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• W3033932132 endingPage "e0234185" @default.
• W3033932132 startingPage "e0234185" @default.
• W3033932132 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." @default.
• W3033932132 created "2020-06-12" @default.
• W3033932132 creator A5001816949 @default.
• W3033932132 creator A5018161688 @default.
• W3033932132 creator A5073382602 @default.
• W3033932132 creator A5078521665 @default.
• W3033932132 date "2020-06-05" @default.
• W3033932132 modified "2023-10-13" @default.
• W3033932132 title "Principal component analysis of blood microRNA datasets facilitates diagnosis of diverse diseases" @default.
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