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Updated: Jul 26, 2025
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
microRNA-based predictor for diagnosis of frontotemporal dementia
Iddo Magen1,2, Nancy-Sarah Yacovzada1,2, Jason D Warren3
1Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
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.
