The commitment of Parkinson's Progression Markers Initiative participants to longitudinal comprehensive clinical and biomarker research assessment is key to its success in acquiring high quality data. As the study has evolved, it has become clear that return of research information to participants should be prioritized to provide participants with their data as they have consistently and reasonably requested. The Parkinson's Progression Markers Initiative is committed to responsible sharing of individual research information with study participants. Two initiatives dedicated to results disclosure were simultaneously implemented: the Return of Research Information program and the Randomized Disclosure Assessment in the Parkinson's At-Risk Cohort clinical trial. These are pioneering studies on research information sharing. These initiatives empower participants and will provide valuable insights on the impact that disclosure may have on participants and study data. ANN NEUROL 2026.

The creation and ongoing development of the myPPMI platform (see Stanley et al in this issue), has enabled the Parkinson's Progression Markers Initiative (PPMI) to expand our research efforts to acquire additional data, engage a large number of participants, and reduce participant burden to enable long-term follow-up. We now review specific virtual and remote studies and sub-studies including Found, PPMI Online, and PPMI Cognitive that PPMI has developed to enhance participant engagement and enable remote data collection. FOUND in PPMI was initiated before myPPMI and continues to serve as a model for remote participant engagement. FOUND maintains longitudinal contact, reducing study attrition, and preserving data continuity. PPMI Online, now part of myPPMI, enables low-burden, participant-reported data collection, reduces geographic barriers, and enables sub-studies of less common subgroups. Cognitive testing is another study within myPPMI to assess longitudinal cognition. myPPMI, a global web-based portal, introduces precision recruitment, real-time eligibility matching, and inclusive design. Together, these innovations enable remote and hybrid recruitment and study conduct, reduce logistical and economic barriers, and advance scalable, participant-centered research to transform the landscape of Parkinson's disease studies across populations. ANN NEUROL 2026.

To better understand the earliest stages of alpha-synucleinopathy, the Parkinson's Progression Markers Initiative (PPMI) has enrolled participants prior to the diagnosis of Parkinson's disease (PD) or dementia with Lewy Bodies (DLB). In this review, we describe lessons learned from prior enrollment and current strategies for PPMI eligibility. Severe hyposmia remains the strongest clinical predictor of aggregated synuclein as measured by a positive cerebrospinal fluid alpha-synuclein seed amplification assay (CSF aSyn SAA). CSF aSyn SAA is positive before dopamine transporter binding decreases, as measured by dopamine imaging. PPMI's adaptive eligibility criteria have enabled efficient identification of people in the early stage of neuronal synuclein disease defined by biomarkers alone and can inform future therapeutic studies. ANN NEUROL 2026.

Abstract Background Pathogenic variants in GCH1 have been associated with Parkinson’s disease (PD), but the clinical phenotype and longitudinal disease course of GCH1 -associated PD remain incompletely characterized. Objectives To characterize the genetic spectrum, clinical phenotype, and longitudinal progression of GCH1 -associated PD across multiple populations. Methods Whole-genome sequencing (WGS) and clinical exome sequencing (CES) data from the Global Parkinson’s Genetics Program (GP2) were analyzed together with unpublished and published GCH1-associated PD patients. Variant pathogenicity was classified according to ACMG criteria. Demographic, clinical, and longitudinal features were compared between GCH1 P/LP variant carriers and non-carrier PD patients; individuals with known pathogenic variants in PD-associated genes were excluded from both groups. Results In the GP2 cohort (PD, n=22,825; controls, n=4,453), 16 pathogenic or likely pathogenic (P/LP) GCH1 variants were identified in 58 individuals, including 54 PD patients, one control, and three individuals with other neurodegenerative phenotypes (two with progressive supranuclear palsy and one with dementia with Lewy bodies). In the pooled-ancestry WGS analysis, GCH1 P/LP variants were enriched in PD patients versus controls (0.267% vs 0.023%; OR=11.854; 95% CI=1.620-86.699; p =0.0006). Variant frequencies in PD patients ranged from 0.121% to 0.714% across ancestries. In the CES cohort, P/LP variants were identified in 0.201% of PD patients. After integrating GP2 with additional unpublished and published datasets, 119 GCH1-associated PD patients were analyzed. Compared with non-carriers, GCH1 P/LP variant carriers had earlier disease onset (53.7 ± 14.8 vs 59.2 ± 11.7 years; p =8.99×10 -5 ), lower levodopa equivalent daily dose requirements (467.5 ± 331.7 vs 680.3 ± 466.39mg/day; p =4.21×10 -8 ), and more frequent family history of PD (47.6% vs 19.9%; p =1.09×10 -8 ). Adjusted Cox models showed significant delayed progression to motor fluctuations (HR=0.32, 95% CI=0.16-0.62) and levodopa-induced dyskinesias (HR=0.51, 95% CI=0.30-0.87). Conclusion GCH1 pathogenic variants were associated with a clinically distinct phenotype characterized by earlier disease onset and slower progression of motor complications. These findings suggest that GCH1 genetic variants may serve as genetic biomarkers for patient stratification and prognosis in PD.

