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Objective: Given the clinical heterogeneity of Parkinson’s disease (PD), identification of early -stage subgroups with shared non-motor symptom (NMS) profiles may clarify its pathophysiology. This study used latent-profile analyses (LPA) to define subgroups based on sleep disturbances, cognitive performance and neuropsychiatric symptoms, and examined dopaminergic function and brain volume differences between them.

Methods: We analyzed data from 51 cognitively normal non-PD older adults and 105 early-stage PD participants from the iPARK trial, including 19 who underwent [11C]-raclopride PET/MR. Participants completed the Hospital Anxiety and Depression Scale, the short version of the Karolinska Sleep Questionnaire and a battery of neuropsychological tests. LPA were used in PD to identify subgroups based on NMS profiles, which were then characterized and examined in relation to dopaminergic integrity and brain morphology.

Results: LPA identified a two-cluster solution as the best fit. Group 1 (N = 49) showed poorer working memory, executive function and processing speed along with greater daytime sleepiness, depression and anxiety. Group 2 (N = 56) exhibited less affected cognitive function and minimal NMS. Groups were similar in demographics, disease duration, motor symptom severity and medication, but differed on UPDRS-1 NMS. Group 1 demonstrated significantly reduced [11C]-raclopride binding potential compared to Group 2 in the left putamen at both ROI- and voxel-wise analysis.

Conclusion: These findings indicate clinically distinct subgroups in early-stage PD. Greater NMS burden is linked to impaired dopaminergic integrity, suggesting a potential neurobiological signature. Early identification of such subgroups may improve understanding of disease heterogeneity and support personalized management and interventions. Clinical trial registration: https://clinicaltrials.gov/study/NCT03680170?id=NCT03680170&rank=1, identifier (NCT03680170).

Beta-adrenoceptor-blockers and agonists have been associated with an increased and decreased risk of Parkinson's disease (PD), respectively. We aimed to investigate whether these medications are linked to clinical heterogeneity and progression in PD. Longitudinal data from the Parkinson's Incident Cohorts Collaboration (n = 1107) were analysed. Baseline clinical status and progression to Hoehn & Yahr stage 3 (H&Y3) or dementia were compared in beta-blocker or beta-agonist users versus non-users of each drug. Baseline motor and cognitive variables were similar in beta-blocker users (n = 195) versus non-users and beta-agonist users (n = 68) versus non-users, following adjustment for relevant confounders. Beta-blocker users (n = 156) progressed faster to H&Y3 (p = 0.002), accounting for relevant confounders (Hazard Ratio (HR) = 1.538; p = 0.011), while beta-agonist users (n = 54) progressed similarly to non-users. Neither drug was associated with progression to dementia. These findings support the possibility that beta-adrenoceptor drugs may have potential in modifying aspects of PD progression. Further investigation is essential to identify any causative component in the relationship.

PURPOSE: The effect of mandibular advancement device therapy on daytime sleepiness remains unclear. Here, we evaluate the effect of a mandibular advancement device on daytime sleepiness using the Karolinska Sleepiness Scale.

METHODS: We randomized 88 snoring patients with an apnea-hypopnea index < 30 and daytime sleepiness to a mandibular advancement device or a sham device for four months. The Karolinska Sleepiness Scale, which measures grades of sleepiness from 1 (very alert) to 9 (very sleepy), was used for seven consecutive days, four times each day. The results were analyzed with quantile regression at quartiles controlling for baseline, age, body mass index (kg/m²), sex, apnea-hypopnea index, and full-time work.

RESULTS: The Karolinska Sleepiness Scale score was lower with the mandibular advancement device than with the sham device at specific time intervals. The positive effect of mandibular advancement device therapy occurred at wake up and before lunch during the whole week and before lunch on weekdays at the middle quartile. The adjusted differences between the interventions favored mandibular advancement device therapy by almost one unit and normalized the Karolinska Sleepiness Scale scores at wake up and before lunch. In addition, there were positive effects of mandibular advancement device therapy before dinner at the highest quartile during the whole week, on weekdays, and on the weekend.

