Parkinson's Progression Markers Initiative: A Milestone-Based Strategy to Monitor Parkinson's Disease Progression

A predictive model for longitudinal cognitive subtypes in Parkinson's disease

BACKGROUND

Longitudinal cognitive changes in Parkinson's disease (PD) exhibit considerable heterogeneity.Predicting cognitive trajectories in early PD patients can improve prognostic counseling and guide clinical trials.

METHODS

This study included 337 early PD patients with 6-year follow-up in the Parkinson's Progression Markers Initiative (PPMI) database.Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) to identify subtypes of longitudinal cognitive trajectories, and a nomogram predictive model was constructed using baseline clinical variables.

RESULTS

The 337 PD patients had a mean age of 61.0 years, mean disease duration of 0.55 years, and mean MoCA score of 27.1 points. Latent class mixed models (LCMM) identified two longitudinal cognitive subtypes: cognitive stable (276 cases, 81.9%) and cognitivel deteriorating (61 cases, 18.1%). The cognitively deteriorating subtype presented poorer baseline cognition, older age, and more severe motor and non-motor symptoms. On biomarkers, the cognitively deteriorating subtype revealed higher serum NFL levels and lower mean striatum DAT uptake. Six baseline clinical variables (age, Letter Number Sequencing score, Symbol Digit Modalities Test score, Benton Judgment of Line Orientation Test score, Hopkins Verbal Learning Test-Revised score, and REM Sleep Behavior Disorder) were selected to construct the nomogram predictive model which achieved an AUC of 0.92.The calibration curve demonstrated high consistency between predicted and observed probabilities.The predictive model has potential utility in disease-modifying clinical trials by pre-screening patients at high risk for cognitive deterioration.

CONCLUSION

This study identified two longitudinal cognitive subtypes: cognitive stable and cognitive deterioration within 6-year follow-up, and eighteen percent of early PD patients shared the cognitive deterioration subtype The predictive model, incorporating six baseline variables could estimate the risk of longitudinal cognitive deterioration in PD.

Neuronal α-Synuclein Disease Stage Progression over 5 Years

BACKGROUND

Neuronal α-synuclein disease (NSD) is defined by the presence of an in vivo biomarker of neuronal alpha-synuclein (n-asyn) pathology. The NSD integrated staging system (NSD-ISS) for research describes progression across the disease continuum as stages 0 to 6.

OBJECTIVE

The aim was to assess 5-year longitudinal change in NSD-ISS in early disease.

METHODS

Analysis included a subset of participants from the Parkinson's Progression Markers Initiative (PPMI) enrolled before 2020 as Parkinson's disease (PD) patients, prodromal PD patients, or healthy controls (HC) who met NSD criteria. Staging was defined based on biomarkers of n-asyn and dopaminergic dysfunction in early stages, clinical features, and severity of functional impairment in stages 3 to 6. Stages were determined annually for 5 years.

RESULTS

Of 576 NSD participants, 494 were enrolled as PD patients, 74 prodromal PD patients, and 8 HCs. At baseline, 24% of participants were stage 2B, 56% Stage 3, 13% stage 4, and less than 5% in other stages. At year 5, the respective percentages for stages 2B to 4 were 11%, 50%, and 34%, indicating progression through NSD stages. Progression was driven by functional impairment in the predominantly motor domain (95%) for stage 2B to 3, increasing degree of nonmotor dysfunction for stages 3 to 4 (46%), and a combination of domains for stages 4 to 5. Initiation of dopaminergic medications led to stage regression in 8% of participants in Stage 3 but 41% in stage 4.

CONCLUSIONS

Our analysis supports the utility of NSD-ISS in defining the stages of disease progression, at least in the early clinical and prodromal stages (2B, 3, or 4), suggesting the value of NSD-ISS as a potential research tool for drug development. Further research involving preclinical cohorts is a crucial next step. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A review of AI-based radiogenomics in neurodegenerative disease

Neurodegenerative diseases are chronic, progressive conditions that cause irreversible damage to the nervous system, particularly in aging populations. Early diagnosis is a critical challenge, as these diseases often develop slowly and without clear symptoms until significant damage has occurred. Recent advances in radiomics and genomics have provided valuable insights into the mechanisms of these diseases by identifying specific imaging features and genomic patterns. Radiogenomics enhances diagnostic capabilities by linking genomics with imaging phenotypes, offering a more comprehensive understanding of disease progression. The growing field of artificial intelligence (AI), including machine learning and deep learning, opens new opportunities for improving the accuracy and timeliness of these diagnoses. This review examines the application of AI-based radiogenomics in neurodegenerative diseases, summarizing key model designs, performance metrics, publicly available data resources, significant findings, and future research directions. It provides a starting point and guidance for those seeking to explore this emerging area of study.

