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pmid:39712025

Common diagnostic biomarkers and molecular mechanisms of Helicobacter pylori infection and inflammatory bowel disease.

Minglin Zhang · Tong Liu · Lijun Luo · Yi Zhang · Qijiao Chen · Fen Wang · Yuxin Xie

Frontiers in immunology · 2024 doi:10.3389/fimmu.2024.1492810

Paper

complete

Experiment

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Data

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pmid:39712025
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2026-11-01T20:30:02Z
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title
Common diagnostic biomarkers and molecular mechanisms of Helicobacter pylori infection and inflammatory bowel disease.
doi
10.3389/fimmu.2024.1492810
pmid
39712025
authors array · 7 items
[0]
Minglin Zhang
[1]
Tong Liu
[2]
Lijun Luo
[3]
Yi Zhang
[4]
Qijiao Chen
[5]
Fen Wang
[6]
Yuxin Xie
journal
Frontiers in immunology
year
2024
abstract
Background: Helicobacter pylori (H. pylori) may be present in the intestinal mucosa of patients with inflammatory bowel disease (IBD), which is a chronic inflammation of the gastrointestinal tract. The role of H. pylori in the pathogenesis of IBD remains unclear. In this study, bioinformatics techniques were used to investigate the correlation and co-pathogenic pathways between H. pylori and IBD. Methods: The following matrix data were downloaded from the GEO database: H. pylori-associated gastritis, GSE233973 and GSE27411; and IBD, GSE3365 and GSE179285. Differential gene analysis was performed via the limma software package in the R environment. A protein-protein interaction (PPI) network of DEGs was constructed via the STRING database. Cytoscape software, through the CytoHubba plugin, filters the PPI subnetwork and identifies Hub genes. Validation of the Hub genes was performed in the validation set. Immune analysis was conducted via the CIBERSORT algorithm. Transcription factor interaction and small molecule drug analyses of the Hub genes were also performed. Results: Using the GSE233973 and GSE3365 datasets, 151 differentially expressed genes (DEGs) were identified. GO enrichment analysis revealed involvement in leukocyte migration and chemotaxis, response to lipopolysaccharides, response to biostimulatory stimuli, and regulation of interleukin-8 (IL-8) production. Ten Hub genes (TLR4, IL10, CXCL8, IL1B, TLR2, CXCR2, CCL2, IL6, CCR1 and MMP-9) were identified via the PPI network and Cytoscape software. Enrichment analysis of the Hub genes focused on the lipopolysaccharide response, bacterial molecular response, biostimulatory response and leukocyte movement. Validation using the GSE27411 and GSE179285 datasets revealed that MMP-9 was significantly upregulated in both the H. pylori and IBD groups. The CIBERSORT algorithm revealed immune infiltration differences between the control and disease groups of IBD patients. Additionally, the CMap database identified the top 11 small molecule compounds across 10 cell types, including TPCA-1, AS-703026 and memantine, etc. Conclusion: Our study revealed the co-pathogenic mechanism between H. pylori and IBD and identified 10 Hub genes related to cellular immune regulation and signal transduction. The expression of MMP-9 is significantly upregulated in both H. pylori infection and IBD. This study provides a new perspective for exploring the prevention and treatment of H. pylori infection and IBD.
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For the GSE3365 and GSE233973 datasets, the limma software package was used to identify DEGs in the data in the R environment, and the screening criteria were P.adj. value < 0.05 and |LogFC| > 0.585.
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sections[4] "Screening of coexpressed DEGs" paragraph 2
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For the GSE3365 and GSE233973 datasets, the limma software package was used to identify DEGs in the data in the R environment, and the screening criteria were P.adj. value < 0.05 and |LogFC| > 0.585.
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The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author/s.
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sections[21] "Data availability statement" paragraph 2
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The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author/s.
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Using GSE233973 and GSE3365, the study identified 151 differentially expressed genes shared by H. pylori and IBD.
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Using the GSE233973 and GSE3365 datasets, 151 differentially expressed genes (DEGs) were identified.
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Using GSE233973 and GSE3365, the study identified 151 differentially expressed genes shared by H. pylori and IBD.
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[126]
GSM76156
sample_count
127
group_sizes
null
group_sizes_basis
null
platform
96
taxon
Homo sapiens
title
Comparison of PBMCs in Inflammatory Bowel Disease
resolution_checked_at
2026-11-01T18:46:34Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 8 items
[0]
asset:data:geo:GSE179285 not downloaded
[1]
