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Objective To determine the evolution of numerous neuropsychiatric symptoms and cognitive abilities in Parkinson disease from disease onset. Methods Prospectively collected, longitudinal (untreated, disease onset to year 5), observational data from Parkinson's Progression Markers Initiative annual visits was used to evaluate prevalence, correlates, and treatment of 10 neuropsychiatric symptoms and cognitive impairment in Parkinson disease participants and matched healthy controls. Results Of 423 Parkinson disease participants evaluated at baseline, 315 (74.5%) were assessed at year 5. Eight neuropsychiatric symptoms studied increased in absolute prevalence by 6.2–20.9% at year 5 relative to baseline, and cognitive impairment increased by 2.7–6.2%. In comparison, the frequency of neuropsychiatric symptoms in healthy controls remained stable or declined over time. Antidepressant and anxiolytic/hypnotic use in Parkinson disease were common at baseline and increased over time (18% to 27% for the former; 13% to 24% for the latter); antipsychotic and cognitive‐enhancing medication use was uncommon throughout (2% and 5% of patients at year 5); and potentially harmful anticholinergic medication use was common and increased over time. At year 5 the cross‐sectional prevalence for having three or more neuropsychiatric disorders/cognitive impairment was 56% for Parkinson disease participants versus 13% for healthy controls, and by then seven of the examined disorders had either occurred or been treated at some time point in the majority of Parkinson disease patients. Principal component analysis suggested an affective disorder subtype only. Interpretation Neuropsychiatric features in Parkinson disease are common from the onset, increase over time, are frequently comorbid, and fluctuate in severity.

Introduction Individuals with idiopathic rapid eye movement sleep behavior disorder (iRBD) are at high risk for a clinical diagnosis of an α‐synucleinopathy (aSN). They could serve as a key population for disease‐modifying trials. Abnormal dopamine transporter (DAT) imaging is a strong candidate biomarker for risk of aSN diagnosis in iRBD. Our primary objective was to identify a quantitative measure of DAT imaging that predicts diagnosis of clinically‐defined aSN in iRBD. Methods The sample included individuals with iRBD, early Parkinson’s Disease (PD), and healthy controls (HC) enrolled in the Parkinson Progression Marker Initiative, a longitudinal, observational, international, multicenter study. The iRBD cohort was enriched with individuals with abnormal DAT binding at baseline. Motor and nonmotor measures were compared across groups. DAT specific binding ratios (SBR) were used to calculate the percent of expected DAT binding for age and sex using normative data from HCs. Receiver operative characteristic analyses identified a baseline DAT binding cutoff that distinguishes iRBD participants diagnosed with an aSN in follow‐up versus those not diagnosed. Results The sample included 38 with iRBD, 205 with PD, and 92 HC who underwent DAT‐SPECT at baseline. Over 4.7 years of mean follow‐up, 14 (36.84%) with iRBD were clinically diagnosed with aSN. Risk of aSN diagnosis was significantly elevated among those with baseline putamen SBR ≤ 48% of that expected for age and sex, relative to those above this cutoff (hazard ratio = 17.8 [95%CI: 3.79–83.3], P = 0.0003). Conclusion We demonstrate the utility of DAT SBR to identify individuals with iRBD with increased short‐term risk of an aSN diagnosis.