OBJECTIVE:To determine the impact of dopamine deficiency and isolated rapid eye movement (REM) sleep behavior disorder (iRBD) on cognitive performance in early neuronal α-synuclein disease (NSD) with hyposmia but without motor disability. METHODS:Using Parkinson's Progression Markers Initiative baseline data, cognitive performance was assessed with a cognitive summary score (CSS) derived from robust healthy control (HC) norms. Performance was examined for participants with hyposmia in early NSD-Integrated Staging System (NSD-ISS), either stage 2A (cerebrospinal fluid α-synuclein seed amplification assay [SAA]+, dopamine transporter scan [DaTscan]-) or 2B (SAA+, DaTscan+). RESULTS:Participants were stage 2A (n = 101), stage 2B (N = 227), and HCs (n = 158). Although stage 2 had intact Montreal Cognitive Assessment scores (mean [SD] = 27.0 [2.3]), stage 2A had a numerically worse CSS (z-score mean difference = 0.05, p = NS; effect size = 0.09) and stage 2B a statistically worse CSS (z-score mean difference = 0.23, p < 0.05; effect size = 0.40) compared with HCs. In stage 2A, hyposmia alone was associated with normal cognition, but those with comorbid iRBD had significantly worse cognition (z-score mean difference = 0.33, p < 0.05, effect size =0.50). In stage 2B, hyposmia alone had abnormal cognition (z-score mean difference = 0.18, p = 0.0078, effect size = 0.29), and superimposed iRBD had a statistically significant additive effect. INTERPRETATION:Using a novel CSS, we demonstrated that hyposmia is associated with cognitive deficits in prodromal NSD without motor disability, particularly when comorbid dopamine system impairment or comorbid iRBD is present. Therefore, it is critical to include and assess cognition at all stages when studying synuclein disease, even in the absence of motor disability. ANN NEUROL 2025;98:482-491.

Among LRRK2-associated parkinsonism cases with nigral degeneration, over two-thirds demonstrate evidence of pathologic alpha-synuclein, but many do not. Understanding the clinical phenotype and underlying biology in such individuals is critical for therapeutic development. Our objective was to compare clinical and biomarker features, and rate of progression over 4 years of follow-up, among LRRK2-associated parkinsonism cases with and without in vivo evidence of alpha-synuclein aggregates. Data were from the Parkinson's Progression Markers Initiative, a multicentre prospective cohort study. The sample included individuals diagnosed with Parkinson disease with pathogenic variants in LRRK2. Presence of CSF alpha-synuclein aggregation was assessed with seed amplification assay. A range of clinician- and patient-reported outcome assessments were administered. Biomarkers included dopamine transporter scan, CSF amyloid-beta1-42, total tau, phospho-tau181, urine bis(monoacylglycerol)phosphate levels and serum neurofilament light chain. Linear mixed-effects (LMMs) models examined differences in trajectory in CSF-negative and CSF-positive groups. A total of 148 LRRK2 parkinsonism cases (86% with G2019S variant), 46 negative and 102 positive for CSF alpha-synuclein seed amplification assay, were included. At baseline, the negative group was older than the positive group [median (inter-quartile range) 69.1 (65.2-72.3) versus 61.5 (55.6-66.9) years, P < 0.001] and a greater proportion were female [28 (61%) versus 43 (42%), P = 0.035]. Despite being older, the negative group had similar duration since diagnosis and similar motor rating scale [16 (11-23) versus 16 (10-22), P = 0.480] though lower levodopa equivalents. Only 13 (29%) of the negative group were hyposmic, compared with 75 (77%) of the positive group. The negative group, compared with the positive group, had higher per cent-expected putamenal dopamine transporter binding for their age and sex [0.36 (0.29-0.45) versus 0.26 (0.22-0.37), P < 0.001]. Serum neurofilament light chain was higher in the negative group compared with the positive group [17.10 (13.60-22.10) versus 10.50 (8.43-14.70) pg/mL; age-adjusted P-value = 0.013]. In terms of longitudinal change, the negative group remained stable in functional rating scale score in contrast to the positive group who had a significant increase (worsening) of 0.729 per year (P = 0.037), but no other differences in trajectory were found. Among individuals diagnosed with Parkinson disease with pathogenic variants in the LRRK2 gene, we found clinical and biomarker differences in cases without versus with in vivo evidence of CSF alpha-synuclein aggregates. LRRK2 parkinsonism cases without evidence of alpha-synuclein aggregates as a group exhibit less severe motor manifestations and decline. The underlying biology in LRRK2 parkinsonism cases without evidence of alpha-synuclein aggregates requires further investigation.

