ArticleFrontiers in veterinary science2024
Assessing the use of blood microRNA expression patterns for predictive diagnosis of myxomatous mitral valve disease in dogs.
Article in Frontiers in veterinary science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Identification of altered salivary microRNAs in Cavalier King Charles Spaniels affected by mitral valve disease at different ACVIM stages.Scientific reports · 2026Article
- A machine learning model for cancer screening in dogs using comprehensive circulating microRNA profiles.Journal of veterinary internal medicine · 2026Article
- Application of NMR-based metabolomics and machine learning for non-invasive disease screening in dogs.Frontiers in veterinary science · 2026Article
- Recent advances in omics-based research of mitral valve disease.Frontiers in cardiovascular medicine · 2026Review
- Genetic Basis of Myxomatous Mitral Valve Disease in Cavalier King Charles Spaniel Dogs-A Review.Veterinary sciences · 2025Review
- MicroRNA Expression Profiling in Canine Myxomatous Mitral Valve Disease Highlights Potential Diagnostic Tool and Molecular Pathways.Veterinary sciences · 2025Article
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Authors and funding
11 authors.
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Abstract
Background: Myxomatous mitral valve disease (MMVD) is a common, acquired, and progressive canine heart disease. The presence of heart murmur and current cardiac biomarkers are useful in MMVD cases but are not sufficiently discriminatory for staging an individual patient. Objectives: This study aimed to conduct a preliminary assessment of canine serum and plasma expression profiles of 15 selected miRNA markers for accurate discrimination between MMVD patients and healthy controls. Additionally, we aim to evaluate the effectiveness of this method in differentiating between pre-clinical (stage B1/B2) and clinical (stage C/D) MMVD patients. Animals: Client-owned dogs ( Methods: A multicenter, cross-sectional, prospective investigation was conducted. MicroRNA expression profiles were compared among dogs, and these profiles were used as input for predictive modeling. This approach aimed to distinguish between healthy controls and MMVD patients, as well as to achieve a more fine-grained differentiation between pre-clinical and clinical MMVD patients. Results: Performance metrics revealed a compelling ability of the method to differentiate healthy controls from dogs with MMVD (sensitivity 0.85; specificity 0.82; and accuracy 0.83). For the discrimination between the pre-clinical ( Conclusion and clinical importance: The use of miRNA expression profiles in combination with customized probabilistic predictive modeling shows good scope to devise a reliable diagnostic tool to distinguish healthy controls from MMVD cases (stages B1 to D). Investigation into the ability to discriminate between the pre-clinical and clinical MMVD cases using the same method yielded promising early results, which could be further enhanced with data from an increased study population.
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