Comprehensive analysis to identify the influences of SARS-CoV-2 infections to inflammatory bowel disease.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36817436", "kind": "science-record", "revision": 4, "content_hash": "sha256:84fba13ac7161faa3beefbbae69e3205c9716e1ea8bcae8dbc434fef48306745", "created_at": "2026-11-01T19:01:24Z", "updated_at": "2026-11-01T22:51:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive analysis to identify the influences of SARS-CoV-2 infections to inflammatory bowel disease.", "doi": "10.3389/fimmu.2023.1024041", "pmid": "36817436", "authors": ["Chengyan Zhang", "Zeyu Ma", "Xi Nan", "Wenhui Wang", "Xianchang Zeng", "Jinming Chen", "Zhijian Cai", "Jianli Wang"], "journal": "Frontiers in immunology", "year": 2023, "abstract": "Background: Coronavirus disease 2019 (COVID-19) and inflammatory bowel disease (IBD) are both caused by a disordered immune response and have direct and profound impacts on health care services. In this study, we implemented transcriptomic and single-cell analysis to detect common molecular and cellular intersections between COVID-19 and IBD that help understand the linkage of COVID-19 to the IBD patients.\nMethods: Four RNA-sequencing datasets (GSE147507, GSE126124, GSE9686 and GSE36807) from Gene Expression Omnibus (GEO) database are extracted to detect mutual differentially expressed genes (DEGs) for IBD patients with the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to find shared pathways, candidate drugs, hub genes and regulatory networks. Two single-cell RNA sequencing (scRNA-eq) datasets (GSE150728, PRJCA003980) are used to analyze the immune characteristics of hub genes and the proportion of immune cell types, so as to find common immune responses between COVID-19 and IBD.\nResults: A total of 121 common DEGs were identified among four RNA-seq datasets, and were all involved in the functional enrichment analysis related to inflammation and immune response. Transcription factors-DEGs interactions, miRNAs-DEGs coregulatory networks, and protein-drug interactions were identified based on these datasets. Protein-protein interactions (PPIs) was built and 59 hub genes were identified. Moreover, scRNA-seq of peripheral blood monocyte cells (PBMCs) from COVID-19 patients revealed a significant increase in the proportion of CD14+ monocytes, in which 38 of 59 hub genes were highly enriched. These genes, encoding inflammatory cytokines, were also highly expressed in inflammatory macrophages (IMacrophage) of intestinal tissues of IBD patients.\nConclusions: We conclude that COVID-19 may promote the progression of IBD through cytokine storms. The candidate drugs and DEGs-regulated networks may suggest effective therapeutic methods for both COVID-19 and IBD.", "claims": [{"id": "claim-method", "statement": "To acquire DEGs for the datasets GSE147507 and GSE126124, the “limma” package (21) was employed to select DEGs with |log2FC | > 0.585 (22) and p-value < 0.05 (23).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36817436", "locator": "sections[4] \"Identification of DEGs and the common DEGs among COVID-19 and IBD\" paragraph 2", "quote": "To acquire DEGs for the datasets GSE147507 and GSE126124, the “limma” package (21) was employed to select DEGs with |log2FC | > 0.585 (22) and p-value < 0.05 (23)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36817436", "locator": "sections[21] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The integrated analysis identified 121 differentially expressed genes shared by COVID-19, Crohn's disease, and ulcerative colitis.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36817436", "locator": "sections[12] \"Identification of the common DEGs between COVID-19 and IBD\" paragraph 2", "quote": "We identified 121 common DEGs between these datasets through a Venn diagram ( Figure 2 and Supplementary Table S1 )."