OBJECTIVES:Tools are needed to evaluate the risk of developing Parkinson disease (PD) in at-risk populations. In this study, we examine differences in alpha-synuclein seed amplification assay (αSyn-SAA) qualitative results and amplification parameters between nonmanifesting carriers (NMCs) of PD-related pathogenic variants, prodromal PD, and PD and the risk of developing a synucleinopathy in participants with prodromal PD. METHODS:Cross-sectional and longitudinal CSF αSyn-SAA results from participants in the Parkinson's Progression Markers Initiative were analyzed. αSyn-SAA positivity and amplification parameters (maximum fluorescence [Fmax], time-to-threshold [TTT], time-to-50% Fmax [T50], and area under the curve [AUC]) were compared between NMCs, participants with prodromal PD, and participants with PD, and their relationship with the likelihood of phenoconversion in participants with prodromal PD was investigated. RESULTS:Samples from 1,027 participants were analyzed (159 healthy controls [HCs], 247 NMCs, 96 participants with prodromal PD, and 525 participants with PD). TTT and T50 were faster, and AUC was higher in αSyn-SAA+ participants with prodromal PD and PD than αSyn-SAA+ NMCs and HC participants (Kruskal-Wallis χ2 = 4.15-13.96, p < 0.0002-0.04). Participants with prodromal PD with positive αSyn-SAA tests and faster TTT had higher rates of phenoconversion (log-rank p = 0.001 and log-rank test-for-trend p < 0.0001). There were no changes in 48 participants with prodromal PD with longitudinal assays. DISCUSSION:αSyn-SAA positivity and faster seed amplification are associated with a greater risk of developing PD in at-risk individuals and may aid in predicting phenoconversion.

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.

The study goal was to use a very large study cohort to establish normative data for the revised UPSIT (UPSIT-R) and to compare the resultant percentiles to those of the original UPSIT. A second study was performed to compare the performance of these two tests in a cohort of persons with and without Parkinson’s disease (PD). UPSIT-R percentiles were derived by age and sex in 16,972 volunteers. Non-parametric statistics were employed to compare the results of those with and without PD. UPSIT-R performance declined with increasing age; deficits were more pronounced in men than women. The magnitude of the difference between the original and revised test percentile scores differed by age and sex. Olfactory deficits in PD were confirmed on the UPSIT-R. This study provides normative data clinically useful for assessing the relative degree of dysfunction in persons 60 years of age and older using the UPSIT-R. Trial Registration Information: ClinicalTrials.gov NCT05065060 .

