ArticleFrontiers in cardiovascular medicine2023
Hypoxia-associated genes predicting future risk of myocardial infarction: a GEO database-based study.
Article in Frontiers in cardiovascular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Risk prediction models for depression in patients with coronary heart disease: a systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2024Pooled it
- Vitamin D Receptor Regulates Oxidative Stress and Apoptosis Via the HIF-1α/HO-1 Pathway in Cardiomyocytes.Cell biochemistry and biophysics · 2025Article
- Molecular pathways in cardiovascular disease under hypoxia: Mechanisms, biomarkers, and therapeutic targets.Journal of biomedical research · 2025Article
- Inflammatory Biomarkers in Coronary Artery Disease: Insights From Mendelian Randomization and Transcriptomics.Journal of inflammation research · 2025Article
- Sevoflurane Suppresses Cardiomyocyte Pyroptosis in Myocardial Ischemia via NLRP3 Inflammasome Signaling.Analytical cellular pathology (Amsterdam) · 2025Article
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Authors and funding
4 authors at 4 institutions in 1 country.
Funding
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Abstract
Background: Patients with unstable angina (UA) are prone to myocardial infarction (MI) after an attack, yet the altered molecular expression profile therein remains unclear. The current work aims to identify the characteristic hypoxia-related genes associated with UA/MI and to develop a predictive model of hypoxia-related genes for the progression of UA to MI. Methods and results: Gene expression profiles were obtained from the GEO database. Then, differential expression analysis and the WGCNA method were performed to select characteristic genes related to hypoxia. Subsequently, all 10 hypoxia-related genes were screened using the Lasso regression model and a classification model was established. The area under the ROC curve of 1 shows its excellent classification performance and is confirmed on the validation set. In parallel, we construct a nomogram based on these genes, showing the risk of MI in patients with UA. Patients with UA and MI had their immunological status determined using CIBERSORT. These 10 genes were primarily linked to B cells and some inflammatory cells, according to correlation analysis. Conclusion: Overall, GWAS identified that the CSTF2F UA/MI risk gene promotes atherosclerosis, which provides the basis for the design of innovative cardiovascular drugs by targeting CSTF2F.
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