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pmid:27390852

Systems Genetic Analyses Highlight a TGFβ-FOXO3 Dependent Striatal Astrocyte Network Conserved across Species and Associated with Stress, Sleep, and Huntington's Disease.

Joseph R Scarpa · Peng Jiang · Bojan Losic · Ben Readhead · Vance D Gao · Joel T Dudley · Martha H Vitaterna · Fred W Turek · Andrew Kasarskis

PLoS genetics · 2016 doi:10.1371/journal.pgen.1006137

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Systems Genetic Analyses Highlight a TGFβ-FOXO3 Dependent Striatal Astrocyte Network Conserved across Species and Associated with Stress, Sleep, and Huntington's Disease.
doi
10.1371/journal.pgen.1006137
pmid
27390852
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Joseph R Scarpa
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Peng Jiang
[2]
Bojan Losic
[3]
Ben Readhead
[4]
Vance D Gao
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Joel T Dudley
[6]
Martha H Vitaterna
[7]
Fred W Turek
[8]
Andrew Kasarskis
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PLoS genetics
year
2016
abstract
Recent systems-based analyses have demonstrated that sleep and stress traits emerge from shared genetic and transcriptional networks, and clinical work has elucidated the emergence of sleep dysfunction and stress susceptibility as early symptoms of Huntington's disease. Understanding the biological bases of these early non-motor symptoms may reveal therapeutic targets that prevent disease onset or slow disease progression, but the molecular mechanisms underlying this complex clinical presentation remain largely unknown. In the present work, we specifically examine the relationship between these psychiatric traits and Huntington's disease (HD) by identifying striatal transcriptional networks shared by HD, stress, and sleep phenotypes. First, we utilize a systems-based approach to examine a large publicly available human transcriptomic dataset for HD (GSE3790 from GEO) in a novel way. We use weighted gene coexpression network analysis and differential connectivity analyses to identify transcriptional networks dysregulated in HD, and we use an unbiased ranking scheme that leverages both gene- and network-level information to identify a novel astrocyte-specific network as most relevant to HD caudate. We validate this result in an independent HD cohort. Next, we computationally predict FOXO3 as a regulator of this network, and use multiple publicly available in vitro and in vivo experimental datasets to validate that this astrocyte HD network is downstream of a signaling pathway important in adult neurogenesis (TGFβ-FOXO3). We also map this HD-relevant caudate subnetwork to striatal transcriptional networks in a large (n = 100) chronically stressed (B6xA/J)F2 mouse population that has been extensively phenotyped (328 stress- and sleep-related measurements), and we show that this striatal astrocyte network is correlated to sleep and stress traits, many of which are known to be altered in HD cohorts. We identify causal regulators of this network through Bayesian network analysis, and we highlight their relevance to motor, mood, and sleep traits through multiple in silico approaches, including an examination of their protein binding partners. Finally, we show that these causal regulators may be therapeutically viable for HD because their downstream network was partially modulated by deep brain stimulation of the subthalamic nucleus, a medical intervention thought to confer some therapeutic benefit to HD patients. In conclusion, we show that an astrocyte transcriptional network is primarily associated to HD in the caudate and provide evidence for its relationship to molecular mechanisms of neural stem cell homeostasis. Furthermore, we present a unified systems-based framework for identifying gene networks that are associated with complex non-motor traits that manifest in the earliest phases of HD. By analyzing and integrating multiple independent datasets, we identify a point of molecular convergence between sleep, stress, and HD that reflects their phenotypic comorbidity and reveals a molecular pathway involved in HD progression.
