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pmid:34925639

Crosstalk between Venous Thromboembolism and Periodontal Diseases: A Bioinformatics Analysis.

Zheng He · Qilong Jiang · Fuping Li · Mingxiang Chen

Disease markers · 2021 doi:10.1155/2021/1776567

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

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title
Crosstalk between Venous Thromboembolism and Periodontal Diseases: A Bioinformatics Analysis.
doi
10.1155/2021/1776567
pmid
34925639
authors array · 4 items
[0]
Zheng He
[1]
Qilong Jiang
[2]
Fuping Li
[3]
Mingxiang Chen
journal
Disease markers
year
2021
abstract
BACKGROUND: This current study applied bioinformatics analysis to reveal the crosstalk between venous thromboembolism (VTE) and periodontitis, as well as the potential role of immune-related genes in this context. METHODS: Expression data were downloaded from the GEO database. Blood samples from venous thromboembolism (VTE) were used (GSE19151), while for periodontal disease, we used gingival tissue samples (GSE10334, GSE16134, and GSE23586). After batch correction, we used "limma" packages of R language for differential expression analysis (p value < 0.05, ∣logFC | ≥0.5). We used Venn diagrams to extract the differentially expressed genes common to VTE and periodontitis as potential crosstalk genes and applied functional enrichment analysis (GO biological process and KEGG pathway). The protein-protein interaction (PPI) network of crosstalk genes was constructed by Cytoscape software. The immune-related genes were downloaded from the literature. The Wilcoxon test was used to test the scores of immune infiltrating cells. The crosstalk genes were further screened by LASSO Logistic Regression. RESULTS: For periodontitis, 427 case and 136 control samples, and for VTE, 70 case and 63 control samples were included. The obtained PPI network had 1879 nodes and 2257 edges. Moreover, 782 immune genes and 28 cell types were included in the analysis. Over 90% of immune cells had different expressions in VTE and periodontitis. We obtained 12 significant pathways corresponding to crosstalk genes. CD3D, CSF3R, and CXCR4 acted as an immune gene and a crosstalk gene. We obtained a total of 12 shared biomarker crosstalk genes. Among those 12 biomarker crosstalk genes, 4 were immune genes (LGALS1, LSP1, SAMSN1, and WIPF1). CONCLUSION: Four biomarker crosstalk genes between periodontitis and VTE were also immune genes, i.e., LGALS1, LSP1, SAMSN1, and WIPF1. The findings of the current study need further validation and are a basis for development of biomarkers.
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At the same time, the Wilcoxon test was used to test the scores of immune infiltrating cells in case samples of VTE and PD in two datasets to see whether there was a significant relationship between the same immune cells in the two diseases (p < 0.05).
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sections[7] "2.5. Immunoinfiltration Analysis of Immune Genes for VTE and PD" paragraph 2
quote
At the same time, the Wilcoxon test was used to test the scores of immune infiltrating cells in case samples of VTE and PD in two datasets to see whether there was a significant relationship between the same immune cells in the two diseases (p < 0.05).
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sections[22] "Data Availability" paragraph 2
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Four potential biomarker crosstalk genes were also immune genes, i.e., LGALS1, LSP1, SAMSN1, and WIPF1 between periodontitis and VTE.
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Four biomarker crosstalk genes between periodontitis and VTE were also immune genes, i.e., LGALS1, LSP1, SAMSN1, and WIPF1.
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Four potential biomarker crosstalk genes were also immune genes, i.e., LGALS1, LSP1, SAMSN1, and WIPF1 between periodontitis and VTE.
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310
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null
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null
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570
taxon
Homo sapiens
title
Bacterial Correlates of Gingival Gene Expression
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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[3] object · 15 fields
id
data:geo:GSE19151
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raw
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geo-series
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application/vnd.ncbi.geo-series+json
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19151
sha256
null
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null
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resolved
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reader_required
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GSE19151
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null
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
structure object · 15 fields
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GEO
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GEO accession URL
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
access_statement_kind
data_availability_statement
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sample_count
133
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null
group_sizes_basis
null
platform
571
taxon
Homo sapiens
title
Whole Blood Gene Expression Profiles Distinguish Patients with Single versus Recurrent Venous Thromboembolism
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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[4] object · 15 fields
id
data:geo:GSE23586
role
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geo-series
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application/vnd.ncbi.geo-series+json
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE23586
sha256
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null
note
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
structure object · 15 fields
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GEO
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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data_availability_statement
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[5]
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sample_count
6
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Altered gene expressions of leukocyte transendothelial migration and cell communication pathways in periodontitis-affected gingival tissues
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
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false
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[4]
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asset:data:geo:GSE19151 licence not read
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asset:data:geo:GSE23586 licence not read
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state
partial
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[0] object · 10 fields
id
method-1
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group_comparison
specific
wilcoxon
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group_comparison_wilcoxon
