ArticleAnnals of translational medicine2022
Single-cell transcriptomic, transcriptomic, and metabolomic characterization of human atherosclerosis.
Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 10 citations in OpenAlex.
- A Proteomic Atlas of Human Milk: Uncovering Milk Functional Components.Research square · 2026Article
- Mitochondrial cardiovascular diseases: molecular mechanisms, multi-omics exploration and therapeutic strategies.Journal of advanced research · 2026Review
- Early diagnosis of acute myocardial infarction via hub genes identified by integrated weighted gene co-expression network analysis.American heart journal plus : cardiology research and practice · 2025Article
- Cathepsin D inhibits AGEs-induced phenotypic transformation in vascular smooth muscle cells.Scientific reports · 2025Article
- Integrative multi-omics analysis of IFNγ-induced macrophages and atherosclerotic plaques reveals macrophage-dependent STAT1-driven transcription in atherosclerosis.Frontiers in immunology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Atherosclerosis is the main cause of many cardiovascular and cerebrovascular diseases (CVDs), and gaining a deeper understanding of the intercellular connections and key central genes which mediate formation of atherosclerotic plaques is required. Methods: We performed a comprehensive bioinformatics analysis of differential genetic screening, Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway annotation, protein-protein interactions (PPIs), pseudo-timing, intercellular communication, transcription factors on carotid single-cell sequencing data, and aortic bulk transcriptome and metabolomic data. Results: Ten cell types were identified in the data: T cells, monocytes, smooth muscle cells, endothelial cells, B cells, fibroblasts, plasma cells, mast cells, dendritic cells, and natural killer cells. Endothelial, fibroblast, macrophage, and smooth muscle cell subtype differentiation trajectories, interaction networks, and important transcription factors were characterized in detail. Finally, using this information combined with transcriptome and metabolome analyses, we found the key genes and signaling pathways of atherosclerosis, especially the advanced glycation end products and receptor for advanced glycation end products signaling pathway (AGE-RAGE signaling pathway) in diabetic complications, linked the differential metabolites with fibroblasts and atherosclerosis and contributed to it in patients with diabetes. Conclusions: Collectively, this study provides key genes, signaling pathways, cellular communication, and transcription factors among endothelial cells, fibroblasts, macrophages, and smooth muscle cells for the study of atherosclerotic plaques, and provides a basis for the diagnosis and treatment of atherosclerosis-like sclerosis.
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.