The α-synuclein seed amplification assay: Interpreting a test of Parkinson's pathology

The α-synuclein seed amplification assay (αSyn-SAA) sensitively detects Lewy pathology, the amyloid state of α-synuclein, in the cerebrospinal fluid (CSF) of patients with Parkinson's disease (PD). The αSyn-SAA harnesses the physics of seeding, whereby a superconcentrated solution of recombinant α-synuclein lowers the thermodynamic threshold (nucleation barrier) for aggregated α-synuclein to act as a nucleation catalyst ("seed") to trigger the precipitation (nucleation) of monomeric α-synuclein into pathology. This laboratory setup increases the signal for identifying a catalyst if one is present in the tissue examined. The result is binary: positive, meaning precipitation occurred, and a catalyst is present, or negative, meaning no precipitation, therefore no catalyst. Since protein precipitation via seeding can only occur at a concentration many-fold higher than the human brain, laboratory-elicited seeding does not mean human brain seeding. We suggest that a positive αSyn-SAA reveals the presence of pathological α-synuclein but not the underlying etiology for the precipitation of monomeric α-synuclein into its pathological form. Thus, a positive αSyn-SAA supports a clinical diagnosis of PD but cannot inform disease pathogenesis, ascertain severity, predict the rate of progression, define biology or biological subtypes, or monitor treatment response.

Association of motor subtype and tremor type with Parkinson's disease progression: An exploratory longitudinal analysis

BackgroundParkinson's disease (PD) is a neurodegenerative disorder with heterogenous symptoms and progression rates. Some studies have classifying PD into tremor-dominant and non-tremor-dominant PD (TD-PD and Non-TD-PD), finding that TD-PD tend to have a better prognosis, slower disease progression, and lower pathological burden compared to Non-TD-PD. However, this classification does not consider the specific types of tremors, even though recent studies have shown that different types of tremors in PD might have distinct underlying mechanism.ObjectiveData from 517 de novo drug-naïve PD patients was analyzed.MethodsSurvival analysis was carried out including motor subtypes, rest tremor presence, kinetic tremor presence, postural tremor presence, as well as the instability of tremor presence or motor subtypes as predictors. Occurrence of 6 outcomes, including motor and non-motor milestones at follow-up, were used as the time-to-event.ResultsBoth TD-PD subtype and rest tremor presence was associated with slower PD progression, while kinetic tremor presence and postural tremor presence, especially kinetic tremor presence, was associated with a faster one.ConclusionsOur study suggests different types of tremors are associated with distinct PD prognoses, indicating potential differences in underlying mechanisms. Further investigation is warranted to elucidate the specific mechanisms underlying different types of tremors in PD and to explain their relationship to disease prognosis.

Digital Outcomes as Biomarkers of Disease Progression in Early Parkinson's Disease: A Systematic Review

Outcomes derived from digital health technologies (DHTs) are promising candidate markers for monitoring Parkinson's disease (PD) progression. They have the potential to represent a significant shift in clinical research and therapeutic development in PD. However, their ability to track disease progression is yet to be established. This systematic review aimed to identify digital biomarkers capable of tracking early PD progression (disease duration <5 years) by reviewing longitudinal studies (minimum follow-up of 6 months). We evaluated study design and quality, population features, reported DHTs and their performance to track progression. Of 1507 records screened, 15 studies were selected, published between 2009 and 2023, with the majority coming from the last 5 years. Of the 15, 11 were observational and four were interventional trials (follow-up range: 6-60 months). Twelve different DHTs were used (8 required active tests, 8 in-hospital use), capturing features related to motor function and daily activities, including five DHTs focused on gait/posture. Rating scales were used as comparators in all but one study. Three DHTs detected longitudinal changes when scales did not, with one study showing larger effect sizes for change over time of selected DHT features compared to rating scales. Four studies showed longitudinal correlations among DHT features and rating scales. Preliminary promising data suggest that DHT-derived outcomes may help reduce sample sizes in disease-modifying trials. There is a need to standardize study methodologies and facilitate data sharing to confirm these results and further validate the sensitivity of DHTs to track disease progression in PD. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The Impact of the Blood-Brain Barrier and Its Dysfunction in Parkinson's Disease: Contributions to Pathogenesis and Progression