ObjectiveTo examine the baseline prevalence and longitudinal evolution in non-motor symptoms (NMS) in a prospective cohort of, at baseline, patients with de novo Parkinson’s disease (PD) compared with healthy controls (HC).MethodsParkinson’s Progression Markers Initiative (PPMI) is a longitudinal, ongoing, controlled study of de novo PD participants and HC. NMS were rated using the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Part I score and other validated NMS scales at baseline and after 2 years. Biological variables included cerebrospinal fluid (CSF) markers and dopamine transporter imaging.Results423 PD subjects and 196 HC were enrolled and followed for 2 years. MDS-UPDRS Part I total mean (SD) scores increased from baseline 5.6 (4.1) to 7.7 (5.0) at year 2 in PD subjects (p<0.001) versus from 2.9 (3.0) to 3.2 (3.0) in HC (p=0.38), with a significant difference between the groups (p<0.001). In the multivariate analysis, higher baseline NMS score was associated with female sex (p=0.008), higher baseline MDS-UPDRS Part II scores (p<0.001) and more severe motor phenotype (p=0.007). Longitudinal increase in NMS severity was associated with the older age (0.008) and lower CSF Aβ1–42 (0.005) at baseline. There was no association with the dose or class of dopaminergic therapy.ConclusionsThis study of NMS in early PD identified clinical and biological variables associated with both baseline burden and predictors of progression. The association of a greater longitudinal increase in NMS with lower baseline Aβ1–42 level is an important finding that will have to be replicated in other cohorts.Trial registrationClinicalTrials.gov identifier: NCT01141023.

Alpha-synuclein seed amplification assays (αSyn-SAAs) are promising diagnostic tools for Parkinson’s disease (PD) and related synucleinopathies. They enable detection of seeding-competent alpha-synuclein aggregates in living patients and have shown high diagnostic accuracy in several PD and other synucleinopathy patient cohorts. However, there has been confusion about αSyn-SAAs for their methodology, nomenclature, and relative accuracies when performed by various laboratories. We compared αSyn-SAA results obtained from three independent laboratories to evaluate reproducibility across methodological variations. We utilized the Parkinson’s Progression Markers Initiative (PPMI) cohort, with DATSCAN data available for comparison, since clinical diagnosis of early de novo PD is critical for neuroprotective trials, which often use dopamine transporter imaging to enrich their cohorts. Blinded cerebrospinal fluid (CSF) samples for a randomly selected subset of PPMI subjects (30 PD, 30 HC, and 20 SWEDD), from both baseline and year 3 collections for the PD and HC groups (140 total CSF samples) were analyzed in parallel by each lab according to their own established and optimized αSyn-SAA protocols. The αSyn-SAA results were remarkably similar across laboratories, displaying high diagnostic performance (sensitivity ranging from 86 to 96% and specificity from 93 to 100%). The assays were also concordant for samples with results that differed from clinical diagnosis, including 2 PD patients determined to be clinically inconsistent with PD at later time points. All three assays also detected 2 SWEDD subjects as αSyn-SAA positive who later developed PD with abnormal DAT-SPECT. These multi-laboratory results confirm the reproducibility and value of αSyn-SAA as diagnostic tools, illustrate reproducibility of the assay in expert hands, and suggest that αSyn-SAA has potential to provide earlier diagnosis with comparable or superior accuracy to existing methods.

To assess the neurobiological substrate of initial cognitive decline in Parkinson's disease (PD) to inform patient management, clinical trial design, and development of treatments. We longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition. Additionally, longitudinal structural MRI and DAT scan data were included. Univariate analyses were run initially, with false discovery rate = 0.2, to select biomarker variables for inclusion in multivariable longitudinal mixed-effect models. By year 3, cognitive impairment was diagnosed in 15-38% participants depending on the criteria applied. Biomarkers, some longitudinal, predicting cognitive impairment in multivariable models were: (1) dopamine deficiency (decreased caudate and putamen DAT availability); (2) diffuse, cortical decreased brain volume or thickness (frontal, temporal, parietal, and occipital lobe regions); (3) co-morbid Alzheimer's disease Aβ amyloid pathology (lower CSF Aβ 1-42); and (4) genes (COMT val/val and BDNF val/val genotypes). Cognitive impairment in PD increases in frequency 50-200% in the first several years of disease, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer's disease plaque pathology, and genetic factors.

