microRNA-based predictor for diagnosis of frontotemporal dementia.

This 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. We 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). On 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. The 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. © 2023 British Neuropathological Society.

Citation

Iddo Magen, Nancy-Sarah Yacovzada, Jason D Warren, Carolin Heller, Imogen Swift, Yoana Bobeva, Andrea Malaspina, Jonathan D Rohrer, Pietro Fratta, Eran Hornstein. microRNA-based predictor for diagnosis of frontotemporal dementia. Neuropathology and applied neurobiology. 2023 Aug;49(4):e12916

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PMID: 37317649

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