A research biologic definition and staging of neuronal alpha-synucleinopathies, including Parkinson's disease and dementia with Lewy bodies, is critical toward improving clinical trial design and drug development. Neuronal synuclein disease, and the companion Integrated Staging System, are a biologic definition and staging system conceptualized by multiple stakeholders including academia, industry, advocacy organizations, and importantly, people with lived experiences. In large part, this was informed and enabled by the knowledge garnered from the Parkinson's Progression Markers Initiative. This review provides a historical perspective and details contributions from the Parkinson's Progression Markers Initiative, among others, that made this advancement possible. These include the key role it played in validation of an in vivo biomarker of neuronal alpha-synuclein, longitudinal characterization of dopaminergic dysfunction imaging, biospecimen collection and assays, comprehensive genetic characterization, and clinical phenotyping. In addition, the Parkinson's Progression Markers Initiative is generating and sharing data that will be used to address key gaps in knowledge, revisions, and future refinements of a biologic definition and staging of synucleinopathies. ANN NEUROL 2026.

The alpha-synuclein seed amplification assay in cerebrospinal fluid is the first validated molecular measurement of alpha-synuclein biology in a living person. The SAA test is transforming our understanding of aging and neurodegenerative diseases by detecting abnormal synuclein biology, and data suggests SAA positivity can occur across Parkinson's disease, Alzheimer's disease, and Dementia with Lewy Bodies. To accelerate development of this important research tool, the Michael J. Fox Foundation proactively funded a community of researchers to work both independently and collaboratively, leading to rapid and iterative progress and validation. The collective validation of the assay across industry and academic groups culminated in a Food and Drug Administration Letter of Support for the test in clinical trials for PD. This article describes the principles that accelerated the development of the assay including patient engagement, collaboration, a commitment to open science through data, sample, and knowledge sharing, and showcases how an international community of experts rallied together towards a common goal.

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.

Background: Biomarkers of abnormal alpha-synuclein (asyn) that can be obtained with minimal invasiveness are needed. Promising data on dermal serine-129-phosphorylated alpha-synuclein (dermal-ps129-asyn) have emerged but accuracy for aggregated asyn in cerebrospinal fluid (CSF) has not been examined. Objective: Determine sensitivity and specificity of dermal-ps129-asyn for neuronal asyn measured with cerebrospinal fluid asyn seed amplification assay (CSFasynSAA). Methods: Cross-sectional observational study; 50 individuals with positive or negative CSFasynSAA underwent 3 skin biopsies for blinded assessment of phospho-serine-129 asyn in nerve terminals. Sensitivity and specificity versus CSFasynSAA were calculated. Results: Among 50 participants, 30/38 CSFasynSAA+ were dermal-ps129-asyn+; 6/12 CSFasynSAA- were dermal-ps129-asyn-, yielding sensitivity of 79% and specificity of 50%. Conclusion: Dermal-ps129-asyn has low specificity for CSF asyn SAA in this small sample. This precludes its use as a marker of CSF neuronal asyn aggregates. Future studies are needed to determine optimal methods to assess asyn aggregates in central and peripheral compartments. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Protocols ### Funding Statement This study was funded by The Michael J. Fox Foundation for Parkinson's Research, Grant ID: 026366/026110. PPMI is a public-private partnership 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: Data were obtained on 25-August, 2025 from the PPMI database (www.ppmi-info.org/access-data-specimens/download-data), RRID:SCR_006431. Analyses, conducted by PPMI Statistics Core, used actual dates, a restricted (not publicly available) data element. PPMI Data Access Committee approved use of CSFasynSAA and DaTscan results. 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 were obtained on 25-August, 2025 from the PPMI database (www.ppmi-info.org/access-data-specimens/download-data), RRID:SCR_006431. Analyses, conducted by PPMI Statistics Core, used actual dates, a restricted (not publicly available) data element. PPMI Data Access Committee approved use of CSFasynSAA and DaTscan results.