Objective To determine clinical and biological variables that predict time to initiation of symptomatic therapy in de novo Parkinson's disease patients. Methods Parkinson's Progression Markers Initiative is a longitudinal case–control study of de novo, untreated Parkinson's disease participants at enrolment. Participants contribute a wide range of motor and non‐motor measures, including biofluids and imaging biomarkers. The machine learning method of random survival forests was used to examine the ability of baseline variables to predict time to initiation of symptomatic therapy since study enrollment (baseline). Results There were 423 PD participants enrolled in PPMI and 33 initial baseline variables. Cross‐validation results showed that the three‐predictor subset of disease duration (time from diagnosis to enrollment), the modified Schwab and England activities of daily living scale, and the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS‐UPDRS) total score modestly predicted time to initiation of symptomatic therapy (C = 0.70, pseudo‐R2 = 0.13). Prediction using the three variables was similar to using the entire set of 33. None of the biological variables increased accuracy of the prediction. A prognostic index for time to initiation of symptomatic therapy was created using the linear and nonlinear effects of the three top variables based on a post hoc Cox model. Interpretation Our findings using a novel machine learning method support previously reported clinical variables that predict time to initiation of symptomatic therapy. However, the inclusion of biological variables did not increase prediction accuracy. Our prognostic index constructed, based on the group‐level survival curve can provide an indication of the risk of initiation of ST for PD patients based on functions of the three top predictors.

Background Efforts to identify fluid biomarkers of Parkinson’s disease (PD) have intensified in the last decade. As the role of inflammation in PD pathophysiology becomes increasingly recognized, investigators aim to define inflammatory signatures to help elucidate underlying mechanisms of disease pathogenesis and aid in identification of patients with inflammatory endophenotypes that could benefit from immunomodulatory interventions. However, discordant results in the literature and a lack of information regarding the stability of inflammatory factors over a 24-h period have hampered progress. Methods Here, we measured inflammatory proteins in serum and CSF of a small cohort of PD ( n  = 12) and age-matched healthy control (HC) subjects ( n  = 6) at 11 time points across 24 h to (1) identify potential diurnal variation, (2) reveal differences in PD vs HC, and (3) to correlate with CSF levels of amyloid β (Aβ) and α-synuclein in an effort to generate data-driven hypotheses regarding candidate biomarkers of PD. Results Despite significant variability in other factors, a repeated measures two-way analysis of variance by time and disease state for each analyte revealed that serum IFNγ, TNF, and neutrophil gelatinase-associated lipocalin (NGAL) were stable across 24 h and different between HC and PD. Regression analysis revealed that C-reactive protein (CRP) was the only factor with a strong linear relationship between CSF and serum. PD and HC subjects showed significantly different relationships between CSF Aβ proteins and α-synuclein and specific inflammatory factors, and CSF IFNγ and serum IL-8 positively correlated with clinical measures of PD. Finally, linear discriminant analysis revealed that serum TNF and CSF α-synuclein discriminated between PD and HC with a minimum of 82% sensitivity and 83% specificity. Conclusions Our findings identify a panel of inflammatory factors in serum and CSF that can be reliably measured, distinguish between PD and HC, and monitor inflammation as disease progresses or in response to interventional therapies. This panel may aid in generating hypotheses and feasible experimental designs towards identifying biomarkers of neurodegenerative disease by focusing on analytes that remain stable regardless of time of sample collection.

Several characteristics associated with increased risk for Parkinson's disease (PD) have been identified, including specific genotypes and various non-motor symptoms. Characterizing non-motor features, such as cognitive abilities, among individuals considered at-risk for PD is essential to improving prediction of future neurodegeneration. Participants belonging to the following cohorts of the Parkinson Progression Markers Initiative (PPMI) study were included: de novo PD with dopamine transporter binding deficit (n = 423), idiopathic REM sleep behavior disorder (RBD, n = 39), hyposmia (n = 26) and non-PD mutation carrier (NMC; Leucine-rich repeat kinase 2 (LRRK2) G2019S (n = 88) and glucocerebrosidase (GBA) gene (n = 38) mutations)). Inclusion criteria enriched the RBD and hyposmia cohorts, but not the NMC cohort, with individuals with dopamine transporter binding deficit. Baseline neuropsychological performance was compared, and analyses were adjusted for age, sex, education, and depression. The RBD cohort performed significantly worse than the hyposmia and NMC cohorts on Symbol Digit Modality Test (mean (SD) 32.4 (9.16) vs. 41.8 (9.98), p = 0.002 and vs. 45.2 (10.9), p<0.001) and Judgment of Line Orientation (11.3 (2.36) vs.12.9 (1.87), p = 0.004 and vs. 12.9 (1.87), p<0.001). The RBD cohort also performed worse than the hyposmia cohort on the Montreal Cognitive Assessment (25.5 (4.13) vs. 27.3 (1.71), p = 0.02). Hyposmics did not differ from PD or NMC cohorts on any cognitive test score. Among individuals across a spectrum of risk for PD, cognitive function is worse among those with the characteristic most strongly associated with future risk of PD or dementia with Lewy bodies, namely RBD.

