Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by classic motor symptoms such as tremor, bradykinesia, rigidity, and postural instability as well as several non-motor symptoms. The heterogenous nature of PD has increased interest in classifying patients into subtypes based on clinical and/or pathologic features. This approach might allow for personalized therapies ranging from non-medical interventions to disease modifying therapies. As the field continues to advance, PD can be classified into simple motor, non-motor, or genetic subtypes among many others, though more complex subtypes have emerged because of artificial intelligence (AI) and machine learning (ML) systems. Herein, the authors describe the current state of subtyping in PD and the effects of subtyping on the development of personalized PD treatment strategies. The article was based on a literature search using PubMed to identify relevant peer-reviewed articles on PD subtypes and treatment strategies. Subtyping PD effectively may allow for the development of patient-specific treatment regimens, disease prediction strategies, and improved clinical trial designs, though limitations exist. Future investigations should aim to provide more robust subtyping criteria that allows for disease fluidity.
Hey et al. (Mon,) studied this question.