More than 57 million people globally suffer from neurodegenerative diseases, a figure expected to double every 20 years. Despite this growing burden, there are currently no cures, and treatment options remain limited due to disease heterogeneity, prolonged preclinical and prodromal phases, poor understanding of disease mechanisms, and diagnostic challenges. Identifying novel biomarkers is crucial for improving early detection, prognosis, staging and subtyping of these conditions. High-dimensional molecular studies in biofluids ('omics') offer promise for scalable biomarker discovery, but challenges in assembling large, diverse datasets hinder progress. To address this, the Global Neurodegeneration Proteomics Consortium (GNPC)-a public-private partnership-established one of the world's largest harmonized proteomic datasets. It includes approximately 250 million unique protein measurements from multiple platforms from more than 35,000 biofluid samples (plasma, serum and cerebrospinal fluid) contributed by 23 partners, alongside associated clinical data spanning Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). This dataset is accessible to GNPC members via the Alzheimer's Disease Data Initiative's AD Workbench, a secure cloud-based environment, and will be available to the wider research community on 15 July 2025. Here we present summary analyses of the plasma proteome revealing disease-specific differential protein abundance and transdiagnostic proteomic signatures of clinical severity. Furthermore, we describe a robust plasma proteomic signature of APOE ε4 carriership, reproducible across AD, PD, FTD and ALS, as well as distinct patterns of organ aging across these conditions. This work demonstrates the power of international collaboration, data sharing and open science to accelerate discovery in neurodegeneration research.

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.

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

Objectives:To determine the impact of dopamine deficiency and isolated REM sleep behavior disorder (iRBD) on cognitive performance in early neuronal alpha-synuclein disease (NSD) with hyposmia. Methods:Using Parkinson's Progression Markers Initiative baseline data, cognitive performance was assessed with a cognitive summary score (CSS) developed by applying regression-based internal norms derived from a robust healthy control (HC) group. Performance was examined for participants with hyposmia classified as NSD-Integrated Staging System (NSD-ISS) Stage 2, either Stage 2A (CSF alpha-synuclein seed amplification assay [SAA]+, SPECT 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 overall 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-value NS; effect size=0.09) and Stage 2B had a statistically worse CSS (z-score mean difference =0.23, p-value <0.05; effect size=0.40) compared with HCs. In Stage 2A participants with hyposmia alone had normal cognition, but presence of comorbid iRBD was associated with significantly worse cognition (z-score mean difference =0.33, p-value <0.05, effect size =0.50). In Stage 2B participants with hyposmia had abnormal cognition (z-score mean difference =0.18, p-value =.0078, effect size =0.29), and superimposed iRBD had a non-statistically significant additive effect. Interpretation:Using a CSS, early NSD with hyposmia is associated with measurable cognitive deficits compared with robust HCs, particularly in presence of dopamine system impairment or comorbid iRBD, highlighting the importance of focusing on cognition in early-stage synuclein disease.

Parkinson's disease and dementia with Lewy bodies are currently defined by their clinical features, with α-synuclein pathology as the gold standard to establish the definitive diagnosis. We propose that, given biomarker advances enabling accurate detection of pathological α-synuclein (ie, misfolded and aggregated) in CSF using the seed amplification assay, it is time to redefine Parkinson's disease and dementia with Lewy bodies as neuronal α-synuclein disease rather than as clinical syndromes. This major shift from a clinical to a biological definition of Parkinson's disease and dementia with Lewy bodies takes advantage of the availability of tools to assess the gold standard for diagnosis of neuronal α-synuclein (n-αsyn) in human beings during life. Neuronal α-synuclein disease is defined by the presence of pathological n-αsyn species detected in vivo (S; the first biological anchor) regardless of the presence of any specific clinical syndrome. On the basis of this definition, we propose that individuals with pathological n-αsyn aggregates are at risk for dopaminergic neuronal dysfunction (D; the second biological anchor). Our biological definition establishes a staging system, the neuronal α-synuclein disease integrated staging system (NSD-ISS), rooted in the biological anchors (S and D) and the degree of functional impairment caused by clinical signs or symptoms. Stages 0-1 occur without signs or symptoms and are defined by the presence of pathogenic variants in the SNCA gene (stage 0), S alone (stage 1A), or S and D (stage 1B). The presence of clinical manifestations marks the transition to stage 2 and beyond. Stage 2 is characterised by subtle signs or symptoms but without functional impairment. Stages 2B-6 require both S and D and stage-specific increases in functional impairment. A biological definition of neuronal α-synuclein disease and an NSD-ISS research framework are essential to enable interventional trials at early disease stages. The NSD-ISS will evolve to include the incorporation of data-driven definitions of stage-specific functional anchors and additional biomarkers as they emerge and are validated. Presently, the NSD-ISS is intended for research use only; its application in the clinical setting is premature and inappropriate.

