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BACKGROUND AND OBJECTIVE: Parkinsonian disorders, including Parkinsons disease (PD), multiple system atrophy (MSA), dementia with Lewy bodies (DLB), progressive supranuclear palsy (PSP), and corticobasal syndrome (CBS), exhibit overlapping early-stage symptoms, complicating definitive diagnosis despite heterogeneous cellular and regional pathophysiology. Additionally, the progression and the eventual conversion of prodromal conditions such as REM behavior disorder (RBD) to PD, MSA, or DLB remain challenging to predict. Extracellular vesicles (EVs) are small, membrane-enclosed structures released by cells, playing a vital role in communicating cell-state-specific messages. Due to their ability to cross the blood-brain barrier into the peripheral circulation, measuring biomarkers in blood-isolated speculative CNS enriched EVs has become a popular diagnostic approach. However, replication and independent validation remain challenging in this field. Here, we aimed to evaluate the diagnostic accuracy of speculative CNS-enriched EVs for parkinsonian disorders. METHODS: We conducted a PRISMA-guided systematic review and meta-analysis, covering 18 studies with a total of 1695 patients with PD, 253 with MSA, 21 with DLB, 172 with PSP, 152 with CBS, 189 with RBD, and 1288 HCs, employing either hierarchical bivariate models or univariate models based on study size. RESULTS: Diagnostic accuracy was moderate for differentiating patients with PD from HCs, but revealed high heterogeneity and significant publication bias, suggesting an inflation of the perceived diagnostic effectiveness. The bias observed indicates that studies with non-significant or lower effect sizes were less likely to be published. Although results for differentiating patients with PD from those with MSA or PSP and CBS appeared promising, their validity is limited due to the small number of involved studies coming from the same research group. Despite initial reports, our analyses suggest that using speculative CNS-enriched EV biomarkers may not reliably differentiate patients with MSA from HCs or patients with RBD from HCs, due to their lesser accuracy and substantial variability among the studies, further complicated by substantial publication bias. CONCLUSION: Our findings underscore the moderate, yet unreliable diagnostic accuracy of biomarkers in speculative CNS-enriched EVs in differentiating parkinsonian disorders, highlighting the presence of substantial heterogeneity and significant publication bias. These observations reinforce the need for larger, more standardized, and unbiased studies to validate the utility of these biomarkers but also call for the development of better biomarkers for parkinsonian disorders.

While Parkinsons disease remains clinically defined by cardinal motor symptoms resulting from nigrostriatal degeneration, it is now appreciated that the disease commonly consists of multiple pathologies, but it is unclear where these co-pathologies occur early in disease and whether they are responsible for the nigrostriatal degeneration. For the past number of years, we have been studying a well-characterized cohort of subjects with motor impairment that we have termed mild motor deficits. Motor deficits were determined on a modified and validated Unified Parkinsons Disease Rating Scale III but were insufficient in degree to diagnose Parkinsons disease. However, in our past studies, cases in this cohort had a selection bias, as both a clinical syndrome in between no motor deficits and Parkinsons disease, plus nigral Lewy pathology as defined post-mortem, were required for inclusion. Therefore, in the current study, we only based inclusion on the presence of a clinical phenotype with mild motor impairment insufficient to diagnose Parkinsons disease. Then, we divided this group further based upon whether or not subjects had a synucleinopathy in the nigrostriatal system. Here we demonstrate that loss of nigral dopaminergic neurons, loss of putamenal dopaminergic innervation and loss of the tyrosine hydroxylase-phenotype in the substantia nigra and putamen occur equally in mild motor deficit groups with and without nigral alpha-synuclein aggregates. Indeed, the common feature of these two groups is that both have similar degrees of AT8 positive phosphorylated tau, a pathology not seen in the nigrostriatal system of age-matched controls. These findings were confirmed with early (tau Ser208 phosphorylation) and late (tau Ser396/Ser404 phosphorylation) tau markers. This suggests that the initiation of nigrostriatal dopaminergic neurodegeneration occurs independently of alpha-synuclein aggregation and can be tau mediated.