BACKGROUND:Cognitive impairment is common at all stages of Parkinson's disease (PD), but there is no consensus on which neuropsychological tests to use or how to interpret cognitive battery results. A cognitive summary score (CSS) combines the richness of a neuropsychological battery with the simplicity of a single score. OBJECTIVE:The objective of this study was to determine whether a CSS created using robust norming can detect early cognitive deficits in de novo, untreated PD. METHODS:Baseline cognitive data from PD participants and healthy control participants (HCs) in the Parkinson's Progression Markers Initiative were used to (1) create a robust HC subgroup without cognitive decline, (2) generate regression-based z scores for six cognitive measures using this subgroup, and (3) create a CSS by averaging all z scores. RESULTS:PD participants scored worse than HCs on all cognitive tests, with larger effects when compared with the robust HC subgroup rather than all HCs. Applying internally derived norms, the largest effects were for processing speed/working memory (Cohen's d = -0.55) and verbal episodic memory (Cohen's d = -0.48 and -0.52). Robust norming shifted PD performance from average (CSS z score = -0.01) to low average (CSS z score = -0.40), with a larger effect for the CSS (PD vs. robust HC subgroup; Cohen's d = -0.60) compared with individual tests. CONCLUSIONS:Patients with PD perform worse cognitively than HCs, particularly in processing speed and verbal memory. Robust norming increases effect sizes and decreases PD scores to expected levels. The CSS outperformed individual tests and may detect cognitive changes in early PD, making it a useful outcome measure in clinical research. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Summary: Background: Synuclein pathology in neurodegenerative diseases, such as Parkinson’s disease (PD) and Dementia with Lewy bodies (DLB), begins years before motor or cognitive symptoms arise. Alpha-Synuclein seed amplification assays (α-syn SAA) may detect aggregated synuclein before symptoms occur. Methods: Data from the Parkinson Associated Risk Syndrome Study (PARS) have shown that individuals with hyposmia, without motor or cognitive symptoms, are enriched for dopamine transporter imaging (DAT) deficit and are at high risk to develop clinical parkinsonism or related synucleinopathies. α-syn aggregates in CSF were measured in 100 PARS participants using α-syn SAA. Findings: CSF α-syn SAA was positive in 48% (34/71) of hyposmic compared to 4% (1/25) of normosmic PARS participants (relative risk, 11.97; 95% CI, 1.73–82.95). Among α-syn SAA positive hyposmics 65% remained without a DAT deficit for up to four years follow-up. α-syn SAA positive hyposmics were at higher risk of having DAT deficit (12 of 34) compared to α-syn SAA negative hyposmics (4 of 37; relative risk, 3.26; 95% CI, 1.16–9.16), and 7 of 12 α-syn SAA positive hyposmics with DAT deficit developed symptoms consistent with synucleinopathy. Interpretation: Approximately fifty percent of PARS participants with hyposmia, easily detected using simple, widely available tests, have synuclein pathology detected by α-syn SAA. Approximately, one third (12 of 34) α-syn SAA positive hyposmic individuals also demonstrate DAT deficit. This study suggests a framework to investigate screening paradigms for synuclein pathology that could lead to design of therapeutic prevention studies in individuals without symptoms. Funding: The study was funded by the U.S. Department of Defense, the Helen Graham Foundation and the Michael J. Fox Foundation for Parkinson's Research.

ABSTRACTBackgroundREM sleep behavior disorder (RBD) is an early manifestation of alpha-synucleinopathy in many cases. Dream enactment behavior (DEB), the clinical hallmark of RBD, has many etiologies and cannot be used alone to predict underlying alpha-synucleinopathy. We compared the proportion of people with alpha-synucleinopathy, as measured by CSF alpha-synuclein seed amplification assay (CSFasynSAA), between people with polysomnographic-confirmed RBD (RBD-PSG) and people who reported DEB on a questionnaire and were further selected with smell testing and DAT-SPECT.MethodsParticipants were enrolled in the Parkinson’s Progression Marker Initiative (PPMI) and ≥60 years old without a diagnosis of Parkinson’s disease. Participants had either RBD-PSG or self-reported DEB. Self-reported DEB participants had to have hyposmia (<10thpercentile for age/sex) and at least mild DAT-SPECT abnormality (<100% age/sex-expected). We compared CSFasynSAA between RBD-PSG and self-reported DEB with hyposmia (DEB+Hypos). RBD-PSG participants also underwent smell testing and DAT-SPECT; we determined the predictive value of these tests in RBD-PSG with regards to CSFasynSAA.ResultsCSFasynSAA was positive in 171/240 (71%) of RBD-PSG and %) 180/210 (86%) of DEB+Hypos participants. Among RBD-PSG, hyposmia strongly predicted CSFasynSAA+ (PPV: 92% [95% CI 87%-97%]). Smell identification was more accurate than DAT-SPECT in predicting CSFasynSAA+ in RBD-PSG (AUC for UPSIT: 0.89 [95% CI 0.84 – 0.94]; AUC for DAT-SPECT: 0.65 [95% CI 0.58 – 0.73]).ConclusionsSmell testing may be an effective and scalable method to identify people with alpha-synucleinopathy among those with self-reported DEB. Among individuals with RBD diagnosed by PSG, smell testing improved prediction of positive CSF alpha-synuclein biomarker.

