MiR-320a as a Potential Novel Circulating Biomarker of Arrhythmogenic CardioMyopathy.
Elena SommarivaYuri D'AlessandraFloriana Maria FarinaMichela CasellaFabio CattaneoValentina CattoMattia ChiesaIlaria StadiottiSilvia BrambillaAntonio Dello RussoCorrado CarbucicchioGiulia VettorDaniela RiggioMaria Teresa SandriAndrea BarbutiGianluca VernilloManuela MuratoriMatteo Dal FerroGianfranco SinagraSilvia MoimasMauro GiaccaGualtiero Ivanoe ColomboGiulio PompilioClaudio TondoPublished in: Scientific reports (2017)
Diagnosis of Arrhythmogenic CardioMyopathy (ACM) is challenging and often late after disease onset. No circulating biomarkers are available to date. Given their involvement in several cardiovascular diseases, plasma microRNAs warranted investigation as potential non-invasive diagnostic tools in ACM. We sought to identify circulating microRNAs differentially expressed in ACM with respect to Healthy Controls (HC) and Idiopathic Ventricular Tachycardia patients (IVT), often in differential diagnosis. ACM and HC subjects were screened for plasmatic expression of 377 microRNAs and validation was performed in 36 ACM, 53 HC, 21 IVT. Variable importance in data partition was estimated through Random Forest analysis and accuracy by Receiver Operating Curves. Plasmatic miR-320a showed 0.53 ± 0.04 fold expression difference in ACM vs. HC (p < 0.01). A similar trend was observed when comparing ACM (n = 13) and HC (n = 17) with athletic lifestyle, a ACM precipitating factor. Importantly, ACM patients miR-320a showed 0.78 ± 0.05 fold expression change vs. IVT (p = 0.03). When compared to non-invasive ACM diagnostic parameters, miR-320a ranked highly in discriminating ACM vs. IVT and it increased their accuracy. Finally, miR-320a expression did not correlate with ACM severity. Our data suggest that miR-320a may be considered a novel potential biomarker of ACM, specifically useful in ACM vs. IVT differentiation.
Keyphrases
- long non coding rna
- cell proliferation
- poor prognosis
- long noncoding rna
- end stage renal disease
- cardiovascular disease
- heart failure
- ejection fraction
- newly diagnosed
- chronic kidney disease
- prognostic factors
- binding protein
- type diabetes
- metabolic syndrome
- risk assessment
- climate change
- machine learning
- electronic health record
- patient reported
- cardiovascular risk factors
- human health
- cardiovascular events