asset:data:geo:GSE179285 licence not read
[2]
asset:data:geo:GSE233973 not downloaded
[3]
asset:data:geo:GSE233973 licence not read
[4]
asset:data:geo:GSE27411 not downloaded
[5]
asset:data:geo:GSE27411 licence not read
[6]
asset:data:geo:GSE3365 not downloaded
[7]
asset:data:geo:GSE3365 licence not read
analysis object · 4 fields
state
complete
methods array · 3 items
[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
parameters object · 0 fields
data_shapes array · 1 item
[0]
count_matrix_with_condition
evidence object · 3 fields
score
1
band
verbatim
quote
For the GSE3365 and GSE233973 datasets, the limma software package was used to identify DEGs in the data in the R environment, and the screening criteria were P.adj. value < 0.05 and |LogFC| > 0.585.
[1] object · 10 fields
id
method-2
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network_analysis
specific
ppi_network
label
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dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
protein-protein interaction
[2] object · 10 fields
id
method-3
family
network_analysis
specific
pathway_enrichment
label
Network / pathway analysis
dsl_operations array · 1 item
[0]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
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band
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quote
GO enrichment
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]
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[5]
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[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
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expressible
true
required_operations array · 3 items
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normalise_counts
[1]
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 · 4 items
[0]
GSE233973
[1]
GSE27411
[2]
GSE3365
[3]
GSE179285
resolved_accessions array · 4 items
[0]
GSE233973
[1]
GSE27411
[2]
GSE3365
[3]
GSE179285
statements array · 1 item
[0]
The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author/s.
basis
The paper names GSE233973, GSE27411, GSE3365, GSE179285 in Gene Expression Omnibus (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 · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
assets array · 2 items
[0]
source:pmid:39712025
[1]
data:geo:GSE179285
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:GSE179285
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
2026-11-01T19:43:13Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
11001
completion_tokens
1765
cached_tokens
128
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
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review.independent_reader
[1]
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[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
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gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:39712025
type
paper
label
pmid:39712025
[1] object · 3 fields
id
source:pmid:39712025
type
manuscript
label
PMID 39712025 full text
[2] object · 3 fields
id
data:geo:GSE179285
type
dataset
label
GEO GSE179285
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:39712025
type
paper
label
pmid:39712025
[1] object · 3 fields
id
source:pmid:39712025
type
manuscript
label
PMID 39712025 full text
[2] object · 3 fields
id
data:geo:GSE179285
type
dataset
label
GEO GSE179285
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-39712025
type
extraction
used array · 1 item
[0]
source:pmid:39712025
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE179285
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE179285
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
id
agent:corpus-assay-engine
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software
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Corpus assay engine
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id
agent:minimax-reader
type
software
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MiniMax literature reader
source_run_id
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dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
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lineage object · 4 fields
parent_id
pmid:39712025
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sha256:8a1b116b416fe7f43af9dad1ddd0c47f6ef6b69a5b384abadf604a73fcbddcc7
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gaps array · 12 items
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asset:data:geo:GSE179285 licence not read
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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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[11]
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dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
For the GSE3365 and GSE233973 datasets, the limma software package was used to identify DEGs in the data in the R environment, and the screening criteria were P.adj. value < 0.05 and |LogFC| > 0.585.
order_basis
analysis_only