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Using weighted gene coexpression network analysis[21], we constructed transcriptional networks of the CN, CB, and CTX from the HD cohort
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sections[3] "Gene network remodeling in the caudate, cerebellum, and frontal cortex of a human HD cohort" paragraph 2
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Using weighted gene coexpression network analysis[21], we constructed transcriptional networks of the CN, CB, and CTX from the HD cohort
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[198]
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[213]
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[216]
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[217]
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[228]
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[234]
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[235]
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[300]
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404
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null
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null
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96;97
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Homo sapiens
title
Human cerebellum, frontal cortex [BA4, BA9] and caudate nucleus HD tissue experiment
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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data:geo:GSE60137
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null
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All mouse data was generated and collected by authors of this manuscript and is available at NCBI GEO under accession number GSE60312. All human HD data was publicly available at NCBI GEO under accession numbers GSE3790 and GSE26927.
structure object · 15 fields
repository
GEO
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GEO accession URL
access_statement_verbatim
All mouse data was generated and collected by authors of this manuscript and is available at NCBI GEO under accession number GSE60312. All human HD data was publicly available at NCBI GEO under accession numbers GSE3790 and GSE26927.
access_statement_kind
data_availability_statement
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[5]
GSM1466228
sample_count
6
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null
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null
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13912
taxon
Mus musculus
title
Foxo3 Regulated Genes in G1E-ER-GATA-1 Cells
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
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licence_read
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null
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All mouse data was generated and collected by authors of this manuscript and is available at NCBI GEO under accession number GSE60312. All human HD data was publicly available at NCBI GEO under accession numbers GSE3790 and GSE26927.
structure object · 15 fields
repository
GEO
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GEO accession URL
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All mouse data was generated and collected by authors of this manuscript and is available at NCBI GEO under accession number GSE60312. All human HD data was publicly available at NCBI GEO under accession numbers GSE3790 and GSE26927.
access_statement_kind
data_availability_statement
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sample_count
100
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null
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null
platform
17021
taxon
Mus musculus
title
A systems approach identifies networks and genes linking sleep and stress: implications for neuropathology
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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gaps array · 14 items
[0]
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[5]
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[6]
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[7]
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[8]
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[13]
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analysis object · 4 fields
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[0] object · 10 fields
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edge_list
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score
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pathway enrichment
[1] object · 10 fields
id
method-2
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null
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null
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weighted gene coexpression network analysis
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parameters object · 0 fields
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evidence object · 3 fields
score
1
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verbatim
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Using weighted gene coexpression network analysis[21], we constructed transcriptional networks of the CN, CB, and CTX from the HD cohort
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gaps array · 1 item
[0]
method.reader_named_unmapped
capability object · 3 fields
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complete
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[0] object · 6 fields
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capability:computational_analysis
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[0]
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candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
state
complete
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pathway_enrich
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capability object · 4 fields
tier
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capability:computational_analysis
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
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tier
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GSE18326
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resolved_accessions array · 7 items
[0]
GSE60312
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statements array · 1 item
[0]
All mouse data was generated and collected by authors of this manuscript and is available at NCBI GEO under accession number GSE60312. All human HD data was publicly available at NCBI GEO under accession numbers GSE3790 and GSE26927.
basis
The paper names GSE60312, GSE3790, GSE26927, GSE60137, GSE13347, GSE18326, GSE26297 in NCBI GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 1 item
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[0]
source:pmid:27390852
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run_analysis
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data_gaps array · 1 item
[0]
data:geo:GSE13347
gaps array · 0 items
review object · 5 fields
state
partial
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kind
extraction_review
reader object · 5 fields
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MiniMax-M3.1-Flash