OBJECTIVE:Remote identification of individuals with severe hyposmia may enable scalable recruitment of participants with underlying alpha-synuclein aggregation. We evaluated the performance of a staged screening paradigm using remote smell testing to enrich for abnormal dopamine transporter single-photon emission computed tomography imaging (DAT-SPECT) and alpha-synuclein aggregation. METHODS:The Parkinson's Progression Markers Initiative (PPMI) recruited participants for the prodromal cohort who were 60-years and older without a Parkinson's disease diagnosis. Participants were invited to complete a University of Pennsylvania Smell Identification Test (UPSIT) independently through an online portal. Hyposmic participants were invited to complete DAT-SPECT, which determined eligibility for enrollment in longitudinal assessments and further biomarker evaluation including cerebrospinal fluid alpha-synuclein seed amplification assay (aSynSAA). RESULTS:As of January 29, 2024, 49,843 participants were sent an UPSIT and 31,293 (63%) completed it. Of UPSIT completers, 8,301 (27%) scored <15th percentile. Of 1,546 who completed DAT-SPECT, 1,060 (69%) had DAT-SPECT binding <100% expected for age and sex. Participants with an UPSIT <10th percentile (n = 1,221) had greater likelihood of low DAT-SPECT binding compared to participants with an UPSIT in the 10th to 15th percentile (odds ratio, 3.01; 95% confidence interval, 1.85-4.91). Overall, 55% (198/363) of cases with UPSIT <15th percentile and DAT-SPECT <100% had positive aSynSAA, which increased to 70% (182/260) when selecting for more severe hyposmia (UPSIT <10th percentile). INTERPRETATION:Remote screening for hyposmia and reduced DAT-SPECT binding identifies participants with a high proportion positive aSynSAA. Longitudinal data will be essential to define progression patterns in these individuals to ultimately inform recruitment into disease modification clinical trials. ANN NEUROL 2025;97:730-740.

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.