BACKGROUND:Emerging evidence shows that α-synuclein seed amplification assays (SAAs) have the potential to differentiate people with Parkinson's disease from healthy controls. We used the well characterised, multicentre Parkinson's Progression Markers Initiative (PPMI) cohort to further assess the diagnostic performance of the α-synuclein SAA and to examine whether the assay identifies heterogeneity among patients and enables the early identification of at-risk groups. METHODS:This cross-sectional analysis is based on assessments done at enrolment for PPMI participants (including people with sporadic Parkinson's disease from LRRK2 and GBA variants, healthy controls, prodromal individuals with either rapid eye movement sleep behaviour disorder (RBD) or hyposmia, and non-manifesting carriers of LRRK2 and GBA variants) from 33 participating academic neurology outpatient practices worldwide (in Austria, Canada, France, Germany, Greece, Israel, Italy, the Netherlands, Norway, Spain, the UK, and the USA). α-synuclein SAA analysis of CSF was performed using previously described methods. We assessed the sensitivity and specificity of the α-synuclein SAA in participants with Parkinson's disease and healthy controls, including subgroups based on genetic and clinical features. We established the frequency of positive α-synuclein SAA results in prodromal participants (RBD and hyposmia) and non-manifesting carriers of genetic variants associated with Parkinson's disease, and compared α-synuclein SAA to clinical measures and other biomarkers. We used odds ratio estimates with 95% CIs to measure the association between α-synuclein SAA status and categorical measures, and two-sample 95% CIs from the resampling method to assess differences in medians between α-synuclein SAA positive and negative participants for continuous measures. A linear regression model was used to control for potential confounders such as age and sex. FINDINGS:This analysis included 1123 participants who were enrolled between July 7, 2010, and July 4, 2019. Of these, 545 had Parkinson's disease, 163 were healthy controls, 54 were participants with scans without evidence of dopaminergic deficit, 51 were prodromal participants, and 310 were non-manifesting carriers. Sensitivity for Parkinson's disease was 87·7% (95% CI 84·9-90·5), and specificity for healthy controls was 96·3% (93·4-99·2). The sensitivity of the α-synuclein SAA in sporadic Parkinson's disease with the typical olfactory deficit was 98·6% (96·4-99·4). The proportion of positive α-synuclein SAA was lower than this figure in subgroups including LRRK2 Parkinson's disease (67·5% [59·2-75·8]) and participants with sporadic Parkinson's disease without olfactory deficit (78·3% [69·8-86·7]). Participants with LRRK2 variant and normal olfaction had an even lower α-synuclein SAA positivity rate (34·7% [21·4-48·0]). Among prodromal and at-risk groups, 44 (86%) of 51 of participants with RBD or hyposmia had positive α-synuclein SAA (16 of 18 with hyposmia, and 28 of 33 with RBD). 25 (8%) of 310 non-manifesting carriers (14 of 159 [9%] LRRK2 and 11 of 151 [7%] GBA) were positive. INTERPRETATION:This study represents the largest analysis so far of the α-synuclein SAA for the biochemical diagnosis of Parkinson's disease. Our results show that the assay classifies people with Parkinson's disease with high sensitivity and specificity, provides information about molecular heterogeneity, and detects prodromal individuals before diagnosis. These findings suggest a crucial role for the α-synuclein SAA in therapeutic development, both to identify pathologically defined subgroups of people with Parkinson's disease and to establish biomarker-defined at-risk cohorts. FUNDING:PPMI is funded by the Michael J Fox Foundation for Parkinson's Research and funding partners, including: Abbvie, AcureX, Aligning Science Across Parkinson's, Amathus Therapeutics, Avid Radiopharmaceuticals, Bial Biotech, Biohaven, Biogen, BioLegend, Bristol-Myers Squibb, Calico Labs, Celgene, Cerevel, Coave, DaCapo Brainscience, 4D Pharma, Denali, Edmond J Safra Foundation, Eli Lilly, GE Healthcare, Genentech, GlaxoSmithKline, Golub Capital, Insitro, Janssen Neuroscience, Lundbeck, Merck, Meso Scale Discovery, Neurocrine Biosciences, Prevail Therapeutics, Roche, Sanofi Genzyme, Servier, Takeda, Teva, UCB, VanquaBio, Verily, Voyager Therapeutics, and Yumanity.

