ArticleFrontiers in neuroscience2022
Machine learning-based identification of the novel circRNAs circERBB2 and circCHST12 as potential biomarkers of intracerebral hemorrhage.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Systematic review and meta-analysis of stroke blood biomarker data highlights need for more translational research methods.Nature communications · 2026Pooled it
- Machine learning models based on laboratory data: new insight into the differential diagnosis of tuberculous and viral meningitis.Frontiers in cellular and infection microbiology · 2026Article
- Machine Learning-Driven Identification of Blood-Based Biomarkers and Therapeutic Agents for Personalized Ischemic Stroke Management.Journal of cardiovascular translational research · 2025Article
- Unveiling Pharmacogenomics Insights into Circular RNAs: Toward Precision Medicine in Cancer Therapy.Biomolecules · 2025Review
- Signature and function of plasma exosome-derived circular RNAs in patients with hypertensive intracerebral hemorrhage.Molecular genetics and genomics : MGG · 2024Article
- CircRNA-mediated regulation of cardiovascular disease.Frontiers in cardiovascular medicine · 2024Review
- Identification of immune-related biomarkers for intracerebral hemorrhage diagnosis based on RNA sequencing and machine learning.Frontiers in immunology · 2024Article
- High hsa_circ_0081621 expression indicates a poor prognosis of laryngeal squamous cell carcinoma: A bioinformatics analysis and retrospective clinical study.Oncology letters · 2023Article
- Targeting Non-Coding RNA for CNS Injuries: Regulation of Blood-Brain Barrier Functions.Neurochemical research · 2023Review
- Circular RNAs in ferroptosis: regulation mechanism and potential clinical application in disease.Frontiers in pharmacology · 2023Review
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The roles and potential diagnostic value of circRNAs in intracerebral hemorrhage (ICH) remain elusive. Methods: This study aims to investigate the expression profiles of circRNAs by RNA sequencing and RT-PCR in a discovery cohort and an independent validation cohort. Bioinformatics analysis was performed to identify the potential functions of circRNA host genes. Machine learning classification models were used to assess circRNAs as potential biomarkers of ICH. Results: A total of 125 and 284 differentially expressed circRNAs (fold change > 1.5 and FDR < 0.05) were found between ICH patients and healthy controls in the discovery and validation cohorts, respectively. Nine circRNAs were consistently altered in ICH patients compared to healthy controls. The combination of the novel circERBB2 and circCHST12 in ICH patients and healthy controls showed an area under the curve of 0.917 (95% CI: 0.869-0.965), with a sensitivity of 87.5% and a specificity of 82%. In combination with ICH risk factors, circRNAs improved the performance in discriminating ICH patients from healthy controls. Together with hsa_circ_0005505, two novel circRNAs for differentiating between patients with ICH and healthy controls showed an AUC of 0.946 (95% CI: 0.910-0.982), with a sensitivity of 89.1% and a specificity of 86%. Conclusion: We provided a transcriptome-wide overview of aberrantly expressed circRNAs in ICH patients and identified hsa_circ_0005505 and novel circERBB2 and circCHST12 as potential biomarkers for diagnosing ICH.
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