Prodromal Parkinson disease subtypes - key to understanding heterogeneity

In Parkinson disease (PD), pathological processes and neurodegeneration begin long before the cardinal motor symptoms develop and enable clinical diagnosis. In this prodromal phase, risk and prodromal markers can be used to identify individuals who are likely to develop PD, as in the recently updated International Parkinson and Movement Disorders Society research criteria for prodromal PD. However, increasing evidence suggests that clinical and prodromal PD are heterogeneous, and can be classified into subtypes with different clinical manifestations, pathomechanisms and patterns of spatial and temporal progression in the CNS and PNS. Genetic, pathological and imaging markers, as well as motor and non-motor symptoms, might define prodromal subtypes of PD. Moreover, concomitant pathology or other factors, including amyloid-beta and tau pathology, age and environmental factors, can cause variability in prodromal PD. Patients with REM sleep behaviour disorder (RBD) exhibit distinct patterns of alpha-synuclein pathology propagation and might indicate a body-first subtype rather than a brain-first subtype. Identification of prodromal PD subtypes and a full understanding of variability at this stage of the disease is crucial for early and accurate diagnosis and for targeting of neuroprotective interventions to ensure efficacy. In this Review, Berg et al. summarize current understanding of prodromal Parkinson disease and consider the prodrome in the context of the clinical and pathological heterogeneity of the disease. They explore the possibility that prodromal Parkinson disease can be classified into subtypes.

Automated summary

Parkinson's disease begins its pathological processes and neurodegeneration long before clinical diagnosis, allowing for identification of individuals likely to develop the disease through risk and prodromal markers. Heterogeneity in clinical and prodromal PD suggests that subtypes exist, differentiated by clinical manifestations, pathomechanisms, and progression patterns. Understanding this variability is crucial for early and accurate diagnosis, as well as for targeting neuroprotective interventions effectively.