ArticlePloS one2020
Principal component analysis of blood microRNA datasets facilitates diagnosis of diverse diseases.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Circulating miRNA profiles in COVID-19 patients and meta-analysis: implications for disease progression and prognosis.Scientific reports · 2023Pooled it
- A systematic review of non-coding RNA genes with differential expression profiles associated with autism spectrum disorders.PloS one · 2023Pooled it
- Principal Component-Based Comprehensive Physical Health Score Associates With Long-Term Death in Patients With Ischemic Stroke.Journal of the American Heart Association · 2026Article
- MicroRNA bioinformatics in precision oncology: an integrated pipeline from NGS to AI-based target discovery.Journal of applied genetics · 2025Review
- Machine Learning-Based Etiologic Subtyping of Ischemic Stroke Using Circulating Exosomal microRNAs.International journal of molecular sciences · 2024Article
- MicroRNAs are associated with cardiac biomarkers, cardiac structure and function and incident outcomes in heart failure.ESC heart failure · 2024Article
- Potential diagnostic and drug target markers in glioblastoma.Scientific reports · 2024Article
- miR-603 promotes cell proliferation and differentiation by targeting TrkB in acute promyelocytic leukemia.Annals of hematology · 2023Article
- Altered microRNA expression in patients with sarcoidosis.Sarcoidosis, vasculitis, and diffuse lung diseases : official journal of WASOG · 2023Article
- Cellular miR-6741-5p as a Prognostic Biomarker Predicting Length of Hospital Stay among COVID-19 Patients.Viruses · 2022Article
- Establishment of a male fertility prediction model with sperm RNA markers in pigs as a translational animal model.Journal of animal science and biotechnology · 2022Article
- Multi-Method Diagnosis of Blood Microscopic Sample for Early Detection of Acute Lymphoblastic Leukemia Based on Deep Learning and Hybrid Techniques.Sensors (Basel, Switzerland) · 2022Article
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- Insomnia subtypes characterised by objective sleep duration and NREM spectral power and the effect of acute sleep restriction: an exploratory analysis.Scientific reports · 2021Article
- CRPGCN: predicting circRNA-disease associations using graph convolutional network based on heterogeneous network.BMC bioinformatics · 2021Article
- Leveraging publicly available coronavirus data to identify new therapeutic targets for COVID-19.PloS one · 2021Article
- Copper Content Inversion of Copper Ore Based on Reflectance Spectra and the VTELM Algorithm.Sensors (Basel, Switzerland) · 2020Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Early, ideally pre-symptomatic, recognition of common diseases (e.g., heart disease, cancer, diabetes, Alzheimer's disease) facilitates early treatment or lifestyle modifications, such as diet and exercise. Sensitive, specific identification of diseases using blood samples would facilitate early recognition. We explored the potential of disease identification in high dimensional blood microRNA (miRNA) datasets using a powerful data reduction method: principal component analysis (PCA). Using Qlucore Omics Explorer (QOE), a dynamic, interactive visualization-guided bioinformatics program with a built-in statistical platform, we analyzed publicly available blood miRNA datasets from the Gene Expression Omnibus (GEO) maintained at the National Center for Biotechnology Information at the National Institutes of Health (NIH). The miRNA expression profiles were generated from real time PCR arrays, microarrays or next generation sequencing of biologic materials (e.g., blood, serum or blood components such as platelets). PCA identified the top three principal components that distinguished cohorts of patients with specific diseases (e.g., heart disease, stroke, hypertension, sepsis, diabetes, specific types of cancer, HIV, hemophilia, subtypes of meningitis, multiple sclerosis, amyotrophic lateral sclerosis, Alzheimer's disease, mild cognitive impairment, aging, and autism), from healthy subjects. Literature searches verified the functional relevance of the discriminating miRNAs. Our goal is to assemble PCA and heatmap analyses of existing and future blood miRNA datasets into a clinical reference database to facilitate the diagnosis of diseases using routine blood draws.
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