The pathogenesis and clinical heterogeneity of Parkinson's disease (PD) have been evaluated from molecular, pathophysiological, and clinical perspectives. High-throughput proteomic analysis of cerebrospinal fluid (CSF) opened new opportunities for scrutinizing this heterogeneity. To date, this is the most comprehensive CSF-based proteomics profiling study in PD with 569 patients (350 idiopathic patients, 65 GBA + mutation carriers and 154 LRRK2 + mutation carriers), 534 controls, and 4135 proteins analyzed. Combining CSF aptamer-based proteomics with genetics we determined protein quantitative trait loci (pQTLs). Analyses of pQTLs together with summary statistics from the largest PD genome wide association study (GWAS) identified 68 potential causal proteins by Mendelian randomization. The top causal protein, GPNMB, was previously reported to be upregulated in the substantia nigra of PD patients. We also compared the CSF proteomes of patients and controls. Proteome differences between GBA + patients and unaffected GBA + controls suggest degeneration of dopaminergic neurons, altered dopamine metabolism and increased brain inflammation. In the LRRK2 + subcohort we found dysregulated lysosomal degradation, altered alpha-synuclein processing, and neurotransmission. Proteome differences between idiopathic patients and controls suggest increased neuroinflammation, mitochondrial dysfunction/oxidative stress, altered iron metabolism and potential neuroprotection mediated by vasoactive substances. Finally, we used proteomic data to stratify idiopathic patients into "endotypes". The identified endotypes show differences in cognitive and motor disease progression based on previously reported protein-based risk scores.Our findings not only contribute to the identification of new therapeutic targets but also to shape personalized medicine in CNS neurodegeneration.

