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pmid:41517672

Exploring the pathogenesis of nonalcoholic fatty liver disease complicated by atherosclerosis via bioinformatics.

Rui Yan · Ping Li · Jiahui Song · Yuwei Qiang · Guangyao Zhai

Medicine · 2026 doi:10.1097/MD.0000000000047035

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
id
pmid:41517672
kind
science-record
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sha256:0461538cbccc5dea0f873f36be20d90fb903d2c27ac18e0a17ed531d3d3856a3
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T20:31:29Z
updated_at
2026-11-01T22:57:43Z
generator object · 2 fields
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corpus-assay-engine
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paper object · 10 fields
state
complete
title
Exploring the pathogenesis of nonalcoholic fatty liver disease complicated by atherosclerosis via bioinformatics.
doi
10.1097/MD.0000000000047035
pmid
41517672
authors array · 5 items
[0]
Rui Yan
[1]
Ping Li
[2]
Jiahui Song
[3]
Yuwei Qiang
[4]
Guangyao Zhai
journal
Medicine
year
2026
abstract
This study aimed to explore the common differentially expressed genes (DEGs) between atherosclerosis (AS) and nonalcoholic fatty liver disease (NAFLD) through bioinformatics. The GSE89632 and GSE100927 datasets from the open-source GEO database were selected for analysis in this study. DEGs between the control and disease groups were identified from the datasets of NAFLD and AS, leading to the identification of genes that are commonly dysregulated in both conditions. Gene set enrichment analysis (GSEA) was performed on 2 datasets, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to investigate the potential biological functions and signaling pathways associated with the common DEGs. A protein-protein interaction network was constructed using the STRING database to identify hub genes. The diagnostic efficacy of these hub genes was evaluated through receiver operating characteristic curve analysis of the GSE63067 and GSE57691 datasets. A total of 45 common DEGs were identified. GSEA indicated that there were common pathways in the GSE89632 and GSE100927 datasets. The GO and KEGG pathway enrichment analyses revealed that the co-expressed genes were mainly enriched in regulating cytokine production, increasing responsiveness to external stimuli, and macrophage activation. The identified signaling pathways primarily included cytokine-cytokine receptor interaction, the toll-like receptor signaling pathway, and the interleukin-17 signaling pathway. Ten hub genes were OSM, IL1B, CCL3, CSF3, IL1RN, TAGLN, CNN1, RGCC, MYH11, and ACTG2. Common DEGs were identified between AS and NAFLD, indicating that these diseases may mutually influence and exacerbate each other during their progression. Exploring their shared pathogenic mechanisms may provide insights into potential therapeutic targets and contribute to the prevention of AS development in patients with NAFLD.
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DEG screening between NAFLD and control groups, as well as between AS and control groups, was implemented using the limma package (version 3.40.6) in R software.
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sections[5] "2.2.1. DEG screening" paragraph 3
quote
DEG screening between NAFLD and control groups, as well as between AS and control groups, was implemented using the limma package (version 3.40.6) in R software.
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sections[25] "(untitled)" paragraph 1
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The datasets generated during and/or analyzed during the current study are publicly available.
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A total of 45 common DEGs were identified between AS and NAFLD.
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qualitative
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null
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sections[0] "Abstract" paragraph 1
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A total of 45 common DEGs were identified.
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complete
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experiment object · 8 fields
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A total of 45 common DEGs were identified between AS and NAFLD.
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the published estimate and its evidence
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The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.
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Apply the paper's statistical method to the resolved series and compare the result with the published target.
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The datasets generated during and/or analyzed during the current study are publicly available.
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The datasets generated during and/or analyzed during the current study are publicly available.
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GSM2696704
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GSM2696712
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104
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null
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null
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17077
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Homo sapiens
title
Atherosclerotic and control peripheral artery gene expression
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2026-11-01T15:39:54Z
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identifier_resolution_only_no_download_no_licence_read
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null
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GEO accession URL
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The datasets generated during and/or analyzed during the current study are publicly available.
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GSM1386787
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GSM1386831
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GSM1386847
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GSM1386848
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GSM1386850
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68
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null
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null
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10558
taxon
Homo sapiens
title
Differential gene expression in human abdominal aortic aneurysm and atherosclerosis
resolution_checked_at
2026-11-01T15:39:54Z
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identifier_resolution_only_no_download_no_licence_read
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[3] object · 15 fields
id
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null
note
The datasets generated during and/or analyzed during the current study are publicly available.
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GEO
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GEO accession URL
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The datasets generated during and/or analyzed during the current study are publicly available.
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data_availability_statement
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[17]
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18
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null
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null
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570
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Homo sapiens
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Expression data from human non-alcoholic fatty liver disease stages
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2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
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data:geo:GSE89632
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GSE89632
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null
note
The datasets generated during and/or analyzed during the current study are publicly available.
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repository
GEO
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GEO accession URL
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The datasets generated during and/or analyzed during the current study are publicly available.
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data_availability_statement
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63
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null
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null
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14951
taxon
Homo sapiens
title
Genome-wide analysis of hepatic gene expression in patients with non-alcoholic fatty liver disease and in healthy donors in relation to hepatic fatty acid composition and other nutritional factors
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2026-11-01T15:39:55Z
resolution_check
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[2]
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[3]
asset:data:geo:GSE57691 licence not read
[4]
asset:data:geo:GSE63067 not downloaded
[5]
asset:data:geo:GSE63067 licence not read
[6]
asset:data:geo:GSE89632 not downloaded
[7]
asset:data:geo:GSE89632 licence not read
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[0]
normalise_counts
[1]
differential_expression_fit
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fdr_bh
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[0]
count_matrix_with_condition
evidence object · 3 fields
score
1
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verbatim
quote
DEG screening between NAFLD and control groups, as well as between AS and control groups, was implemented using the limma package (version 3.40.6) in R software.
[1] object · 10 fields
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Group comparison
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[0]
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two_or_more_groups_continuous
evidence object · 3 fields
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evidence object · 3 fields
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method-5
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Network / pathway analysis
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pathway enrichment
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Automated Assays Laravel application and simulated adapters
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[0]
The datasets generated during and/or analyzed during the current study are publicly available.
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The paper names GSE89632, GSE100927, GSE63067, GSE57691 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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DEG screening between NAFLD and control groups, as well as between AS and control groups, was implemented using the limma package (version 3.40.6) in R software.
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The GSE89632 and GSE100927 datasets from the open-source GEO database were selected for analysis in this study. DEGs between the control and disease groups were identified from the datasets of NAFLD and AS, leading to the identification of genes that are commonly dysregulated in both conditions. Gene set enrichment analysis (GSEA) was performed on 2 datasets, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to investigate the potential biological functions and signaling pathways associated with the common DEGs. A protein-protein interaction network was constructed using the STRING database to identify hub genes. The diagnostic efficacy of these hub genes was evaluated through receiver operating characteristic curve analysis of the GSE63067 and GSE57691 datasets. A total of 45 common DEGs were identified. GSEA indicated that there were common pathways in the GSE89632 and GSE100927 datasets. The GO and KEGG pathway enrichment analyses revealed that the co-expressed genes were mainly enriched in regulating cytokine production, increasing responsiveness to external stimuli, and macrophage activation. The identified signaling pathways primarily included cytokine-cytokine receptor interaction, the toll-like receptor signaling pathway, and the interleukin-17 signaling pathway. Ten hub genes were OSM, IL1B, CCL3, CSF3, IL1RN, TAGLN, CNN1, RGCC, MYH11, and ACTG2. Common DEGs were identified between AS and NAFLD, indicating that these diseases may mutually influence and exacerbate each other during their progression. 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