Importance Identifying individuals in the earliest stages of synucleinopathy is essential to evaluate drugs aimed to slow progression or prevent manifest disease. Remote identification of hyposmic individuals may enable scalable recruitment of participants with underlying alpha-synuclein pathology. Objective To evaluate the performance of a staged screening paradigm using smell testing to enrich for deficit on dopaminergic transporter (DAT) imaging and pathologic alpha-synuclein aggregation. Design Cross-sectional analysis of data from the Parkinson’s Progression Markers Initiative (PPMI). Setting Screening activities were completed both at home and local PPMI sites. Participants Individuals aged 60 and older without a diagnosis of Parkinson’s disease Interventions or Exposures: Participants were asked to complete a University of Pennsylvania Smell Identification Test (UPSIT) remotely. Participants with hyposmia were invited to complete DAT imaging, which determined eligibility for enrollment in longitudinal assessments and further biomarker evaluation including cerebrospinal fluid synuclein seed amplification assay (synSAA). Main Outcomes and Measures We determined the proportion of people with hyposmia, impaired DAT binding, and positive synSAA and explored determinants of these biomarkers. Results As of January 29, 2024, 49,843 participants were sent an UPSIT and 31,293 (63%) completed it. Of UPSIT completers, 8,301 (27%) scored <15th %ile. Of 1,546 who completed DAT, 19% had DAT binding < 65% expected for age and sex. Self-reported features were independently associated with severe hyposmia (UPSIT <10th %ile), such as REM sleep behavior disorder (RBD) or dream enactment behavior (DEB) (aOR: 1.9, 95% CI 1.7–2.1) and subjective smell loss (aOR: 15.0, 95% CI 13.7–16.3). Participants with an UPSIT <10th %ile (N=1,221) had greater likelihood of low DAT binding compared to participants with an UPSIT in the 10th – 15th %ile (OR 3.01, 95% CI 1.85–4.91). Among remotely recruited participants with synSAA results obtained, 198/363 (55%) had positive synSAA at baseline. This proportion increased when the cohort was limited to an UPSIT<10th %ile (182/257, 71%). Conclusion and Relevance Remote screening for severe hyposmia identifies participants with a high proportion of positive synSAA and reduced DAT binding. This staged screening protocol is an effective approach to identify cohorts for therapeutic trials aiming to slow progression in alpha-synucleinopathy. ### Competing Interest Statement EB has received research funding through his institution from MJFF, the NIH, and Gateway LLC and consulting fees from Guidepoint Inc and Rune Labs. LC declares research funding through her institution from Biogen, MJFF, the NIH, the University of Pittsburgh, and the UPMC Competitive Medical Research Fund, travel support from MJFF, and authorship royalties from Wolters Kluwel. AS receives research funding through his institution from MJFF and the NIH, consulting fees from SPARC Therapeutics, Capsida Therapeutics, and the Parkinson Study Group, and honoraria for lectures from Bial and participation on a Data Safety Monitoring Board for Wave Life Sciencies, Inhibikase, Prevail, the Huntington Study Group, and Massachusetts General Hospital. CG, CCG, and CSt declare research funding paid through their institution from MJFF. MB, TF, LH, and MKo receives research funding through their institution from MJFF and reimbursement for travel from MJFF. CC declares research funding through his institution from MJFF and the NIH. SC and MKu is an employee of MJFF. KF declares research funding through her institution from MJFF and consulting fees from Ontarget Labs and OncoNano. LC declares employment at Amprion, research funding through his employer from MJFF and the NIH, employee stock options at Amprion, and US Patents or patent application numbers 11959927, 11970520, 11254718, 20210164998, 20210223268, 20190353669, 20230084155, and 20240085435, all assigned to Amprion. CS is the Founder, Chief Scientific Officer, Consultant, shareholder and member of the Board of Directors of Amprion Inc, a biotech company focusing on the commercialization of the SAA technology for diagnosis of neurodegenerative diseases. TS has received research funding from the MJFF, Parkinson′s Foundation, NINDS, Amneal, Biogen, Roche, Neuroderm, Sanofi, Prevail, and UCB, and consulting fees from AcureX, Adamas, AskBio, Amneal, Blue Rock Therapeutics, Critical Path for Parkinson′s Consortium, Denali, MJFF, Neuroderm, Sanoif, Sinopia, Roche, Takeda, and Vanqua Bio, and participated on Advisory Board for AcureX, Adamas, AskBio, Biohaven, Denali, GAIN, Neuron23, and Roche, and a Scientific Advisory Board for Koneksa, Neuroderm, Sanofi, and UCB. KM declares research funding through his institution from MJFF, consulting fees for Invicro, MJFF, Roche, Calico, Coave, Neuron23, Orbimed, Biohaven, Sanofi, Koneksa, Merck, Lilly, Inhibikase, XingIMaging, IRLabs, Prothena. CT reports research funding through her institution from MJFF, NIH, Gateway LLC, Department of Defense, Roche Genentech, Biogen, Parkinson Foundation, Marcus Program in Precision Medicine, and consulting fees from CNS Ratings, Australian Parkinson′s Mission, Biogen, Evidera, Supernus, Neurocrine, WebMD/Medscape, and fees from Cadent (DSMB), Adamas (Steering Committee), Biogen (Steering Committee), Kyowa Kirin (Advisory Board), Lundbeck (Advisory Board), Jazz/Cavion (Steering Committee), Acorda (Advisory Board), Bial (DMC), and Genentech. ### Clinical Protocols ### Funding Statement PPMI - a public-private partnership - is funded by the Michael J. Fox Foundation for Parkinson's Research and funding partners, including 4D Pharma, Abbvie, AcureX, Allergan, Amathus Therapeutics, Aligning Science Across Parkinson's, AskBio, Avid Radiopharmaceuticals, BIAL, BioArctic, Biogen, Biohaven, BioLegend, BlueRock Therapeutics, Bristol-Myers Squibb, Calico Labs, Capsida Biotherapeutics, Celgene, Cerevel Therapeutics, Coave Therapeutics, DaCapo Brainscience, Denali, Edmond J. Safra Foundation, Eli Lilly, Gain Therapeutics, GE HealthCare, Genentech, GSK, Golub Capital, Handl Therapeutics, Insitro, Jazz Pharmaceuticals, Johnson & Johnson Innovative Medicine, Lundbeck, Merck, Meso Scale Discovery, Mission Therapeutics, Neurocrine Biosciences, Neuron23, Neuropore, Pfizer, Piramal, Prevail Therapeutics, Roche, Sanofi, Servier, Sun Pharma Advanced Research Company, Takeda, Teva, UCB, Vanqua Bio, Verily, Voyager Therapeutics, the Weston Family Foundation and Yumanity Therapeutics. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The WIRB-Copernicus Group (WCG) IRB has approved this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data used in the preparation of this article were obtained on January 29, 2024 from the Parkinson’s Progression Markers Initiative (PPMI) database ([www.ppmi-info.org/access-data-specimens/download-data][1]), RRID:SCR 006431. For up-to-date information on the study, visit [www.ppmi-info.org][2]. This analysis was conducted by the PPMI Statistics Core and used actual dates of activity for participants, a restricted data element not available to public users of PPMI data. Statistical analysis codes used to perform the analyses in this article are shared on Zenodo (10.5281/zenodo.11391274). This analysis used DaTscan and αSyn-SAA results for prodromal participants, obtained from PPMI upon request after approval by the PPMI Data Access Committee. [1]: http://www.ppmi-info.org/access-data-specimens/download-data [2]: http://www.ppmi-info.org