Summary Background Recent research demonstrates that α-synuclein seed amplification assays (αSyn-SAA) accurately differentiate Parkinson’s disease (PD) patients from healthy controls (HC). We used the well-characterized, multicenter Parkinson’s Progression Markers Initiative (PPMI) cohort to further assess the diagnostic performance of αSyn-SAA and to examine whether the assay identifies heterogeneity among patients and enables early identification in at-risk groups. Methods αSyn-SAA analysis of cerebrospinal fluid (CSF) was performed using previously described methods. We assessed sensitivity and specificity in PD and HC, including subgroups based on genetic and clinical features. We determined the frequency of positive αSyn-SAA results in prodromal participants (REM sleep behavior disorder and hyposmia) and non-manifesting carriers (NMCs) of genetic variants associated with PD and compared αSyn-SAA to clinical measures and other biomarkers. Findings 1,123 participants were included: 545 PD, 163 HCs, 54 participants with scans without evidence of dopaminergic deficit (SWEDDs), 51 prodromal participants, and 310 NMCs. Sensitivity and specificity for PD versus HC were 88% and 96%, respectively. Sensitivity in sporadic PD with the typical olfactory deficit was 99%. The proportion of positive αSyn-SAA was lower in subgroups including LRRK2 PD (68%) and sporadic PD patients without olfactory deficit (78%). Participants with LRRK2 variant and normal olfaction had an even lower αSyn-SAA positivity rate (35%). Among prodromal and at-risk groups, 86% of RBD and hyposmic cases had positive αSyn-SAA. 8% of NMC (either LRRK2 or GBA) were positive. Interpretation This study represents the largest analysis of αSyn-SAA for biochemical diagnosis of PD. Our results demonstrate that the assay classifies PD patients with high sensitivity and specificity, provides information about molecular heterogeneity, and detects prodromal individuals prior to diagnosis. These findings suggest a crucial role for αSyn-SAA in therapeutic development, both to identify pathologically defined subgroups of PD patients and to establish biomarker-defined at-risk cohorts. Funding PPMI – a public-private partnership – is funded by the Michael J. Fox Foundation for Parkinson’s Research and funding partners, including: PPMI is supported by a consortium of private and philanthropic parnters: Abbvie, AcureX, Aligning Science Across Parkinson’s, Amathus Therapeutics, Avid Radiopharmaceuticals, Bial Biotech, Biohaven, Biogen, BioLegend, Bristol-Myers Squibb, Calico Labs, Celgene, Cerevel, Coave, DaCapo Brainscience, 4D Pharma, Denali, Edmond J. Safra Foundation, Eli Lilly, GE Healthcare, Genentech, GlaxoSmithKline, Golub Capital, Insitro, Janssen Neuroscience, Lundbeck, Merck, Meso Scale Discovery, Neurocrine Biosciences, Prevail Therapeutics, Roche, Sanofi Genzyme, Servier, Takeda, Teva, UCB, VanquaBio, Verily, Voyager Therapeutics, and Yumanity. Research in Context Evidence before the study We searched PubMed with the terms Parkinson’s disease (PD), prodromal, Non-manifest carriers, GBA, LRRK2 and real-me quaking-induced conversion (RT-QuIC), protein misfolding cyclic amplification (PMCA), and seed amplification assay (SAA) for articles published in English on or before Oct 25, 2022, in any field. This is a large and rapidly growing literature, and a number of studies were identified, including case-series of PD patients with and without genetic variants, individuals with isolated REM sleep behavior disorder (RBD), and a small number of studies of non-manifesting carriers of genetic variants (4) associated with PD. Added value of the study To our knowledge, this is the largest report of comparative data from a cohort of PD patients, healthy controls, individuals with clinical syndromes prodromal to PD (hyposmia and RBD), and non-manifest carriers of LRRK2 G2019S and GBA N370S mutations. The strengths of our data include a large sample size, robust clinical data set, a high percentage of DAT scans completed, and the ability to compare non-manifest carriers to similar aged healthy controls, which allows for inter-group comparisons and sub-group analysis. The key novel findings in this study include: 1) marked variability in rates of positive αSyn-SAA results particularly among LRRK2 variant carriers depending on olfactory performance and sex; 2) αSyn-SAA positivity in prodromal and NMCs without dopaminergic imaging abnormalities in a substantial number of cases, while the converse is less common, indicating that αSyn-SAA may be a very early indicator of synucleinopathy. We also confirmed the high diagnostic accuracy of αSyn-SAA for sporadic PD vs. HC and that αSyn-SAA is negative in the vast majority of NMC, suggesting that the presence of synuclein aggregates in CSF is not a life-long trait but rather acquired at some point relatively close to disease onset. Implications of all available evidence Our results demonstrate that the assay classifies PD patients with high sensitivity and specificity, provides information about molecular heterogeneity, and detects prodromal individuals prior to diagnosis. These findings suggest a crucial role for αSyn-SAA in therapeutic development, both to identify pathologically defined subgroups of PD patients and to establish biomarker-defined at-risk cohorts.