\n Digital self-management tools including mobile apps and wearables can enhance personalized care in Parkinson’s disease, and incorporating patient and clinician feedback into their evaluation can empower users and nurture patient-clinician relationships, necessitating a review to assess the state of the art and refine their use.This review aimed to summarize the state of the art of self-management systems used in Parkinson’s disease management, detailing the application of self-management techniques and the integration of clinicians. It also aimed to provide a concise synthesis on the acceptance and usability of these systems from the clinicians’ standpoint, reflecting both patient engagement and clinician experience.The review was organized following the PRISMA extension for Scoping Reviews and PICOS frameworks. Studies were retrieved from PubMed, CINAHL, Scopus, ACM Digital Library, and IEEE Xplore. Data was collected using a predefined form and then analyzed descriptively.Of the 15,231 studies retrieved, 33 were included. Five technology types were identified, with systems combining technologies being the most evaluated. Common self-management strategies included educational material and symptom journals. Only 11 studies gathered data from clinicians or reported evidence of clinician integration; out of those, six studies point out the importance of raw data availability, data visualization, and integrated data summaries.While self-management systems for Parkinson’s disease are well-received by patients, the studies underscore the urgency for more research into their usability for clinicians and integration into daily medical workflows to enhance overall care quality.Digital tools, such as smartphone applications and wearable devices, could help people with Parkinson’s disease manage their symptoms by using data and technology to provide support that is personalized to them and by supporting communication between patients and healthcare providers. This review studies current literature on these digital self-management systems for people with Parkinson’s disease. Of the 33 studies included in our review, we found that many of these systems combine different types of digital technologies (for example, a mobile app and a wearable sensor). The most common strategies to help support patients with self-management included in these digital tools were providing educational health content and symptom diaries. Only a few studies have considered healthcare providers’ perspectives on these systems. Those that did highlighted a need for better access to patient data, improved data presentation, and summaries of key health insights. While patients find digital self-management tools favorable, further research is needed to ensure they meet healthcare providers’ professional needs and can fit easily into daily clinical routines, ultimately improving care for individuals with Parkinson’s disease. [ABSTRACT FROM AUTHOR]

We report on a patient with ciltacabtagene autoleucel-induced movement and neurocognitive toxicity, which was refractory to immunosuppression but responsive to combination dopaminergic therapy (carbidopa/levodopa, ropinirole, amantadine). Response was seen upon both initial treatment and rechallenge after unintended withdrawal. This is the first report of a successful symptomatic treatment of this well-described neurotoxic syndrome. [ABSTRACT FROM AUTHOR]

Background: Multiple system atrophy (MSA), an atypical parkinsonian syndrome, is a rapidly progressive neurodegenerative disease with currently no established fluid biomarkers available. MSA is characterized by an oligodendroglial α-synucleinopathy, progressive neuronal cell loss and concomitant astrocytosis. Here, we investigate glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) as fluid biomarkers for differential diagnosis, assessment of clinical disease severity and prediction of disease progression in MSA. Methods: GFAP and NfL levels were analyzed in plasma and CSF samples of 47 MSA patients as well as 24 Parkinson's disease (PD) and 25 healthy controls (HC) as reference cohorts. In MSA, biomarker levels were correlated to baseline and longitudinal clinical disease severity (UMSARS scores). Results: In MSA, GFAP levels in CSF and plasma predicted baseline clinical disease severity as indicated by UMSARS scores, while NfL levels predicted clinical disease progression as indicated by longitudinal changes in UMSARS scores. Cross-sectionally, NfL levels in CSF and plasma were significantly elevated in MSA compared to both PD and HC. Receiver operating curves (ROC) indicated high diagnostic accuracy of NfL for distinguishing MSA from PD (CSF: AUC = 0.97, 95% CI 0.90–1.00; plasma: AUC = 0.90, 95% CI 0.81–1.00). Discussion: In MSA, GFAP shows promise as novel biomarker for assessing current clinical disease severity, while NfL might serve as biomarker for prediction of disease progression and differential diagnosis of MSA against PD. [ABSTRACT FROM AUTHOR]

Background: Epidemiological studies on multisystem atrophy (MSA) are scarce. Our aim has been to analyse 10-year incidence, point prevalence, survival, and the time to diagnosis of MSA in Navarre, a northern Spanish region. Methods: This is a population-based observational retrospective study, from 2012 to 2021, which covered the population of Navarre (followed until 31 December 2021). Data from various sources of health information were reviewed in order to identify all potential diagnoses of MSA, that were validated from medical records. Patients were included if they fulfilled the new Movement Disorder Society criteria. Results: We observed a crude average annual incidence rate (IR) of 0.49/100,000 person-years, with the highest occurring in the age group of 60–69 years. No significant IR differences by sex or subtype were observed. Point prevalence in December 2021 was 2.43/100,000 inhabitants. Joinpoint analysis for global incidence and prevalence experienced stable annual rates during the whole period, showing an upward trend for prevalence without a statistically significant slop. The median age at symptom onset was 65 years (range 47–76). The median time to diagnosis was 36 months, without statistically significant differences between sex, age at diagnosis or subtypes. Median time of survival from clinical onset was 7 years. Age of onset above 70 years and autonomic onset were associated with reduced survival. Conclusions: This is the first population-based epidemiological study on MSA in Spain. It provides detailed incidence and prevalence data for MSA that may be useful for appropriate management of health resources. [ABSTRACT FROM AUTHOR]