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pmid:37291580

Exploring the molecular mechanism of comorbidity of autism spectrum disorder and inflammatory bowel disease by combining multiple data sets.

Jinyi Zhu · Haoran Meng · Li Zhang · Yan Li

Journal of translational medicine · 2023 doi:10.1186/s12967-023-04218-z

Paper

complete

Experiment

complete

Data

partial

Analysis

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title
Exploring the molecular mechanism of comorbidity of autism spectrum disorder and inflammatory bowel disease by combining multiple data sets.
doi
10.1186/s12967-023-04218-z
pmid
37291580
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[0]
Jinyi Zhu
[1]
Haoran Meng
[2]
Li Zhang
[3]
Yan Li
journal
Journal of translational medicine
year
2023
abstract
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is difficult to diagnose. Inflammatory bowel disease (IBD) is a common chronic digestive disease. Previous studies have shown a potential correlation between ASD and IBD, but the pathophysiological mechanism remains unclear. The purpose of this research was to examine the biological mechanisms underlying the differentially expressed genes (DEGs) of ASD and IBD using bioinformatics tools. METHODS: Limma software was used to evaluate the DEGs between ASD and IBD. The GSE3365, GSE18123, and GSE150115 microarray data sets were acquired from the Gene Expression Omnibus (GEO) database. We then performed 6 analyses, namely, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation; weighted gene coexpression network analysis; correlation analysis of hub genes with autophagy, ferroptosis and immunity; transcriptional regulation analysis of hub genes; single-cell sequencing analysis; and potential therapeutic drug prediction. RESULTS: A total of 505 DEGs associated with ASD and 616 DEGs associated with IBD were identified, and 7 genes overlapped between these sets. GO and KEGG analyses revealed several pathways enriched in both diseases. A total of 98 common genes related to ASD and IBD were identified by weighted gene coexpression network analysis (WGCNA), and 4 hub genes were obtained by intersection with the 7 intersecting DEGs, which were PDGFC, CA2, GUCY1B3 and SDPR. We also found that 4 hub genes in the two diseases were related to autophagy, ferroptosis or immune factors. In addition, motif-TF annotation analysis showed that cisbp__M0080 was the most relevant motif. We also used the Connectivity Map (CMap) database to identify 4 potential therapeutic agents. CONCLUSION: This research reveals the shared pathogenesis of ASD and IBD. In the future, these common hub genes may provide new targets for further mechanistic research as well as new therapies for patients with ASD and IBD.
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The limma package [10] was used to compare the normal and disease-affected groups, and the screening criteria for DEGs were P value < 0.05 and |logFC|>0.585.
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The limma package [10] was used to compare the normal and disease-affected groups, and the screening criteria for DEGs were P value < 0.05 and |logFC|>0.585.
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The Series Matrix File data file of GSE18123 was downloaded from the NCBI GEO public database [9].
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A total of 98 common genes related to ASD and IBD were identified by weighted gene coexpression network analysis (WGCNA), and 4 hub genes were obtained by intersection with the 7 intersecting DEGs, which were PDGFC, CA2, GUCY1B3 and SDPR.
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A total of 98 common genes related to ASD and IBD were identified by weighted gene coexpression network analysis (WGCNA), and 4 hub genes were obtained by intersection with the 7 intersecting DEGs, which were PDGFC, CA2, GUCY1B3 and SDPR.
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A total of 98 common genes related to ASD and IBD were identified by weighted gene coexpression network analysis (WGCNA), and 4 hub genes were obtained by intersection with the 7 intersecting DEGs, which were PDGFC, CA2, GUCY1B3 and SDPR.
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identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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gaps array · 6 items
[0]
asset:data:geo:GSE150115 not downloaded
[1]
asset:data:geo:GSE150115 licence not read
[2]
asset:data:geo:GSE18123 not downloaded
[3]
asset:data:geo:GSE18123 licence not read
[4]
asset:data:geo:GSE3365 not downloaded
[5]
asset:data:geo:GSE3365 licence not read
analysis object · 4 fields
state
complete
methods array · 1 item
[0] object · 10 fields
id
method-1
family
differential_expression
specific
limma_voom
label
Differential expression analysis
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
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data_shapes array · 1 item
[0]
count_matrix_with_condition