To apply Neuronal α-Synuclein Disease Integrated Staging System (NSD-ISS) in PPMI participants

Background and ObjectivesIn Parkinson disease (PD), Alzheimer disease (AD) copathology is common and clinically relevant. However, the longitudinal progression of AD CSF biomarkers-beta-amyloid 1-42 (A beta 42), phosphorylated tau 181 (p-tau181), and total tau (t-tau)-in PD is poorly understood and may be distinct from clinical AD. Moreover, it is unclear whether CSF p-tau181 and serum neurofilament light (NfL) have added prognostic utility in PD, when combined with CSF A beta 42. First, we describe longitudinal trajectories of biofluid markers in PD. Second, we modified the AD beta-amyloid/tau/neurodegeneration (ATN) framework for application in PD (ATNPD) using CSF A beta 42 (A), p-tau181 (T), and serum NfL (N) and tested ATNPD prediction of longitudinal cognitive decline in PD.MethodsParticipants were selected from the Parkinson's Progression Markers Initiative cohort, clinically diagnosed with sporadic PD or as controls, and followed up annually for 5 years. Linear mixed-effects models (LMEMs) tested the interaction of diagnosis with longitudinal trajectories of analytes (log transformed, false discovery rate [FDR] corrected). In patients with PD, LMEMs tested how baseline ATNPD status (AD [A+T+N +/-] vs not) predicted clinical outcomes, including Montreal Cognitive Assessment (MoCA; rank transformed, FDR corrected).ResultsParticipants were 364 patients with PD and 168 controls, with comparable baseline mean (+/- SD) age (patients with PD = 62 +/- 10 years; controls = 61 +/- 11 years]; Mann-Whitney Wilcoxon: p = 0.4) and sex distribution (patients with PD = 231 male individuals [63%]; controls = 107 male individuals [64%]; chi 2: p = 1). Patients with PD had overall lower CSF p-tau181 (beta = -0.16, 95% CI -0.23 to -0.092, p = 2.2e-05) and t-tau than controls (beta = -0.13, 95% CI -0.19 to -0.065, p = 4e-04), but not A beta 42 (p = 0.061) or NfL (p = 0.32). Over time, patients with PD had greater increases in serum NfL than controls (beta = 0.035, 95% CI 0.022 to 0.048, p = 9.8e-07); slopes of patients with PD did not differ from those of controls for CSF A beta 42 (p = 0.18), p-tau181 (p = 1), or t-tau (p = 0.96). Using ATNPD, PD classified as A+T+N +/- (n = 32; 9%) had worse cognitive decline on global MoCA (beta = -73, 95% CI -110 to -37, p = 0.00077) than all other ATNPD statuses including A+ alone (A+T-N-; n = 75; 21%).DiscussionIn patients with early PD, CSF p-tau181 and t-tau were low compared with those in controls and did not increase over 5 years of follow-up. Our study shows that classification using modified ATNPD (incorporating CSF A beta 42, CSF p-tau181, and serum NfL) can identify biologically relevant subgroups of PD to improve prediction of cognitive decline in early PD.

