical cortical transcriptome disorganization in autism
Open accessAbstract
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 coexpression 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.
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Analysis of how gene co-expression modules interact within the cortical transcriptome of ASD supports the idea that a MIA-preserved translation initiation module is highly connected with immune/inflammation modules and other synaptic, cell cycle, and neurogenesis processes.
“Furthermore, analysis of how gene co-expression modules interact within the cortical transcriptome of ASD (i.e. via eigengene network analysis of the same ASD transcriptome dataset analyzed here) supports the idea that a MIA-preserved translation initiation module is highly connected with immune/inflammation modules and other synaptic, cell cycle, and neurogenesis processes.99”
From Maternal immune activation dysregulation of the fetal brain transcriptome and relevance to the pathophysiology of autism spectrum disorder (2018) · cites this paper as [99]
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Lombardo, M. V., Moon, H. M., Su, J. J., et al. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/064683 · Cited by 26 · see citing works
Self-citationDewitt, J. J., Hecht, P. M., Grepo, N., Wilkinson, B., Evgrafov, O. V., Morris, K. V., Knowles, J. A., & Campbell, D. B. (2016) · Developmental Neuroscience · doi:10.1159/000453258 · Cited by 23 · see citing works
Gokoolparsadh, A., Sutton, G. J., Charamko, A., Green, N. F. O., Pardy, C. J., & Voineagu, I. (2016) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-016-2304-0 · Cited by 18 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Lombardo, M. V., Moon, H. M., Su, J., Palmer, T. D., Courchesne, E., & Pramparo, T. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.15 · Cited by 201 · see citing works
Self-citation
- Authors
- Lombardo, M. V., Courchesne, E., Lewis, N. E., & Pramparo, T.
- Affiliations
- University of Cambridge (GB)
- University of California San Diego (US)
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2016-03-10
- OpenAlex
- W2339049666
- Cited by
- 7
- References
- 86
- Citations by year
- 2025: 1 · 2022: 1 · 2021: 1 · 2019: 1 · 2017: 1 · 2016: 2
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Simons Foundation
- National Alliance for Research on Schizophrenia and Depression (25434)
- Simons Foundation Autism Research Initiative
- National Institutes of Health (KL2TR001444)
- University of California, San Diego (1KL2TR001444)
- National Institute of Mental Health (1 R01 MH110558, R01-MH110558)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- autism spectrum disorder, cortical transcriptome, gene co-expression modules, synaptic dysfunction, protein-protein interaction, brain transcriptomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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