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39712025", "kind": "science-record", "revision": 4, "content_hash": "sha256:7d28649ed35991ac1b9df904dfe6aeeb61cfd294e8bf313debb8d9dc6b361aa3", "created_at": "2026-11-01T20:30:02Z", "updated_at": "2026-11-01T22:55:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Common diagnostic biomarkers and molecular mechanisms of Helicobacter pylori infection and inflammatory bowel disease.", "doi": "10.3389/fimmu.2024.1492810", "pmid": "39712025", "authors": ["Minglin Zhang", "Tong Liu", "Lijun Luo", "Yi Zhang", "Qijiao Chen", "Fen Wang", "Yuxin Xie"], "journal": "Frontiers in immunology", "year": 2024, "abstract": "Background: Helicobacter pylori (H. pylori) may be present in the intestinal mucosa of patients with inflammatory bowel disease (IBD), which is a chronic inflammation of the gastrointestinal tract. The role of H. pylori in the pathogenesis of IBD remains unclear. In this study, bioinformatics techniques were used to investigate the correlation and co-pathogenic pathways between H. pylori and IBD.\nMethods: The following matrix data were downloaded from the GEO database: H. pylori-associated gastritis, GSE233973 and GSE27411; and IBD, GSE3365 and GSE179285. Differential gene analysis was performed via the limma software package in the R environment. A protein-protein interaction (PPI) network of DEGs was constructed via the STRING database. Cytoscape software, through the CytoHubba plugin, filters the PPI subnetwork and identifies Hub genes. Validation of the Hub genes was performed in the validation set. Immune analysis was conducted via the CIBERSORT algorithm. Transcription factor interaction and small molecule drug analyses of the Hub genes were also performed.\nResults: Using the GSE233973 and GSE3365 datasets, 151 differentially expressed genes (DEGs) were identified. GO enrichment analysis revealed involvement in leukocyte migration and chemotaxis, response to lipopolysaccharides, response to biostimulatory stimuli, and regulation of interleukin-8 (IL-8) production. Ten Hub genes (TLR4, IL10, CXCL8, IL1B, TLR2, CXCR2, CCL2, IL6, CCR1 and MMP-9) were identified via the PPI network and Cytoscape software. Enrichment analysis of the Hub genes focused on the lipopolysaccharide response, bacterial molecular response, biostimulatory response and leukocyte movement. Validation using the GSE27411 and GSE179285 datasets revealed that MMP-9 was significantly upregulated in both the H. pylori and IBD groups. The CIBERSORT algorithm revealed immune infiltration differences between the control and disease groups of IBD patients. Additionally, the CMap database identified the top 11 small molecule compounds across 10 cell types, including TPCA-1, AS-703026 and memantine, etc.\nConclusion: Our study revealed the co-pathogenic mechanism between H. pylori and IBD and identified 10 Hub genes related to cellular immune regulation and signal transduction. The expression of MMP-9 is significantly upregulated in both H. pylori infection and IBD. This study provides a new perspective for exploring the prevention and treatment of H. pylori infection and IBD.", "claims": [{"id": "claim-method", "statement": "For the GSE3365 and GSE233973 datasets, the limma software package was used to identify DEGs in the data in the R environment, and the screening criteria were P.adj. value < 0.05 and |LogFC| > 0.585.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39712025", "locator": "sections[4] \"Screening of coexpressed DEGs\" paragraph 2", "quote": "For the GSE3365 and GSE233973 datasets, the limma software package was used to identify DEGs in the data in the R environment, and the screening criteria were P.adj. value < 0.05 and |LogFC| > 0.585."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author/s.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39712025", "locator": "sections[21] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author/s."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using GSE233973 and GSE3365, the study identified 151 differentially expressed genes shared by H. pylori and IBD.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39712025", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Using the GSE233973 and GSE3365 datasets, 151 differentially expressed genes (DEGs) were identified."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Using GSE233973 and GSE3365, the study identified 151 differentially expressed genes shared by H. pylori and IBD.", "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:39712025"], "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:GSE179285"], "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:GSE179285"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39712025", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2024.1492810", "sha256": "sha256:29ba924579623a6159a141beb121faaac339383b49bb2cf0b2338e720a71005e", "bytes": 41723, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2024.1492810", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11659760", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE179285", "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=GSE179285", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE179285", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author/s.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/ Supplementary Material . 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