Parkinson's disease (PD) is a brain disorder in which neuronal cells responsible for the release of dopamine, a neurotransmitter that controls movement, are degenerated or impaired in the substantia nigra and basal ganglia. The disease typically affects people over the age of 5 and presents with a variety of motor and nonmotor dysfunctions, which are unique to each person. The impairment of the blood-brain barrier (BBB) and blood retinal barrier (BRB) due to age-related causes such as weakness of tight junctions or rare genetic factors allows several metabolic intermediates to reach and accumulate inside neurons such as Lewy bodies and α-synuclein, disrupting neuronal homeostasis and leading to genetic and epigenetic changes, e.g., damage to the DNA repair system. This perspective highlights the importance of blood barriers, such as the BBB and BRB, in the progression of PD, as the aggregation of Lewy bodies and α-synuclein disrupts neuronal homeostasis. Genetic and epigenetic factors, neuroinflammation, oxidative stress, and mitochondrial dysfunction play crucial roles in the progression of the disease. The implications of these findings are significant; identifying synaptic dysfunction could lead to earlier diagnosis and treatment, while developing targeted therapies focused on preserving synaptic function may slow or halt disease progression. Understanding the various genetic forms of PD could enable more personalized medicine approaches, and using patient-derived midbrain neurons for research may improve the accuracy of PD models due to the implications of an impaired BBB.

Animal models of Long Covid: A hit-and-run disease

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2) pandemic has caused more than 7 million deaths globally. Despite the presence of infection- and vaccine-induced immunity, SARS-CoV-2 infections remain a major global health concern because of the emergence of SARS-CoV-2 variants that can cause severe acute coronavirus disease 2019 (COVID-19) or enhance Long Covid disease phenotypes. About 5 to 10% of SARS-CoV-2-infected individuals develop Long Covid, which, similar to acute COVID 19, often affects the lung. However, Long Covid can also affect other peripheral organs, especially the brain. The causal relationships between acute disease phenotypes, long-term symptoms, and involvement of multiple organ systems remain elusive, and animal model systems mimicking both acute and post-acute phases are imperative. Here, we review the current state of Long Covid animal models, including current and possible future applications.

Parkinson's Disease Mild Cognitive Impairment with MRI evidence of Cholinergic Nucleus 4 Degeneration: A New Subtype?

Subtyping Parkinson's disease with mild cognitive impairment (PD-MCI) could improve clinical trial design and personalized treatments. Cholinergic nucleus 4 (Ch4) volume has been linked to cognitive impairment severity and future decline in PD. This study investigates whether PD-MCI patients with MRI evidence of Ch4 degeneration have distinct clinical profiles and cognitive trajectories. Baseline MRI scans of 148 PD-MCI participants from the Parkinson's Progression Markers Initiative (PPMI) were analyzed. Patients with low Ch4 grey matter density (GMD) had worse motor, autonomic, and olfactory symptoms, and were more likely to belong to the diffuse malignant PD subtype (51.6% vs. 23.4%; P < 0.01). They also had faster progression to cognitive milestones (P = 0.0046). These findings identify PD-MCI with low Ch4 as a distinct subtype with more severe symptoms and faster cognitive decline, highlighting the importance of considering this group in PD-MCI clinical trials, particularly for cholinergic therapies.

The association of motor reserve and clinical progression in Parkinson's disease

OBJECTIVE

To explore the association of motor reserve (MR) and clinical progression in Parkinson's disease.

METHODS

This longitudinal study using data from the Parkinson's progression markers initiative. Patients with de novo PD who underwent dopamine transporter scans at baseline and finished at least five years clinical follow-up assessments (including motor, cognitive, and non-motor symptoms) were included. The individual MR of PD patients were estimated based on initial motor deficits and striatal dopamine depletion using a residual model. Linear mixed-effects models (LME) were performed to examine the associations of baseline MR and clinical progression.

RESULTS

A total of 303 de novo PD patients were included and the mean follow-up time was 8.95 years. Results of LME models revealed that the baseline MR was associated with motor, cognitive, and non-motor symptoms in PD patients. There was a significant interaction between MR and disease duration for longitudinal changes in motor (p < 0.001), cognitive (p = 0.028) and depression symptoms (p = 0.014). PD patients with lower MR had a more rapid progression to postural instability and cognitive impairment compared with those with higher MR (p = 0.002 and p = 0.001, respectively).

