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pmid:35381625

Identification of Key Genes and Pathways in Peripheral Blood Mononuclear Cells of Type 1 Diabetes Mellitus by Integrated Bioinformatics Analysis.

Xing Li · Mingyu Liao · Jiangheng Guan · Ling Zhou · Rufei Shen · Min Long · Jiaqing Shao

Diabetes & metabolism journal · 2022 doi:10.4093/dmj.2021.0018

Paper

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Experiment

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Data

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title
Identification of Key Genes and Pathways in Peripheral Blood Mononuclear Cells of Type 1 Diabetes Mellitus by Integrated Bioinformatics Analysis.
doi
10.4093/dmj.2021.0018
pmid
35381625
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[0]
Xing Li
[1]
Mingyu Liao
[2]
Jiangheng Guan
[3]
Ling Zhou
[4]
Rufei Shen
[5]
Min Long
[6]
Jiaqing Shao
journal
Diabetes & metabolism journal
year
2022
abstract
BACKGROUND: The onset and progression of type 1 diabetes mellitus (T1DM) is closely related to autoimmunity. Effective monitoring of the immune system and developing targeted therapies are frontier fields in T1DM treatment. Currently, the most available tissue that reflects the immune system is peripheral blood mononuclear cells (PBMCs). Thus, the aim of this study was to identify key PBMC biomarkers of T1DM. METHODS: Common differentially expressed genes (DEGs) were screened from the Gene Expression Omnibus (GEO) datasets GSE9006, GSE72377, and GSE55098, and PBMC mRNA expression in T1DM patients was compared with that in healthy participants by GEO2R. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network analyses of DEGs were performed using the Cytoscape, DAVID, and STRING databases. The vital hub genes were validated by reverse transcription-polymerase chain reaction using clinical samples. The disease-gene-drug interaction network was built using the Comparative Toxicogenomics Database (CTD) and Drug Gene Interaction Database (DGIdb). RESULTS: We found that various biological functions or pathways related to the immune system and glucose metabolism changed in PBMCs from T1DM patients. In the PPI network, the DEGs of module 1 were significantly enriched in processes including inflammatory and immune responses and in pathways of proteoglycans in cancer. Moreover, we focused on four vital hub genes, namely, chitinase-3-like protein 1 (CHI3L1), C-X-C motif chemokine ligand 1 (CXCL1), matrix metallopeptidase 9 (MMP9), and granzyme B (GZMB), and confirmed them in clinical PBMC samples. Furthermore, the disease-gene-drug interaction network revealed the potential of key genes as reference markers in T1DM. CONCLUSION: These results provide new insight into T1DM pathogenesis and novel biomarkers that could be widely representative reference indicators or potential therapeutic targets for clinical applications.
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DEGs between T1DM and healthy PBMC samples were identified via GEO2R online tools with |FC| >1.1 and P<0.05.
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sections[5] "Microarray data processing and DEGs identification" paragraph 2
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DEGs between T1DM and healthy PBMC samples were identified via GEO2R online tools with |FC| >1.1 and P<0.05.
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NCBI-GEO is regarded as a free public database of microarray/gene profile and we obtained the gene expression profile of GSE9006, GSE72377, and GSE55098 analyzed by PBMCs from totally 70 T1DM patients and 54 healthy controls.
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The analysis identified 85 common DEGs among the three datasets, including 52 upregulated genes and 33 downregulated genes.
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sections[13] "Identification of DEGs in each GEO dataset" paragraph 2
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The results showed that there were 85 common DEGs among the three datasets, including 52 upregulated genes and 33 downregulated genes (Fig. 2B), which are listed in Supplementary Table 3.
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Gene expression in PBMCs from children with diabetes
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2026-11-01T15:39:55Z
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[3]
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DEGs between T1DM and healthy PBMC samples were identified via GEO2R online tools with |FC| >1.1 and P<0.05.
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NCBI-GEO is regarded as a free public database of microarray/gene profile and we obtained the gene expression profile of GSE9006, GSE72377, and GSE55098 analyzed by PBMCs from totally 70 T1DM patients and 54 healthy controls.