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The integrated analysis identified 121 differentially expressed genes shared by COVID-19, Crohn's disease, and ulcerative colitis.", "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:36817436"], "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:GSE126124"], "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:GSE126124"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36817436", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2023.1024041", "sha256": "sha256:b11e4805a6fceac4510e56cfc8f517d191a530e8d2ac1331c2f930c737535d0b", "bytes": 53772, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2023.1024041", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9936160", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE126124", "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=GSE126124", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE126124", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE147507", "GSE126124", "GSE9686", "GSE36807", "GSE157103", "GSE75214", "GSE150728", "GSE16879"], "resolved_accessions": ["GSE147507", "GSE126124", "GSE9686", "GSE36807", "GSE157103", "GSE75214", "GSE150728", "GSE16879"], "statements": ["The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."], "basis": "The paper names GSE147507, GSE126124, GSE9686, GSE36807, GSE157103, GSE75214, GSE150728, GSE16879 in Gene Expression Omnibus (GEO) database and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:36817436", "data:geo:GSE126124"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE126124"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:28:08Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 16022, "completion_tokens": 2590, "cached_tokens": 128}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:36817436", "type": "paper", "label": "pmid:36817436"}, {"id": "source:pmid:36817436", "type": "manuscript", "label": "PMID 36817436 full text"}, {"id": "data:geo:GSE126124", "type": "dataset", "label": "GEO GSE126124"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36817436", "type": "paper", "label": "pmid:36817436"}, {"id": "source:pmid:36817436", "type": "manuscript", "label": "PMID 36817436 full text"}, {"id": "data:geo:GSE126124", "type": "dataset", "label": "GEO GSE126124"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36817436", "type": "extraction", "used": ["source:pmid:36817436"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE126124", "type": "accession_resolution", "used": ["data:geo:GSE126124"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"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": {"parent_id": "pmid:36817436", "parent_hash": "sha256:eceeb0e7041aae5f8caec64b45b2f7045ef6ccb6deb3a433c3b0bc1c54a41c09", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE126124 licence not read", "asset:data:geo:GSE126124 not downloaded", "asset:data:geo:GSE147507 licence not read", "asset:data:geo:GSE147507 not downloaded", "asset:data:geo:GSE150728 licence not read", "asset:data:geo:GSE150728 not downloaded", "asset:data:geo:GSE157103 licence not read", "asset:data:geo:GSE157103 not downloaded", "asset:data:geo:GSE16879 licence not read", "asset:data:geo:GSE16879 not downloaded", "asset:data:geo:GSE36807 licence not read", "asset:data:geo:GSE36807 not downloaded", "asset:data:geo:GSE75214 licence not read", "asset:data:geo:GSE75214 not downloaded", "asset:data:geo:GSE9686 licence not read", "asset:data:geo:GSE9686 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["COVID-19 to the IBD patients. Methods: Four RNA-sequencing datasets (GSE147507, GSE126124, GSE9686 and", "f 121 common DEGs were identified among four RNA-seq datasets, and were all involved in the funct", "nes and regulatory networks. Two single-cell RNA sequencing (scRNA-eq) datasets (GSE150728, PRJCA003980)", "care services. In this study, we implemented transcriptomic and single-cell analysis to detect common mo"], "order_basis": "paper_text_order:286", "id": "assay:1"}, {"role": "data_generation", "definition_id": "scrna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "unsupported", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["rugs, hub genes and regulatory networks. Two single-cell RNA sequencing (scRNA-eq) datasets (GSE150728, PRJCA003980)", "and 59 hub genes were identified. Moreover, scRNA-seq of peripheral blood monocyte cells (PBMCs) f", "flammation-related DEGs (IRGs) identified in scRNA-seq data, we downloaded RNA-seq data (GSE16879)"], "order_basis": "paper_text_order:848", "id": "assay:2"}, {"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["after treatment using the platform of GPL570 Affymetrix Human Genome U133 Plus 2.0 Array. The ‘heatm"], "order_basis": "paper_text_order:3341", "id": "assay:3"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["To acquire DEGs for the datasets GSE147507 and GSE126124, the “limma” package (21) was employed to select DEGs with |log2FC | > 0.585 (22) and p-value < 0.05 (23)."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}