ArticleBMC cardiovascular disorders2026
Identification of key genes related to macrophages and metabolic reprogramming in myocardial infarct based on single-cell and bulk transcriptomics data and experimental validation.
Article in BMC cardiovascular disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
backgroundMyocardial infarction (MI), one of the most severe cardiovascular diseases, is influenced by altered macrophage status and metabolic reprogramming (MR), yet the mechanisms of their crosstalk remain unclear. This study used bioinformatics to explore key genes associated with macrophages and MR function in MI.
methodsSingle-cell and bulk transcriptomics data of MI were obtained from public databases, and MR-related genes (MRGs) were downloaded from literature. Macrophage-associated differentially expressed genes (DEGs1) were identified from the single-cell data. Candidate genes were determined by intersecting MI-related DEGs (DEGs2), DEGs1, and MRGs. Machine learning, gene expression, and receiver operating characteristic (ROC) curve analyses were used to identify key genes. Drug prediction analysis was performed. Single-cell data were further analyzed to explore the underlying biological mechanisms of MI, followed by cell communication and pseudo-temporal analyses. Finally, RT-qPCR was used to validate the mRNA expression of key genes.
resultsA total of 304 DEGs1, 1,258 DEGs2, and 1,804 MRGs were intersected, identifying 6 candidate genes. The key genes (ABCG1, GNG11, and RPL24) were successfully identified. Pathways co-enriched by key genes included Huntington's disease, olfactory transduction, oxidative phosphorylation, proteasome, and spliceosome. Two drugs targeting ABCG1, APT and vitamin E, were identified. Macrophages displayed significant interactions with B/plasma cells and dendritic cells (DC) in MI samples. The expression of ABCG1 was significantly increased in MI, while GNG11 and RPL24 were decreased.
conclusionABCG1, GNG11, and RPL24 were identified as key regulators of macrophage function and MR in MI, providing valuable insights for the development of targeted therapies.
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.