ArticleBMC cardiovascular disorders2020
Identification of foam cell biomarkers by microarray analysis.
Article in BMC cardiovascular disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Transcriptome and DNA methylation analysis of the goat pineal gland during puberty.Scientific reports · 2025Article
- Comparative Transcriptome Analysis Unveils Regulatory Factors Influencing Fatty Liver Development in Lion-Head Geese under High-Intake Feeding Compared to Normal Feeding.Veterinary sciences · 2024Article
- The impact ofFrontiers in immunology · 2024Review
- Multi-omics analysis identifies potential mechanisms by which high glucose accelerates macrophage foaming.Molecular and cellular biochemistry · 2023Article
- An integrative analysis of single-cell and bulk transcriptome and bidirectional mendelian randomization analysis identified C1Q as a novel stimulated risk gene for Atherosclerosis.Frontiers in immunology · 2023Article
- Saturated very long-chain fatty acids regulate macrophage plasticity and invasiveness.Journal of neuroinflammation · 2022Article
- Inflammation Drives Stiffness Mediated Uptake of Lipoproteins in Primary Human Macrophages and Foam Cell Proliferation.Annals of biomedical engineering · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLipid infiltration and inflammatory response run through the occurrence of atherosclerosis. Differentiation into macrophages and foam cell formation are the key steps of AS. Aim of this study was that the differential gene expression between foam cells and macrophages was analyzed to search the key links of foam cell generation, so as to explore the pathogenesis of atherosclerosis and provide targets for the early screening and prevention of coronary artery disease (CAD).
methodsThe gene expression profiles of GSE9874 were downloaded from Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE9874) on GPL96 [HG-U133A] Affymetrix Human Genome U133. A total of 22,383 genes were analyzed for differentially expression genes (DEGs) by Bayes package. GO enrichment analysis and KEGG pathway analysis for DEGs were performed using KOBAS 3.0 software (Peking University, Beijing, China). STRING software (STRING 10.0; European Molecular Biology Laboratory, Heidelberg, Germany) was used to analyze the protein-protein interaction (PPI) of DEGs.
resultsA total of 167 DEGs between macrophages and foam cells were identified. Compared with macrophages, 102 genes were significantly upregulated and 65 genes were significantly downregulated (P < 0.01, fold-change > 1) in foam cells. DEGs were mainly enrich in 'sterol biosynthetic and metabolic process', 'cholesterol metabolic and biosynthetic process' by GO enrichment analysis. The results of KEGG pathway analysis showed all differential genes are involved in biological processes through 143 KEGG pathways. A PPI network of the DEGs was constructed and 10 outstanding genes of the PPI network was identified by using Cytoscape, which include HMGCR, SREBF2, LDLR, HMGCS1, FDFT1, LPL, DHCR24, SQLE, ABCA1 and FDPS.
conclusionLipid metabolism related genes and molecular pathways were the key to the transformation of macrophages into foam cells. Therefore, lipid metabolism disorder is the key to turn macrophages into foam cells, which plays a major role in CAD.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.