CONCLUSIONS

The baseline MR of PD patients were associated with motor and non-motor symptoms and can predicted disease prognosis, suggesting that the initial MR in PD would be associated with the individual's capacity to cope with neurodegenerative process as well as comprehensive prognosis.

Neurotrophic factors for Parkinson's disease: Current status, progress, and remaining questions. Conclusions from a 2023 workshop

In 2023, a workshop was organized by the UK charity Cure Parkinson's with The Michael J Fox Foundation for Parkinson's Research and Parkinson's UK to review the field of growth factors (GFs) for Parkinson's disease (PD). This was a follow up to a previous meeting held in 2019.1 This 2023 workshop reviewed new relevant data that has emerged in the intervening 4 years around the development of new GFs and better models for studying them including the merit of combining treatments as well as therapies that can be modulated. We also discussed new insights into GF delivery and trial design that have emerged from the analyses of completed GDNF trials, including the patient voice, as well as the recently completed CDNF trial.2 We then concluded with our recommendations on how GF studies in PD should develop going forward.

Health care utilization at the end of life in Parkinson's disease: a population-based register study

BACKGROUND

Knowledge of health care utilization at the end of life in Parkinson's disease (PD) is sparse. This study aims to investigate end of life health care utilization, characterized by emergency room (ER) visits, receipt of specialized palliative care (SPC), and acute hospital deaths in a Swedish population-based PD cohort.

METHODS

We conducted a retrospective cohort study on deceased patients (≥ 18 years) with a PD diagnosis during their last year of life (n = 922), based on health care-provider data from Region Stockholm´s data warehouse, for the study period 2015-2021. Univariable and multivariable logistic regression analyses tested associations and adjusted Odds ratios (aORs) were calculated.

RESULTS

During the last month of life, approx. half of the cohort had emergency room (ER) visits and risk of frailty (measured by Hospital Frailty Risk Score) significantly predicted these visits (aOR, 3.90 (2.75-5.55)). In total, 120 people (13%) received SPC during their last three months of life, which positively associated with risk for frailty, (aOR, 2.65 (1.43-4.94, p = 0.002). In total, 284 people (31%) died in acute hospital settings. Among community-dwellers, male gender and frailty were strongly associated with acute hospital deaths (aOR, 1.90 (1.15-3.13, p = 0.01) and 3.70 (1.96-6.98, p < 0.0001)).

CONCLUSIONS

Rates of ER visits at end of life and hospital deaths were relatively high in this population-based cohort. Considering a high disease burden, referral to SPC at end of life was relatively low. Sex-specific disparities in health care utilization are apparent. Identifying people with high risk for frailty could assist the planning of optimal end-of-life care for people with PD.

A prediction model for the walking and balance milestone in Parkinson's disease

BACKGROUND

Walking and balance impairments, represented by freezing of gait and falls, are significant contributors to disability in advanced Parkinson's disease (PD) patients. However, the composite measure of the Walking and Balance Milestone (WBMS) has not been thoroughly investigated.

METHODS

This study included 606 early-stage PD patients from the Parkinson's Progression Markers Initiative (PPMI) database, with a disease duration of less than 2 years and no WBMS at baseline. Patients were divided into a model development cohort (70 %) and a validation cohort (30 %) according to the enrollment site. Longitudinal follow-up data over a period of 12 years were analyzed.

RESULTS

Among all 606 patients, the estimated probability of being WBMS-free at the 5th and 10th year was 88 % and 60 %, respectively. Five clinical variables (Age, Symbol Digit Modalities Test (SDMT), postural instability and gait difficulty (PIGD) score, Movement Disorder Society-Unified Parkinson's Disease Rating Scale Part I (MDS-UPDRS-I) score, and REM Sleep Behavior Disorder (RBD) were used to construct the Cox predictive model. The C-index of the model was 0.75 in the development cohort and 0.76 in the validation cohort. By optimizing the PIGD and MDS-UPDRS-I variables, an easy-to-use model was achieved with comparable predictive performance.

CONCLUSION

A predictive model based on five baseline clinical measures (Age, SDMT, PIGD score, MDS-UPDRS-I score, RBD) could effectively estimate the risk of the WBMS in early PD patients. This model is valuable for prognostic counseling and clinical intervention trials for gait and balance impairment.

