Skip to content
DraconiticResearch
Search Sources API
181,713 studies31 sourcesUpdated 24 min ago
Peer-reviewedCC BYHuman mutation

CCR5, CD163, CSF1R, and FCGR3A as Candidate Biomarkers Associated With Mitophagy in Atherosclerosis.

  1. 1Department of Cardiology First Hospital of Quanzhou Affiliated to Fujian Medical University Quanzhou City China fjmu.edu.cn.

Abstract

Atherosclerosis is a chronic inflammatory disease, and the role of mitophagy in its pathogenesis remains unclear. To address this, this study integrated atherosclerosis-related transcriptome data and single-cell sequencing data from the GEO database, obtained mitophagy-related genes from MSigDB, and assessed mitophagy activity via GSEA and ssGSEA; WGCNA was used to screen disease- and mitophagy-associated module genes, and their intersection with differentially expressed genes yielded 286 candidate genes. A protein-protein interaction (PPI) network and cytoHubba algorithms were subsequently used to prioritize key genes, and dual machine learning algorithms (LASSO regression and SVM-RFE) to screen potential biomarkers, which were designated as CCR5, CD163, CSF1R, and FCGR3A. The expression patterns of all four candidates were further assessed in the independent GSE43292 dataset and were concordant with those observed in the discovery dataset. GSEA of samples stratified by candidate-gene expression identified enrichment of gene sets related to myogenesis, allograft rejection, and inflammatory responses; candidate drug-target associations were predicted using DSigDB, and exploratory AutoDock analysis suggested a feasible interaction between sunitinib and CSF1R. Additionally, exploratory single-cell analysis of three atherosclerosis patients identified seven major cell populations, with CD163, CSF1R, and FCGR3A showing macrophage-enriched expression within this dataset. Collectively, this study provides hypothesis-generating evidence for an association between mitophagy-related transcriptional patterns and atherosclerosis. Four candidate biomarkers (CCR5, CD163, CSF1R, and FCGR3A) were prioritized, and a potential CSF1R-sunitinib interaction was proposed for future experimental validation.

Related

  1. Identification of alcohol use disorder-associated and ethanol-responsive proteins and candidate biomarkers using human cortical organoids
    X. Li, A. J. Boreland, A. Agrawal +11
    bioRxivPreprintCC BY-NC-NDFull textCell biologybioRxiv
  2. Network-guided identification of candidate biomarkers for COPD-associated comorbidities using deep learning and real-world transcriptomic data
    J. M. Mas, E. Ramirez, X. Daura
    bioRxivPreprintCC BY-NCFull textSystems & synthetic biologybioRxiv
  3. Atherosclerosis Profiling Reveals BHLHE40 as a Candidate Modulator of VSMC
    Chinyere O. Ibikunle, Enrique J. Garcia, Chenyi Xue +14
    Circulation ResearchPeer-reviewedLicence not statedFull text8 citedImmunologyOpenAlex
  4. Deciphering Vascular Smooth Muscle Cell Phenotype Switching via Integrated Single-Cell Transcriptomics and Machine Learning: CX3CR1 and COL1A1 as Novel Diagnostic Biomarkers for Atherosclerosis
    Zhiqiang Wang, Zhenyu Zhao, Zhixi Hu +1
    MetabolitesPeer-reviewedCC BY 4.0ImmunologyCrossref
  5. Identification of CLOCK and MARK2 as Candidate Blood-Based Biomarkers in Type 2 Diabetes: An Integrated Bulk and Single-Cell Transcriptomic Study
    GenesPeer-reviewedCC BYFull textGenetics & genomicsEurope PMC
BibTeX
@article{fu2026ccr5,
  title = {{CCR5, CD163, CSF1R, and FCGR3A as Candidate Biomarkers Associated With Mitophagy in Atherosclerosis.}},
  author = {Jiadong Fu and Yongda Dong},
  journal = {Human mutation},
  year = {2026},
  month = oct,
  doi = {10.1155/humu/3810886},
  url = {https://europepmc.org/article/MED/42924190},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - CCR5, CD163, CSF1R, and FCGR3A as Candidate Biomarkers Associated With Mitophagy in Atherosclerosis.
AU  - Jiadong Fu
AU  - Yongda Dong
PY  - 2026
DA  - 2026/10/22
JO  - Human mutation
DO  - 10.1155/humu/3810886
UR  - https://europepmc.org/article/MED/42924190
AB  - Atherosclerosis is a chronic inflammatory disease, and the role of mitophagy in its pathogenesis remains unclear. To address this, this study integrated atherosclerosis-related transcriptome data and single-cell sequencing data from the GEO database, obtained mitophagy-related genes from MSigDB, and assessed mitophagy activity via GSEA and ssGSEA; WGCNA was used to screen disease- and mitophagy-associated module genes, and their intersection with differentially expressed genes yielded 286 candidate genes. A protein-protein interaction (PPI) network and cytoHubba algorithms were subsequently used to prioritize key genes, and dual machine learning algorithms (LASSO regression and SVM-RFE) to screen potential biomarkers, which were designated as CCR5, CD163, CSF1R, and FCGR3A. The expression patterns of all four candidates were further assessed in the independent GSE43292 dataset and were concordant with those observed in the discovery dataset. GSEA of samples stratified by candidate-gene expression identified enrichment of gene sets related to myogenesis, allograft rejection, and inflammatory responses; candidate drug-target associations were predicted using DSigDB, and exploratory AutoDock analysis suggested a feasible interaction between sunitinib and CSF1R. Additionally, exploratory single-cell analysis of three atherosclerosis patients identified seven major cell populations, with CD163, CSF1R, and FCGR3A showing macrophage-enriched expression within this dataset. Collectively, this study provides hypothesis-generating evidence for an association between mitophagy-related transcriptional patterns and atherosclerosis. Four candidate biomarkers (CCR5, CD163, CSF1R, and FCGR3A) were prioritized, and a potential CSF1R-sunitinib interaction was proposed for future experimental validation.
SN  - 1059-7794
SN  - 1098-1004
ER  -