microRNA‐based predictor for diagnosis of frontotemporal dementia

Abstract

AbstractAimsThis study aimed to explore the non‐linear relationships between cell‐free microRNAs (miRNAs) and their contribution to prediction of Frontotemporal dementia (FTD), an early onset dementia that is clinically heterogeneous, and too often suffers from delayed diagnosis.MethodsWe initially studied a training cohort of 219 subjects (135 FTD and 84 non‐neurodegenerative controls) and then validated the results in a cohort of 74 subjects (33 FTD and 41 controls).ResultsOn the basis of cell‐free plasma miRNA profiling by next generation sequencing and machine learning approaches, we develop a non‐linear prediction model that accurately distinguishes FTD from non‐neurodegenerative controls in ~90% of cases.ConclusionsThe fascinating potential of diagnostic miRNA biomarkers might enable early‐stage detection and a cost‐effective screening approach for clinical trials that can facilitate drug development.