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evidence object · 3 fields
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quote
At the same time, the Wilcoxon test was used to test the scores of immune infiltrating cells in case samples of VTE and PD in two datasets to see whether there was a significant relationship between the same immune cells in the two diseases (p < 0.05).
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method-2
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limma_voom
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predictors_and_outcome
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method-4
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network_analysis
specific
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protein-protein interaction
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method.group_comparison_wilcoxon
capability object · 3 fields
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complete
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capability:computational_analysis
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candidate
Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
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complete
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nothing:replicable_now
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method object · 5 fields
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group_comparison_wilcoxon
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon.
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tier
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capability:computational_analysis
availability_state
owned
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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
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[0]
GSE19151
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[0]
GSE19151
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[2]
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GSE23586
statements array · 1 item
[0]
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
basis
The paper names GSE19151, GSE10334, GSE16134, GSE23586 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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source:pmid:34925639
[1]
data:geo:GSE10334
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group_comparison_wilcoxon
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null
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data:geo:GSE10334
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extraction_review
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MiniMax-M3.1-Flash
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minimax
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minimax
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independence
single_reader
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method
verbatim
availability
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8060
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1038
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pmid:34925639
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source:pmid:34925639
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PMID 34925639 full text
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GEO GSE10334
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data:geo:GSE10334
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GEO GSE10334
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agent:corpus-assay-engine
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[0]
data were downloaded from the GEO database. Blood samples from venous thromboembolism (VTE) were used (GSE1
order_basis
paper_text_order:328
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assay:1
[1] object · 11 fields
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f2132e96ae6c7a4e
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f2132e96ae6c7a4e
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At the same time, the Wilcoxon test was used to test the scores of immune infiltrating cells in case samples of VTE and PD in two datasets to see whether there was a significant relationship between the same immune cells in the two diseases (p < 0.05).
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34925639", "kind": "science-record", "revision": 4, "content_hash": "sha256:91fa93d5efc5f78ead4cbf971ab5b2da61f38de0de84224f8af54508f343dcc8", "created_at": "2026-11-01T17:36:38Z", "updated_at": "2026-11-01T22:05:23Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Crosstalk between Venous Thromboembolism and Periodontal Diseases: A Bioinformatics Analysis.", "doi": "10.1155/2021/1776567", "pmid": "34925639", "authors": ["Zheng He", "Qilong Jiang", "Fuping Li", "Mingxiang Chen"], "journal": "Disease markers", "year": 2021, "abstract": "BACKGROUND: This current study applied bioinformatics analysis to reveal the crosstalk between venous thromboembolism (VTE) and periodontitis, as well as the potential role of immune-related genes in this context.\nMETHODS: Expression data were downloaded from the GEO database. Blood samples from venous thromboembolism (VTE) were used (GSE19151), while for periodontal disease, we used gingival tissue samples (GSE10334, GSE16134, and GSE23586). After batch correction, we used \"limma\" packages of R language for differential expression analysis (p value < 0.05, ∣logFC | ≥0.5). We used Venn diagrams to extract the differentially expressed genes common to VTE and periodontitis as potential crosstalk genes and applied functional enrichment analysis (GO biological process and KEGG pathway). The protein-protein interaction (PPI) network of crosstalk genes was constructed by Cytoscape software. The immune-related genes were downloaded from the literature. The Wilcoxon test was used to test the scores of immune infiltrating cells. The crosstalk genes were further screened by LASSO Logistic Regression.\nRESULTS: For periodontitis, 427 case and 136 control samples, and for VTE, 70 case and 63 control samples were included. The obtained PPI network had 1879 nodes and 2257 edges. Moreover, 782 immune genes and 28 cell types were included in the analysis. Over 90% of immune cells had different expressions in VTE and periodontitis. We obtained 12 significant pathways corresponding to crosstalk genes. CD3D, CSF3R, and CXCR4 acted as an immune gene and a crosstalk gene. We obtained a total of 12 shared biomarker crosstalk genes. Among those 12 biomarker crosstalk genes, 4 were immune genes (LGALS1, LSP1, SAMSN1, and WIPF1).\nCONCLUSION: Four biomarker crosstalk genes between periodontitis and VTE were also immune genes, i.e., LGALS1, LSP1, SAMSN1, and WIPF1. The findings of the current study need further validation and are a basis for development of biomarkers.", "claims": [{"id": "claim-method", "statement": "At the same time, the Wilcoxon test was used to test the scores of immune infiltrating cells in case samples of VTE and PD in two datasets to see whether there was a significant relationship between the same immune cells in the two diseases (p < 0.05).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34925639", "locator": "sections[7] \"2.5. 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