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minimax
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minimax
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null
independence
same_provider
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method
verbatim
availability
verbatim
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0
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[0] object · 4 fields
id
extraction
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complete
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MiniMax-M3.1-Flash
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classification
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PMID 27390852 full text
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GEO GSE13347
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agent:corpus-assay-engine
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agent:minimax-reader
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343fb30756ba6ec3
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lineage object · 4 fields
parent_id
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[11]
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[13]
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f2132e96ae6c7a4e
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:27390852", "kind": "science-record", "revision": 6, "content_hash": "sha256:47f6a7b701bdf076cc63218ca2d5e18cf5059933ea37190f131c0786be70b33b", "created_at": "2026-11-01T15:40:18Z", "updated_at": "2026-11-01T21:20:35Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Systems Genetic Analyses Highlight a TGFβ-FOXO3 Dependent Striatal Astrocyte Network Conserved across Species and Associated with Stress, Sleep, and Huntington's Disease.", "doi": "10.1371/journal.pgen.1006137", "pmid": "27390852", "authors": ["Joseph R Scarpa", "Peng Jiang", "Bojan Losic", "Ben Readhead", "Vance D Gao", "Joel T Dudley", "Martha H Vitaterna", "Fred W Turek", "Andrew Kasarskis"], "journal": "PLoS genetics", "year": 2016, "abstract": "Recent systems-based analyses have demonstrated that sleep and stress traits emerge from shared genetic and transcriptional networks, and clinical work has elucidated the emergence of sleep dysfunction and stress susceptibility as early symptoms of Huntington's disease. Understanding the biological bases of these early non-motor symptoms may reveal therapeutic targets that prevent disease onset or slow disease progression, but the molecular mechanisms underlying this complex clinical presentation remain largely unknown. In the present work, we specifically examine the relationship between these psychiatric traits and Huntington's disease (HD) by identifying striatal transcriptional networks shared by HD, stress, and sleep phenotypes. First, we utilize a systems-based approach to examine a large publicly available human transcriptomic dataset for HD (GSE3790 from GEO) in a novel way. We use weighted gene coexpression network analysis and differential connectivity analyses to identify transcriptional networks dysregulated in HD, and we use an unbiased ranking scheme that leverages both gene- and network-level information to identify a novel astrocyte-specific network as most relevant to HD caudate. We validate this result in an independent HD cohort. Next, we computationally predict FOXO3 as a regulator of this network, and use multiple publicly available in vitro and in vivo experimental datasets to validate that this astrocyte HD network is downstream of a signaling pathway important in adult neurogenesis (TGFβ-FOXO3). We also map this HD-relevant caudate subnetwork to striatal transcriptional networks in a large (n = 100) chronically stressed (B6xA/J)F2 mouse population that has been extensively phenotyped (328 stress- and sleep-related measurements), and we show that this striatal astrocyte network is correlated to sleep and stress traits, many of which are known to be altered in HD cohorts. We identify causal regulators of this network through Bayesian network analysis, and we highlight their relevance to motor, mood, and sleep traits through multiple in silico approaches, including an examination of their protein binding partners. Finally, we show that these causal regulators may be therapeutically viable for HD because their downstream network was partially modulated by deep brain stimulation of the subthalamic nucleus, a medical intervention thought to confer some therapeutic benefit to HD patients. In conclusion, we show that an astrocyte transcriptional network is primarily associated to HD in the caudate and provide evidence for its relationship to molecular mechanisms of neural stem cell homeostasis. Furthermore, we present a unified systems-based framework for identifying gene networks that are associated with complex non-motor traits that manifest in the earliest phases of HD. By analyzing and integrating multiple independent datasets, we identify a point of molecular convergence between sleep, stress, and HD that reflects their phenotypic comorbidity and reveals a molecular pathway involved in HD progression.", "claims": [{"id": "claim-method", "statement": "Using weighted gene coexpression network analysis[21], we constructed transcriptional networks of the CN, CB, and CTX from the HD cohort", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:27390852", "locator": "sections[3] \"Gene network remodeling in the caudate, cerebellum, and frontal cortex of a human HD cohort\" paragraph 2", "quote": "Using weighted gene coexpression network analysis[21], we constructed transcriptional networks of the CN, CB, and CTX from the HD cohort"}], "state": "complete"}, {"id": "claim-data-access", "statement": "All mouse data was generated and collected by authors of this manuscript and is available at NCBI GEO under accession number GSE60312. All human HD data was publicly available at NCBI GEO under accession numbers GSE3790 and GSE26927.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:27390852", "locator": "sections[22] \"Data Availability\" paragraph 2", "quote": "All mouse data was generated and collected by authors of this manuscript and is available at NCBI GEO under accession number GSE60312. All human HD data was publicly available at NCBI GEO under accession numbers GSE3790 and GSE26927."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:27390852"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE13347"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE13347"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:27390852", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1371/journal.pgen.1006137", "sha256": "sha256:998bfbfdf079bc449b248fda93eb44829a7dd109b0fc3897a63b6ad82543784c", "bytes": 94235, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1371/journal.pgen.1006137", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC4938493", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE13347", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13347", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE13347", "version": null, "note": "All mouse data was generated and collected by authors of this manuscript and is available at NCBI GEO under accession number GSE60312. 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