basis
The paper names GSE9006, GSE72377, GSE55098 in NCBI Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35381625", "kind": "science-record", "revision": 4, "content_hash": "sha256:1c9c54deca4f7787ee0abe422b11cc928695f1dfba49bedddd25314fd1376bcc", "created_at": "2026-11-01T18:14:12Z", "updated_at": "2026-11-01T22:06:15Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Key Genes and Pathways in Peripheral Blood Mononuclear Cells of Type 1 Diabetes Mellitus by Integrated Bioinformatics Analysis.", "doi": "10.4093/dmj.2021.0018", "pmid": "35381625", "authors": ["Xing Li", "Mingyu Liao", "Jiangheng Guan", "Ling Zhou", "Rufei Shen", "Min Long", "Jiaqing Shao"], "journal": "Diabetes & metabolism journal", "year": 2022, "abstract": "BACKGROUND: The onset and progression of type 1 diabetes mellitus (T1DM) is closely related to autoimmunity. Effective monitoring of the immune system and developing targeted therapies are frontier fields in T1DM treatment. Currently, the most available tissue that reflects the immune system is peripheral blood mononuclear cells (PBMCs). Thus, the aim of this study was to identify key PBMC biomarkers of T1DM.\nMETHODS: Common differentially expressed genes (DEGs) were screened from the Gene Expression Omnibus (GEO) datasets GSE9006, GSE72377, and GSE55098, and PBMC mRNA expression in T1DM patients was compared with that in healthy participants by GEO2R. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network analyses of DEGs were performed using the Cytoscape, DAVID, and STRING databases. The vital hub genes were validated by reverse transcription-polymerase chain reaction using clinical samples. The disease-gene-drug interaction network was built using the Comparative Toxicogenomics Database (CTD) and Drug Gene Interaction Database (DGIdb).\nRESULTS: We found that various biological functions or pathways related to the immune system and glucose metabolism changed in PBMCs from T1DM patients. In the PPI network, the DEGs of module 1 were significantly enriched in processes including inflammatory and immune responses and in pathways of proteoglycans in cancer. Moreover, we focused on four vital hub genes, namely, chitinase-3-like protein 1 (CHI3L1), C-X-C motif chemokine ligand 1 (CXCL1), matrix metallopeptidase 9 (MMP9), and granzyme B (GZMB), and confirmed them in clinical PBMC samples. Furthermore, the disease-gene-drug interaction network revealed the potential of key genes as reference markers in T1DM.\nCONCLUSION: These results provide new insight into T1DM pathogenesis and novel biomarkers that could be widely representative reference indicators or potential therapeutic targets for clinical applications.", "claims": [{"id": "claim-method", "statement": "DEGs between T1DM and healthy PBMC samples were identified via GEO2R online tools with |FC| >1.1 and P<0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35381625", "locator": "sections[5] \"Microarray data processing and DEGs identification\" paragraph 2", "quote": "DEGs between T1DM and healthy PBMC samples were identified via GEO2R online tools with |FC| >1.1 and P<0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "NCBI-GEO is regarded as a free public database of microarray/gene profile and we obtained the gene expression profile of GSE9006, GSE72377, and GSE55098 analyzed by PBMCs from totally 70 T1DM patients and 54 healthy controls.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35381625", "locator": "sections[4] \"Microarray data information\" paragraph 2", "quote": "NCBI-GEO is regarded as a free public database of microarray/gene profile and we obtained the gene expression profile of GSE9006, GSE72377, and GSE55098 analyzed by PBMCs from totally 70 T1DM patients and 54 healthy controls."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 85 common DEGs among the three datasets, including 52 upregulated genes and 33 downregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35381625", "locator": "sections[13] \"Identification of DEGs in each GEO dataset\" paragraph 2", "quote": "The results showed that there were 85 common DEGs among the three datasets, including 52 upregulated genes and 33 downregulated genes (Fig. 2B), which are listed in Supplementary Table 3."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The analysis identified 85 common DEGs among the three datasets, including 52 upregulated genes and 33 downregulated genes.", "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:35381625"], "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:GSE55098"], "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:GSE55098"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35381625", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.4093/dmj.2021.0018", "sha256": 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