Now that wearable sensors have become more commonplace, it is possible to monitor individual healthcare-related activity outside the clinic, unleashing potential for early detection of events in diseases such as Parkinson’s disease (PD). However, the unsupervised and “open world” nature of this type of data collection make such applications difficult to develop. In this proof-of-concept study, we used inertial sensor data from Verily Study Watches worn by individuals for up to 23 h per day over several months to distinguish between seven subjects with PD and four without. Since motor-related PD symptoms such as bradykinesia and gait abnormalities typically present when a PD subject is walking, we initially used human activity recognition (HAR) techniques to identify walk-like activity in the unconstrained, unlabeled data. We then used these “walk-like” events to train one-dimensional convolutional neural networks (1D-CNNs) to determine the presence of PD. We report classification accuracies near 90% on single 5-s walk-like events and 100% accuracy when taking the majority vote over single-event classifications that span a duration of one day. Though based on a small cohort, this study shows the feasibility of leveraging unconstrained wearable sensor data to accurately detect the presence or absence of PD.

Several recent publications described algorithms to identify subjects with Parkinson’s disease (PD). In creating the “PREDIGT Score”, we previously developed a hypothesis-driven, simple-to-use formula to potentially calculate the incidence of PD. Here, we tested its performance in the ‘De Novo Parkinson Study’ (DeNoPa) and ‘Parkinson’s Progression Marker Initiative’ (PPMI); the latter included participants from the ‘FOllow Up persons with Neurologic Disease’ (FOUND) cohort. Baseline data from 563 newly diagnosed PD patients and 306 healthy control subjects were evaluated. Based on 13 variables, the original PREDIGT Score identified recently diagnosed PD patients in the DeNoPa, PPMI + FOUND and the pooled cohorts with area-under-the-curve (AUC) values of 0.88 (95% CI 0.83–0.92), 0.79 (95% CI 0.72–0.85), and 0.84 (95% CI 0.8–0.88), respectively. A simplified version (8 variables) generated AUC values of 0.92 (95% CI 0.89–0.95), 0.84 (95% CI 0.81–0.87), and 0.87 (0.84–0.89) in the DeNoPa, PPMI, and the pooled cohorts, respectively. In a two-step, screening-type approach, self-reported answers to a questionnaire (step 1) distinguished PD patients from controls with an AUC of 0.81 (95% CI 0.75–0.86). Adding a single, objective test (Step 2) further improved classification. Among seven biological markers explored, hyposmia was the most informative. The composite AUC value measured 0.9 (95% CI 0.88–0.91) in DeNoPa and 0.89 (95% CI 0.84–0.94) in PPMI. These results reveal a robust performance of the original PREDIGT Score to distinguish newly diagnosed PD patients from controls in two established cohorts. We also demonstrate the formula’s potential applicability to enriching for PD subjects in a population screening-type approach.

ABSTRACT Heterozygous mutations in the GBA1 gene – encoding lysosomal glucocerebrosidase (GCase) – are the most common genetic risk factors for Parkinson's disease (PD). Experimental evidence suggests a correlation between decreased GCase activity and accumulation of alpha-synuclein (aSyn). To enable a better understanding of the relationship between aSyn and GCase activity, we developed and characterized two mouse models that investigate aSyn pathology in the context of reduced GCase activity. The first model used constitutive overexpression of wild-type human aSyn in the context of the homozygous GCase activity-reducing D409V mutant form of GBA1. Although increased aSyn pathology and grip strength reductions were observed in this model, the nigrostriatal system remained largely intact. The second model involved injection of aSyn preformed fibrils (PFFs) into the striatum of the homozygous GBA1 D409V knock-in mouse model. The GBA1 D409V mutation did not exacerbate the pathology induced by aSyn PFF injection. This study sheds light on the relationship between aSyn and GCase in mouse models, highlighting the impact of model design on the ability to model a relationship between these proteins in PD-related pathology.

