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pmid:38464509

CD8+ T and NK cells characterized by upregulation of NPEPPS and ABHD17A are associated with the co-occurrence of type 2 diabetes and coronary artery disease.

Chenyu Dai · Damu Wang · Qianqian Tao · Ziyi Li · Peng Zhai · Yingying Wang · Mei Hou · Simin Cheng · Wei Qi · Longyi Zheng · Huaifang Yao

Frontiers in immunology · 2024 doi:10.3389/fimmu.2024.1267963

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complete

Experiment

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Data

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Analysis

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:38464509
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title
CD8+ T and NK cells characterized by upregulation of NPEPPS and ABHD17A are associated with the co-occurrence of type 2 diabetes and coronary artery disease.
doi
10.3389/fimmu.2024.1267963
pmid
38464509
authors array · 11 items
[0]
Chenyu Dai
[1]
Damu Wang
[2]
Qianqian Tao
[3]
Ziyi Li
[4]
Peng Zhai
[5]
Yingying Wang
[6]
Mei Hou
[7]
Simin Cheng
[8]
Wei Qi
[9]
Longyi Zheng
[10]
Huaifang Yao
journal
Frontiers in immunology
year
2024
abstract
Background: Coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM) are closely related. The function of immunocytes in the pathogenesis of CAD and T2DM has not been extensively studied. The quantitative bioinformatics analysis of the public RNA sequencing database was applied to study the key genes that mediate both CAD and T2DM. The biological characteristics of associated key genes and mechanism of CD8+ T and NK cells in CAD and T2DM are our research focus. Methods: With expression profiles of GSE66360 and GSE78721 from the Gene Expression Omnibus (GEO) database, we identified core modules associated with gene co-expression relationships and up-regulated genes in CAD and T2DM using Weighted Gene Co-expression Network Analysis (WGCNA) and the 'limma' software package. The enriched pathways of the candidate hub genes were then explored using GO, KEGG and GSEA in conjunction with the immune gene set (from the MSigDB database). A diagnostic model was constructed using logistic regression analysis composed of candidate hub genes in CAD and T2DM. Univariate Cox regression analysis revealed hazard ratios (HRs), 95% confidence intervals (CIs), and p-values for candidate hub genes in diagnostic model, while CIBERSORT and immune infiltration were used to assess the immune microenvironment. Finally, monocytes from peripheral blood samples and their immune cell ratios were analyzed by flow cytometry to validate our findings. Results: Sixteen candidate hub genes were identified as being correlated with immune infiltration. Univariate Cox regression analysis revealed that NPEPPS and ABHD17A were highly correlated with the diagnosis of CAD and T2DM. The results indicate that CD8+ T cells (p = 0.04) and NKbright cells (p = 3.7e-3) are significantly higher in healthy controls than in individuals with CAD or CAD combined with T2DM. The bioinformatics results on immune infiltration were well validated by flow cytometry. Conclusions: A series of bioinformatics studies have shown ABHD17A and NPEPPS as key genes for the co-occurrence of CAD and T2DM. Our study highlights the important effect of CD8+ T and NK cells in the pathogenesis of both diseases, indicating that they may serve as viable targets for diagnosis and therapeutic intervention.
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sections[6] "Construction and validation of diagnostic models and hub genes" paragraph 2
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Univariate Cox regression analysis of the expression of candidate hub genes from prediction model was conducted.
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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 authors.
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The results indicate that CD8+ T cells (p = 0.04) and NKbright cells (p = 3.7e-3) are significantly higher in healthy controls than in individuals with CAD or CAD combined with T2DM.
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The results indicate that CD8+ T cells (p = 0.04) and NKbright cells (p = 3.7e-3) are significantly higher in healthy controls than in individuals with CAD or CAD combined with T2DM.
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The results indicate that CD8+ T cells (p = 0.04) and NKbright cells (p = 3.7e-3) are significantly higher in healthy controls than in individuals with CAD or CAD combined with T2DM.
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activity-resolve-GSE66360
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE66360
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:38464509
parent_hash
sha256:442cda6d52019346a480d3a7551b3726ff4a85ee91f9ec25ea1d12b8b4282cc7
fork_of
null
gaps array · 8 items
[0]
asset:data:geo:GSE66360 licence not read
[1]
asset:data:geo:GSE66360 not downloaded
[2]
asset:data:geo:GSE78721 licence not read
[3]
asset:data:geo:GSE78721 not downloaded
[4]
execution.not_run
[5]
review.human_critique
[6]
review.independent_reader
[7]
review.machine_critique
assays array · 3 items
[0] object · 11 fields
role
data_generation
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rna_seq
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.93
evidence array · 1 item
[0]
tative bioinformatics analysis of the public RNA sequencing database was applied to study the key genes
order_basis
paper_text_order:365
id
assay:1
[1] object · 11 fields
role
data_generation
definition_id
flow_cytometry
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
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99e1195c7d6f
confidence
0.99
evidence array · 3 items
[0]
nd their immune cell ratios were analyzed by flow cytometry to validate our findings. Results: Sixteen c
[1]