Background and Objectives: Cognitive impairment is common at all stages in Parkinson's disease (PD). However, the field is hampered by consensus over which neuropsychological tests to use and how to utilize the results generated by a cognitive battery. An option that combines the richness of a neuropsychological battery with the simplicity of a single test score is a cognitive summary score (CSS). The objective was to determine if a CSS created using robust norming is sensitive in detecting early cognitive deficits in de novo, untreated PD. Methods: Using baseline cognitive data from PD participants and healthy controls (HCs) in the Parkinson's Progression Markers Initiative, these steps were taken: (1) creating a robust HC subgroup that did not demonstrate cognitive decline over time; (2) using the robust HC subgroup to create regression-based internally-derived standardized scores (z-scores) for six cognitive scores across five tests; and (3) creating a CSS by averaging all standardized test z-scores. Results: PD participants scored worse than HCs on all cognitive tests, with a larger effect size (PD versus HCs) when the comparison group was the robust HC subgroup compared with all HCs. Applying internally-derived norms rather than published norms, the largest cognitive domain effect sizes (PD vs. robust HCs) were for processing speed/working memory (Cohen's d= -0.55) and verbal episodic memory (Cohen's d= -0.48 and -0.52). In addition, using robust norming shifted PD performance from the middle of the average range (CSS z-score= -0.01) closer to low average (CSS z-score= -0.40), with the CSS having a larger effect size (PD vs. robust HC subgroup; Cohen's d= -0.60) compared with all individual cognitive tests. Discussion: PD patients perform worse cognitively than HC at disease diagnosis on multiple cognitive domains, particularly information processing speed and verbal memory. Using robust norming increases effect sizes and lowers the scores of PD patients to "expected" levels. The CSS performed better than all individual cognitive tests. A CSS developed using a robust norming process may be sensitive to cognitive changes in the earliest stages of PD and have utility as an outcome measure in clinical research, including clinical trials. ### Competing Interest Statement To be included in published paper. ### Clinical Protocols ### Funding Statement PPMI, a public-private partnership, is funded by the Michael J. Fox Foundation for Parkinson's Research and funding partners, including 4D Pharma, Abbvie, AcureX, Allergan, Amathus Therapeutics, Aligning Science Across Parkinson's, AskBio, Avid Radiopharmaceuticals, BIAL, BioArctic, Biogen, Biohaven, BioLegend, BlueRock Therapeutics, Bristol-Myers Squibb, Calico Labs, Capsida Biotherapeutics, Celgene, Cerevel Therapeutics, Coave Therapeutics, DaCapo Brainscience, Denali, Edmond J. Safra Foundation, Eli Lilly, Gain Therapeutics, GE HealthCare, Genentech, GSK, Golub Capital, Handl Therapeutics, Insitro, Jazz Pharmaceuticals, Johnson & Johnson Innovative Medicine, Lundbeck, Merck, Meso Scale Discovery, Mission Therapeutics, Neurocrine Biosciences, Neuron23, Neuropore, Pfizer, Piramal, Prevail Therapeutics, Roche, Sanofi, Servier, Sun Pharma Advanced Research Company, Takeda, Teva, UCB, Vanqua Bio, Verily, Voyager Therapeutics, the Weston Family Foundation and Yumanity Therapeutics. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: PPMI data used in the preparation of this article were obtained November 6, 2023 from the Parkinson's Progression Markers Initiative (PPMI) database (www.ppmi-info.org/access-data-specimens/download-data), RRID:SCR 006431. This analysis was conducted by the PPMI Statistics Core and used actual dates of activity for participants, a restricted data element not available to public users of PPMI data. PPMI data are publicly available from the Parkinson's Progression Markers Initiative (PPMI) database (www.ppmi-info.org/access-data-specimens/download-data). For up-to-date information on the study, visit www.ppmi-info.org. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes PPMI data used in the preparation of this article were obtained November 6, 2023 from the Parkinson's Progression Markers Initiative (PPMI) database (www.ppmi-info.org/access-data-specimens/download-data), RRID:SCR 006431. This analysis was conducted by the PPMI Statistics Core and used actual dates of activity for participants, a restricted data element not available to public users of PPMI data. PPMI data are publicly available from the Parkinson's Progression Markers Initiative (PPMI) database (www.ppmi-info.org/access-data-specimens/download-data). For up-to-date information on the study, visit www.ppmi-info.org.