Despite many pharmacological and surgical treatments addressing the symptoms of Parkinson's disease, there are no approved treatments that slow disease progression. Genetic discoveries in the last 20 years have increased our understanding of the molecular contributors to Parkinson's pathophysiology, uncovered many druggable targets and pathways, and increased investment in treatments that might slow or stop the disease process. Longitudinal, observational studies are dissecting Parkinson's disease heterogeneity and illuminating the importance of molecularly defined subtypes more likely to respond to targeted interventions. Indeed, clinical and pathological differences seen within and across carriers of PD-associated gene mutations suggest the existence of greater biological complexity than previously appreciated and increase the likelihood that targeted interventions based on molecular characteristics will be beneficial. This article offers our current perspective on the promise and current challenges in subtype identification and precision medicine approaches in Parkinson's disease.

Changes in the blood-based RNA transcriptome have the potential to inform biomarkers of Parkinson's disease (PD) progression. Here we sequenced a discovery set of whole-blood RNA species in 4,871 longitudinally collected samples from 1,570 clinically phenotyped individuals from the Parkinson's Progression Marker Initiative (PPMI) cohort. Samples were sequenced to an average of 100 million read pairs to create a high-quality transcriptome. Participants with PD in the PPMI had significantly altered RNA expression (>2,000 differentially expressed genes), including an early and persistent increase in neutrophil gene expression, with a concomitant decrease in lymphocyte cell counts. This was validated in a cohort from the Parkinson's Disease Biomarkers Program (PDBP) consisting of 1,599 participants and by alterations in immune cell subtypes. This publicly available transcriptomic dataset, coupled with available detailed clinical data, provides new insights into PD biological processes impacting whole blood and new paths for developing diagnostic and prognostic PD biomarkers. The authors report whole-blood RNA-seq for 4,871 samples from 1,570 participants in the Parkinson Progression Marker Initiative. This Resource documents blood-based transcriptomic changes associated with PD, including early increases in neutrophil gene expression with a decrease in lymphocytes.

BackgroundParkinson's disease is heterogeneous in symptom presentation and progression. Increased understanding of both aspects can enable better patient management and improve clinical trial design. Previous approaches to modelling Parkinson's disease progression assumed static progression trajectories within subgroups and have not adequately accounted for complex medication effects. Our objective was to develop a statistical progression model of Parkinson's disease that accounts for intra-individual and inter-individual variability and medication effects.MethodsIn this longitudinal data study, data were collected for up to 7-years on 423 patients with early Parkinson's disease and 196 healthy controls from the Parkinson's Progression Markers Initiative (PPMI) longitudinal observational study. A contrastive latent variable model was applied followed by a novel personalised input-output hidden Markov model to define disease states. Clinical significance of the states was assessed using statistical tests on seven key motor or cognitive outcomes (mild cognitive impairment, dementia, dyskinesia, presence of motor fluctuations, functional impairment from motor fluctuations, Hoehn and Yahr score, and death) not used in the learning phase. The results were validated in an independent sample of 610 patients with Parkinson's disease from the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP).FindingsPPMI data were download July 25, 2018, medication information was downloaded on Sept 24, 2018, and PDBP data were downloaded between June 15 and June 24, 2020. The model discovered eight disease states, which are primarily differentiated by functional impairment, tremor, bradykinesia, and neuropsychiatric measures. State 8, the terminal state, had the highest prevalence of key clinical outcomes including 18 (95%) of 19 recorded instances of dementia. At study outset 4 (1%) of 333 patients were in state 8 and 138 (41%) of 333 patients reached stage 8 by year 5. However, the ranking of the starting state did not match the ranking of reaching state 8 within 5 years. Overall, patients starting in state 5 had the shortest time to terminal state (median 2·75 [95% CI 1·75–4·25] years).InterpretationWe developed a statistical progression model of early Parkinson's disease that accounts for intra-individual and inter-individual variability and medication effects. Our predictive model discovered non-sequential, overlapping disease progression trajectories, supporting the use of non-deterministic disease progression models, and suggesting static subtype assignment might be ineffective at capturing the full spectrum of Parkinson's disease progression.FundingMichael J Fox Foundation.