Magen, Iddo;
Yacovzada, Nancy-Sarah;
Warren, Jason D;
Heller, Carolin;
Swift, Imogen;
Bobeva, Yoana;
Malaspina, Andrea;
... Hornstein, Eran; + view all
(2023)
microRNA-based predictor for diagnosis of frontotemporal dementia.
Neuropathology and Applied Neurobiology
, 49
(4)
, Article e12916. 10.1111/nan.12916.
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microRNA based predictor for diagnosis of frontotemporal dementia.pdf - Accepted Version Access restricted to UCL open access staff until 12 July 2024. Download (1MB) |
Abstract
Aims: 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. Methods: 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). Results: 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. Conclusions: 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.
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