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REVIEW article
Front. Neurol.
Sec. Movement Disorders
Volume 15 - 2024 |
doi: 10.3389/fneur.2024.1460576
Simple biomarkers to distinguish Parkinson's disease from its mimics in clinical practice: a comprehensive review and future directions
Provisionally accepted- 1 Institute of Neurology, University Magna Graecia, Catanzaro, Italy
- 2 Department of Medical, Surgical Sciences and Advanced Technologies G.F. Ingrassia, University of Catania, Catania, Sicily, Italy
- 3 Neuroscience Research Center, University Magna Graecia, Catanzaro, Italy
In the last few years, a plethora of biomarkers have been proposed for the differentiation of Parkinson's disease (PD) from its mimics. Most of them consist of complex measures, often based on expensive technology, not easily employed outside research centers. MRI measures have been widely used to differentiate between PD and other parkinsonism. However, these measurements were often performed manually on small brain areas in small patient cohorts with intra-and inter-rater variability. The aim of the current review is to provide a comprehensive and updated overview of the literature on biomarkers commonly used to differentiate PD from its mimics (including parkinsonism and tremor syndromes), focusing on parameters derived by simple qualitative or quantitative measurements that can be used in routine practice. Several electrophysiological, sonographic and MRI biomarkers have shown promising results, including the blink-reflex recovery cycle, tremor analysis, sonographic or MRI assessment of substantia nigra, and several qualitative MRI signs or simple linear measures to be directly performed on MR images. The most significant issue is that most studies have been conducted on small patient cohorts from a single center, with limited reproducibility of the findings. Future studies should be carried out on larger international cohorts of patients to ensure generalizability. Moreover, research on simple biomarkers should seek measurements to differentiate patients with different diseases but similar clinical phenotypes, distinguish subtypes of the same disease, assess disease progression, and correlate biomarkers with pathological data. An even more important goal would be to predict the disease in the preclinical phase.
Keywords: Parkinson's disease, biomarkers, clinical practice, Electrophysiology, MRI
Received: 06 Jul 2024; Accepted: 09 Sep 2024.
Copyright: © 2024 Quattrone, Zappia and Quattrone. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Aldo Quattrone, Neuroscience Research Center, University Magna Graecia, Catanzaro, Italy
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