evidence object · 3 fields
score
1
band
verbatim
quote
The limma package [10] was used to compare the normal and disease-affected groups, and the screening criteria for DEGs were P value < 0.05 and |logFC|>0.585.
targets array · 0 items
gaps array · 0 items
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 3 items
[0]
normalise_counts
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differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 3 items
[0]
GSE18123
[1]
GSE3365
[2]
GSE150115
resolved_accessions array · 3 items
[0]
GSE18123
[1]
GSE3365
[2]
GSE150115
statements array · 1 item
[0]
The Series Matrix File data file of GSE18123 was downloaded from the NCBI GEO public database [9].
basis
The paper names GSE18123, GSE3365, GSE150115 in NCBI GEO public database and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
assets array · 2 items
[0]
source:pmid:37291580
[1]
data:geo:GSE150115
steps array · 1 item
[0]
run_analysis
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE150115
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-11-01T18:43:24Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
null
calls
5
usage object · 3 fields
prompt_tokens
8945
completion_tokens
2165
cached_tokens
256
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
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review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:37291580
type
paper
label
pmid:37291580
[1] object · 3 fields
id
source:pmid:37291580
type
manuscript
label
PMID 37291580 full text
[2] object · 3 fields
id
data:geo:GSE150115
type
dataset
label
GEO GSE150115
activities array · 3 items
[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
used array · 3 items
[0] object · 3 fields
id
pmid:37291580
type
paper
label
pmid:37291580
[1] object · 3 fields
id
source:pmid:37291580
type
manuscript
label
PMID 37291580 full text
[2] object · 3 fields
id
data:geo:GSE150115
type
dataset
label
GEO GSE150115
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-37291580
type
extraction
used array · 1 item
[0]
source:pmid:37291580
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE150115
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE150115
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
id
agent:corpus-assay-engine
type
software
label
Corpus assay engine
[1] object · 3 fields
id
agent:minimax-reader
type
software
label
MiniMax literature reader
source_run_id
reading-sci-2026-11-01
dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
snapshot_id
ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:37291580
parent_hash
sha256:37732505da521860287f949305417eba507bae1c9440b4aa952e4a236ebb5abc
fork_of
null
gaps array · 10 items
[0]
asset:data:geo:GSE150115 licence not read
[1]
asset:data:geo:GSE150115 not downloaded
[2]
asset:data:geo:GSE18123 licence not read
[3]
asset:data:geo:GSE18123 not downloaded
[4]
asset:data:geo:GSE3365 licence not read
[5]
asset:data:geo:GSE3365 not downloaded
[6]
execution.not_run
[7]
review.human_critique
[8]
review.independent_reader
[9]
review.machine_critique
assays array · 1 item
[0] object · 11 fields
role
analysis
definition_id
differential_expression
definition_version
f2132e96ae6c7a4e
required_operations array · 3 items
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fdr_bh
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supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
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The limma package [10] was used to compare the normal and disease-affected groups, and the screening criteria for DEGs were P value < 0.05 and |logFC|>0.585.
order_basis
analysis_only
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assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37291580", "kind": "science-record", "revision": 4, "content_hash": "sha256:a6ec13d0a5e4e7b85ac1b5d1d642389e22522c760791f2002ad8dadf9c885c3d", "created_at": "2026-11-01T19:02:01Z", "updated_at": "2026-11-01T22:52:04Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploring the molecular mechanism of comorbidity of autism spectrum disorder and inflammatory bowel disease by combining multiple data sets.", "doi": "10.1186/s12967-023-04218-z", "pmid": "37291580", "authors": ["Jinyi Zhu", "Haoran Meng", "Li Zhang", "Yan Li"], "journal": "Journal of translational medicine", "year": 2023, "abstract": "BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is difficult to diagnose. Inflammatory bowel disease (IBD) is a common chronic digestive disease. Previous studies have shown a potential correlation between ASD and IBD, but the pathophysiological mechanism remains unclear. The purpose of this research was to examine the biological mechanisms underlying the differentially expressed genes (DEGs) of ASD and IBD using bioinformatics tools.