Disease progression subtypes of Parkinson's disease based on milestone events

BACKGROUND

Parkinson's disease (PD) demonstrates considerable heterogeneity in the manifestation of clinical symptoms and disease progression. Recently, six clinical milestones have been proposed to evaluate disease severity in PD. However, the identification of PD progression subtypes based on these milestone events has not yet been performed.

METHODS

Latent class analysis (LCA) was employed to identify subtypes of PD progression based on the timing of the first occurrence of six milestones within a 6-year follow-up period in Parkinson's Progression Markers Initiative (PPMI) database.

RESULTS

The study cohort consisted of 354 early PD patients, of whom 42.9% experienced at least one milestone within six years. LCA identified two distinct subtypes of PD progression: slow progression (83%) and rapid progression (17%). The total number of milestones over six years was significantly higher in the rapid progression subtype compared to the slow progression subtype (median: 3.00 vs. 0.00, p < 0.001). At baseline, the rapid progression subtype, compared to the slow progression subtype, was characterized by an older age at onset and more severe motor and non-motor symptoms. On biomarkers, the rapid progression subtype demonstrated elevated CSF p-tau and serum NFL, but decreased mean striatal DAT uptake. Five clinical variables (age, SDMT score, MDS-UPDRS I score, MDS-UPDRS II + III scores, and RBD) were selected to construct the predictive model. The original predictive model achieved an AUC of 0.82. In internal validation using bootstrap resampling, the model achieved an AUC of 0.82, with a 95%CI ranging from 0.76 to 0.87. The model's performance was acceptable regarding both calibration and clinical utility.

CONCLUSION

Approximately 17% of early PD patients exhibited the rapid progression subtype, characterized by the occurrence of more and earlier-onset milestones. The nomogram predictive model, incorporating five baseline clinical variables (age, SDMT score, MDS-UPDRS I score, MDS-UPDRS II + III scores, RBD), serves as a valuable tool for prognostic counseling and patient selection in PD clinical trials.

Neuronal alpha-Synuclein Disease integrated staging system performance in PPMI, PASADENA, and SPARK baseline cohorts

The Neuronal alpha-Synuclein Disease (NSD) biological definition and Integrated Staging System (NSD-ISS) provide a research framework to identify individuals with Lewy body pathology and stage them based on underlying biology and increasing degree of functional impairment. Utilizing data from the PPMI, PASADENA, and SPARK studies, we developed and applied biologic and clinical data-informed definitions for the NSD-ISS across the disease continuum. Individuals enrolled as Parkinson's disease, Prodromal, or Healthy Controls were defined and staged based on biological, clinical, and functional anchors at baseline. Across the three studies 1741 participants had SAA data and of these 1030 (59%) were S+ consistent with NSD. Among sporadic PD, 683/736 (93%) were NSD, and the distribution for Stages 2B, 3, and 4 was 25%, 63%, and 9%, respectively. Median (95% CI) time to developing a clinically meaningful outcome was 8.3 (6.2, 10.1), 5.9 (4.1, 6.0), and 2.4 (1.0, 4.0) years for baseline stage 2B, 3, and 4, respectively. We propose pilot biologic and clinical anchors for NSD-ISS. Our results highlight the baseline heterogeneity of individuals currently defined as early PD. Baseline stage predicts time to progression to clinically meaningful milestones. Further research on validation of the anchors in longitudinal cohorts is necessary.

Neuronal alpha-Synuclein Disease Integrated Staging System performance in PPMI, PASADENA, and SPARK baseline cohorts

The Neuronal alpha-Synuclein Disease (NSD) biological definition and Integrated Staging System (NSD-ISS) provide a research framework to identify individuals with Lewy body pathology and stage them based on underlying biology and increasing degree of functional impairment. Utilizing data from the PPMI, PASADENA and SPARK studies, we developed and applied biologic and clinical data-informed definitions for the NSD-ISS across the disease continuum. Individuals enrolled as Parkinson's disease, Prodromal, or Healthy Controls were defined and staged based on biological, clinical, and functional anchors at baseline. Across the three studies 1,741 participants had SAA data and of these 1,030 (59%) were S+ consistent with NSD. Among sporadic PD, 683/736 (93%) were NSD, and the distribution for Stages 2B, 3, and 4 was 25%, 63%, and 9%, respectively. Median (95% CI) time to developing a clinically meaningful outcome was 8.3 (6.2, 10.1), 5.9 (4.1, 6.0), and 2.4 (1.0, 4.0) years for baseline stage 2B, 3, and 4, respectively. We propose pilot biologic and clinical anchors for NSD-ISS. Our results highlight the baseline heterogeneity of individuals currently defined as early PD. Baseline stage predicts time to progression to clinically meaningful milestones. Further research on validation of the anchors in longitudinal cohorts is necessary.