n immune infiltration were well validated by flow cytometry. Conclusions: A series of bioinformatics stu
[2]
9 eligible healthy volunteers, and conducted flow cytometry immune examinations. Firstly, blood is taken
order_basis
paper_text_order:1522
id
assay:2
[2] object · 11 fields
role
analysis
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survival_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 1 item
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cox_ph
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supported
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dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
Univariate Cox regression analysis of the expression of candidate hub genes from prediction model was conducted.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38464509", "kind": "science-record", "revision": 3, "content_hash": "sha256:cd5f3effcfc459e774535b5c86b2f35bda58ce27fbc534d97826eebe571587ec", "created_at": "2026-11-01T19:20:24Z", "updated_at": "2026-11-01T22:11:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "CD8+ T and NK cells characterized by upregulation of NPEPPS and ABHD17A are associated with the co-occurrence of type 2 diabetes and coronary artery disease.", "doi": "10.3389/fimmu.2024.1267963", "pmid": "38464509", "authors": ["Chenyu Dai", "Damu Wang", "Qianqian Tao", "Ziyi Li", "Peng Zhai", "Yingying Wang", "Mei Hou", "Simin Cheng", "Wei Qi", "Longyi Zheng", "Huaifang Yao"], "journal": "Frontiers in immunology", "year": 2024, "abstract": "Background: Coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM) are closely related. The function of immunocytes in the pathogenesis of CAD and T2DM has not been extensively studied. The quantitative bioinformatics analysis of the public RNA sequencing database was applied to study the key genes that mediate both CAD and T2DM. The biological characteristics of associated key genes and mechanism of CD8+ T and NK cells in CAD and T2DM are our research focus.\nMethods: With expression profiles of GSE66360 and GSE78721 from the Gene Expression Omnibus (GEO) database, we identified core modules associated with gene co-expression relationships and up-regulated genes in CAD and T2DM using Weighted Gene Co-expression Network Analysis (WGCNA) and the 'limma' software package. The enriched pathways of the candidate hub genes were then explored using GO, KEGG and GSEA in conjunction with the immune gene set (from the MSigDB database). A diagnostic model was constructed using logistic regression analysis composed of candidate hub genes in CAD and T2DM. Univariate Cox regression analysis revealed hazard ratios (HRs), 95% confidence intervals (CIs), and p-values for candidate hub genes in diagnostic model, while CIBERSORT and immune infiltration were used to assess the immune microenvironment. Finally, monocytes from peripheral blood samples and their immune cell ratios were analyzed by flow cytometry to validate our findings.\nResults: Sixteen candidate hub genes were identified as being correlated with immune infiltration. Univariate Cox regression analysis revealed that NPEPPS and ABHD17A were highly correlated with the diagnosis of CAD and T2DM. The results indicate that CD8+ T cells (p = 0.04) and NKbright cells (p = 3.7e-3) are significantly higher in healthy controls than in individuals with CAD or CAD combined with T2DM. The bioinformatics results on immune infiltration were well validated by flow cytometry.\nConclusions: A series of bioinformatics studies have shown ABHD17A and NPEPPS as key genes for the co-occurrence of CAD and T2DM. Our study highlights the important effect of CD8+ T and NK cells in the pathogenesis of both diseases, indicating that they may serve as viable targets for diagnosis and therapeutic intervention.", "claims": [{"id": "claim-method", "statement": "Univariate Cox regression analysis of the expression of candidate hub genes from prediction model was conducted.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38464509", "locator": "sections[6] \"Construction and validation of diagnostic models and hub genes\" paragraph 2", "quote": "Univariate Cox regression analysis of the expression of candidate hub genes from prediction model was conducted."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . 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Further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The results indicate that CD8+ T cells (p = 0.04) and NKbright cells (p = 3.7e-3) are significantly higher in healthy controls than in individuals with CAD or CAD combined with T2DM.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38464509", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The results indicate that CD8+ T cells (p = 0.04) and NKbright cells (p = 3.7e-3) are significantly higher in healthy controls than in individuals with CAD or CAD combined with T2DM."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The results indicate that CD8+ T cells (p = 0.04) and NKbright cells (p = 3.7e-3) are significantly higher in healthy controls than in individuals with CAD or CAD combined with T2DM.", "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:38464509"], "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:GSE66360"], "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:GSE66360"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38464509", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2024.1267963", "sha256": "sha256:c6882ad237d1653798af55a2ae15d95e61438c0402e2eeb8ec9f3346ff17669e", "bytes": 49810, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2024.1267963", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10921359", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE66360", "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=GSE66360", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE66360", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . 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