To provide a comprehensive description of disease progression in synuclein seeding assay (SAA) positive sporadic Parkinson Disease participants, using Neuronal Synuclein Disease integrated biological and functional impairment staging framework. We analyzed 5-year longitudinal data from 345 participants recruited in the Parkinson's Progression Markers Initiative with the diagnosis of early (less than 2 years of clinical diagnosis at baseline and untreated) sporadic Parkinson's Disease, who were synuclein seeding assay positive. We assessed 5-year progression in a spectrum of clinical and biomarker measures. We used Cox proportional hazards models to assess the association between baseline stage and time to survival, postural instability, cognitive impairment, and other meaningful milestones. Biomarker analysis included dopamine transporter binding measures, CSF-SAA, amyloid-beta, phosphorylated tau and total tau, as well as serum urate, and neurofilament light chain. At baseline there was clear separation of participants by Neuronal Synuclein Disease Stages (23% Stage 2b, 67% Stage 3, 10% Stage 4). Participants in stage 4 at baseline had a significantly higher rate of reaching disability, postural instability, cognitive decline, and the autonomic dysfunction milestones. There was a stage-dependent increase in dopamine deficit at baseline. There was no difference in fluid biomarkers between the stages at baseline and longitudinally. This study highlights the heterogeneity in the early Parkinson's Disease population defined by clinical diagnostic criteria and underscores the importance of shifting from clinical to biologically and functional impairment defined inclusion criteria for clinical trials. Biological drivers of stage heterogeneity must be further explored.

Objectives Detection of α‐synuclein aggregates by seed amplification is a promising Parkinson disease biomarker assay. Understanding intraindividual relationships of α‐synuclein measures could inform optimal biomarker development. The objectives were to test accuracy of α‐synuclein seed amplification assay in central (cerebrospinal fluid) and peripheral (submandibular gland) sources, compare to total α‐synuclein measures, and investigate within‐subject relationships. Methods The Systemic Synuclein Sampling Study aimed to characterize α‐synuclein in multiple tissues and biofluids within Parkinson disease subjects (n = 59) and compared to healthy controls (n = 21). Motor and non‐motor measures and dopamine transporter scans were obtained. Four measures of α‐synuclein were compared: seed amplification assay in cerebrospinal fluid and formalin‐fixed paraffin‐embedded submandibular gland, total α‐synuclein quantified in biofluids using enzyme‐linked immunoassay, and aggregated α‐synuclein in submandibular gland detected by immunohistochemistry. Accuracy of seed amplification assay for Parkinson disease diagnosis was examined and within‐subject α‐synuclein measures were compared. Results Sensitivity and specificity of α‐synuclein seed amplification assay for Parkinson disease diagnosis was 92.6% and 90.5% in cerebrospinal fluid, and 73.2% and 78.6% in submandibular gland, respectively. 25/38 (65.8%) Parkinson disease participants were positive for both cerebrospinal fluid and submandibular gland seed amplification assay. Comparing accuracy for Parkinson disease diagnosis of different α‐synuclein measures, cerebrospinal fluid seed amplification assay was the highest (Youden Index = 83.1%). 98.3% of all Parkinson disease cases had ≥1 measure of α‐synuclein positive. Interpretation α‐synuclein seed amplification assay (cerebrospinal fluid>submandibular gland) had higher sensitivity and specificity compared to total α‐synuclein measures, and within‐subject relationships of central and peripheral α‐synuclein measures emerged.