Loss of monomeric alpha-synuclein (synucleinopenia) and the origin of Parkinson's disease

These facts argue against the gain-of-function synucleinopathy hypothesis, which proposes that Lewy pathology causes Parkinson's disease: (1) most brains from people without neurological symptoms have multiple pathologies; (2) neither pathology type nor distribution correlate with disease severity or progression in Parkinson's disease; (3) aggregated α-synuclein in the form of Lewy bodies is not a space-occupying lesion but the insoluble fraction of its precursor, soluble monomeric α-synuclein; (4) pathology spread is passive, occurring by irreversible nucleation, not active replication; and (5) low cerebrospinal fluid α-synuclein levels predict brain atrophy and clinical disease progression. The transformation of α-synuclein into Lewy pathology may occur as a response to biological, toxic, or infectious stressors whose persistence perpetuates the nucleation process, depleting normal α-synuclein and eventually leading to Parkinson's symptoms from neuronal death. We propose testing the loss-of-function synucleinopenia hypothesis by evaluating the clinical and neurodegenerative rescue effect of replenishing the levels of monomeric α-synuclein.

Associations of Multimorbidity with Cerebrospinal Fluid Biomarkers for Neurodegenerative Disorders in Early Parkinson's Disease: A Crosssectional and Longitudinal Study

OBJECT

The study aims to determine whether multimorbidity status is associated with cerebrospinal fluid (CSF) biomarkers for neurodegenerative disorders.

METHODS

A total of 827 patients were enrolled from the Parkinson's Progression Markers Initiative (PPMI) database, including 638 patients with early-stage Parkinson's disease (PD) and 189 healthy controls (HCs). Multimorbidity status was evaluated based on the count of long-term conditions (LTCs) and the multimorbidity pattern. Using linear regression models, cross-sectional and longitudinal analyses were conducted to assess the associations of multimorbidity status with CSF biomarkers for neurodegenerative disorders, including α-synuclein (αSyn), amyloid-β42 (Aβ42), total tau (t-tau), phosphorylated tau (p-tau), glial fibrillary acidic protein (GFAP), and neurofilament light chain protein (NfL).

RESULTS

At baseline, the CSF t-tau (p = 0.010), p-tau (p = 0.034), and NfL (p = 0.049) levels showed significant differences across the three categories of LTC counts. In the longitudinal analysis, the presence of LTCs was associated with lower Aβ42 (β < -0.001, p = 0.020), and higher t-tau (β = 0.007, p = 0.026), GFAP (β = 0.013, p = 0.022) and NfL (β = 0.020, p = 0.012); Participants with tumor/musculoskeletal/mental disorders showed higher CSF levels of t-tau (β = 0.016, p = 0.011) and p-tau (β = 0.032, p = 0.044) than those without multimorbidity.

CONCLUSION

Multimorbidity, especially severe multimorbidity and the pattern of mental/musculoskeletal/ tumor disorders, was associated with CSF biomarkers for neurodegenerative disorders in early-stage PD patients, suggesting that multimorbidity might play a crucial role in aggravating neuronal damage in neurodegenerative diseases.

Pharmacotherapy for Disease Modification in Early Parkinson's Disease: How Early Should We Be?

Slowing or halting progression continues to be a major unmet medical need in Parkinson's disease (PD). Numerous trials over the past decades have tested a broad range of interventions without ultimate success. There are many potential reasons for this failure and much debate has focused on the need to test 'disease-modifying' candidate drugs in the earliest stages of disease. While generally accepted as a rational approach, it is also associated with significant challenges around the selection of trial populations as well as trial outcomes and durations. From a health care perspective, intervening even earlier and before at-risk subjects have gone on to develop overt clinical disease is at the heart of preventive medicine. Recent attempts to develop a framework for a biological definition of PD are aiming to enable 'preclinical' and subtype-specific diagnostic approaches. The present review addresses past efforts towards disease-modification, including drug targets and reasons for failure, as well as novel targets that are currently being explored in disease-modification trials in early established PD. The new biological definitions of PD may offer new opportunities to intervene even earlier. We critically discuss the potential and challenges around planning 'disease-prevention' trials in subjects with biologically defined 'preclinical' or prodromal PD.