\nMETHODS: Limma software was used to evaluate the DEGs between ASD and IBD. The GSE3365, GSE18123, and GSE150115 microarray data sets were acquired from the Gene Expression Omnibus (GEO) database. We then performed 6 analyses, namely, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation; weighted gene coexpression network analysis; correlation analysis of hub genes with autophagy, ferroptosis and immunity; transcriptional regulation analysis of hub genes; single-cell sequencing analysis; and potential therapeutic drug prediction.\nRESULTS: A total of 505 DEGs associated with ASD and 616 DEGs associated with IBD were identified, and 7 genes overlapped between these sets. GO and KEGG analyses revealed several pathways enriched in both diseases. A total of 98 common genes related to ASD and IBD were identified by weighted gene coexpression network analysis (WGCNA), and 4 hub genes were obtained by intersection with the 7 intersecting DEGs, which were PDGFC, CA2, GUCY1B3 and SDPR. We also found that 4 hub genes in the two diseases were related to autophagy, ferroptosis or immune factors. In addition, motif-TF annotation analysis showed that cisbp__M0080 was the most relevant motif. We also used the Connectivity Map (CMap) database to identify 4 potential therapeutic agents.\nCONCLUSION: This research reveals the shared pathogenesis of ASD and IBD. In the future, these common hub genes may provide new targets for further mechanistic research as well as new therapies for patients with ASD and IBD.", "claims": [{"id": "claim-method", "statement": "The limma package [10] was used to compare the normal and disease-affected groups, and the screening criteria for DEGs were P value < 0.05 and |logFC|>0.585.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37291580", "locator": "sections[3] \"Data download\" paragraph 2", "quote": "The limma package [10] was used to compare the normal and disease-affected groups, and the screening criteria for DEGs were P value < 0.05 and |logFC|>0.585."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The Series Matrix File data file of GSE18123 was downloaded from the NCBI GEO public database [9].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37291580", "locator": "sections[3] \"Data download\" paragraph 2", "quote": "The Series Matrix File data file of GSE18123 was downloaded from the NCBI GEO public database [9]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 98 common genes related to ASD and IBD were identified by weighted gene coexpression network analysis (WGCNA), and 4 hub genes were obtained by intersection with the 7 intersecting DEGs, which were PDGFC, CA2, GUCY1B3 and SDPR.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37291580", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 98 common genes related to ASD and IBD were identified by weighted gene coexpression network analysis (WGCNA), and 4 hub genes were obtained by intersection with the 7 intersecting DEGs, which were PDGFC, CA2, GUCY1B3 and SDPR."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A total of 98 common genes related to ASD and IBD were identified by weighted gene coexpression network analysis (WGCNA), and 4 hub genes were obtained by intersection with the 7 intersecting DEGs, which were PDGFC, CA2, GUCY1B3 and SDPR.", "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:37291580"], "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:GSE150115"], "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:GSE150115"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37291580", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12967-023-04218-z", "sha256": 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"structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The Series Matrix File data file of GSE18123 was downloaded from the NCBI GEO public database [9].", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM4523789", "GSM4523790", "GSM4523791", "GSM4523792", "GSM4523793"], "sample_count": 5, "group_sizes": null, "group_sizes_basis": null, "platform": "18573", "taxon": "Homo sapiens", "title": "Single-Cell Analyses of Colon and Blood Reveal Distinct Immune Cell Signatures of Ulcerative Colitis and Crohn’s Disease", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE18123", "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=GSE18123", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE18123", "version": null, "note": "The Series Matrix File data file of GSE18123 was downloaded from the NCBI GEO public database [9].", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The Series Matrix File data file of GSE18123 was downloaded from the NCBI GEO public database [9].", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM650510", "GSM650512", "GSM650513", "GSM650514", "GSM650515", "GSM650516", "GSM650517", "GSM650518", "GSM650519", "GSM650520", "GSM650521", "GSM650522", "GSM650523", "GSM650525", "GSM650526", "GSM650527", "GSM650528", "GSM650529", "GSM650530", "GSM650531", "GSM650532", "GSM650533", "GSM650534", "GSM650536", "GSM650537", "GSM650538", "GSM650540", "GSM650541", "GSM650542", "GSM650543", "GSM650544", "GSM650545", "GSM650546", "GSM650547", "GSM650548", "GSM650549", 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