CONCLUSION: Mandibular advancement devices used for snoring and sleep apnea reduce daytime sleepiness, particularly at wake up and before lunch, but provide some benefit before dinner.

Background: Prediction models for dementia in Parkinson disease (PD) are needed to better identify high-risk patients, but existing risk models often lack validation in early-stage PD, when prognosis is most challenging.

Objective: This study aims to validate the Montreal Parkinson Risk of Dementia Scale (MoPaRDS) in six population-based cohorts of newly diagnosed PD and to evaluate if incorporating genetic factors (GBA1 and APOE-ε4) enhances its performance.

Methods: We calculated MoPaRDS scores for 1108 newly diagnosed PD patients, and MoPaRDS + GBA1 + APOE for the 941 patients with complete genetic data. We assessed the scores' performance in predicting dementia diagnosed over 10 years using time-dependent receiver operating characteristic (ROC) curves.

Results: Of the 1108 patients (mean age 69.5 ± 10.0 years; 61.0% men), 350 (31.6%) developed dementia. The area under the time-dependent ROC curve (AUC) was 0.79 for MoPaRDS and 0.80 for MoPaRDS + GBA1 + APOE. Subdividing patients based on their MoPaRDS scores revealed annual observed risks of PDD of 39.4% (n = 8; high risk-), 11.4% (n = 176; intermediate risk-), and 5.0% (n = 942; low risk-group). With the suggested cutoff of ≥4, MoPaRDS had a sensitivity of 21.7% and specificity of 94.9%. Including the genetic items improved the sensitivity to 36.4% while maintaining comparable performance for specificity (91.5%).

Conclusions: MoPaRDS demonstrates high specificity but limited sensitivity in early PD, highlighting that a one-size-fits-all approach is inadequate for predicting dementia risk in PD across different disease stages. Integrating genetic items increases sensitivity and identifies more newly diagnosed patients at higher risk of dementia, and may be a useful approach to assist dementia risk assessment in early-stage PD.

Background: Alterations in gut microbiota are observed in Parkinson's disease (PD). Previous studies on microbiota-derived metabolites in PD were small-scale and post-diagnosis, raising concerns about reverse causality.

Objectives: Our goal was to prospectively investigate the association between plasma microbial metabolites and PD risk within a metabolomics framework.

Methods: A nested case–control study within the prospective EPIC4PD cohort, measured pre-diagnostic plasma microbial metabolites using untargeted metabolomics.

Results: Thirteen microbial metabolites were identified nominally associated with PD risk (P-value < 0.05), including amino acids, bile acid, indoles, and hydroxy acid, although none remained significant after multiple testing correction. Three pathways were implicated in PD risk: valine, leucine, and isoleucine degradation, butanoate metabolism, and propanoate metabolism. PD-associated microbial pathways were more pronounced in men, smokers, and overweight/obese individuals.

Conclusion: Changes in microbial metabolites may represent a pre-diagnostic feature of PD. We observed biologically plausible associations between microbial pathways and PD, potentially influenced by individual characteristics.

Background: Synaptic dysfunction and degeneration are central contributors to the pathogenesis and progression of parkinsonian disorders. Therefore, identification and validation of biomarkers reflecting pathological synaptic alterations are greatly needed and could be used in prognostic assessment and to monitor treatment effects.

Objective: To explore candidate biomarkers of synaptic dysfunction in Parkinson's disease (PD) and related disorders.

Methods: Mass spectrometry was used to quantify 15 synaptic proteins in two clinical cerebrospinal fluid (CSF) cohorts, including PD (n1 = 51, n2 = 101), corticobasal degeneration (CBD) (n1 = 11, n2 = 3), progressive supranuclear palsy (PSP) (n1 = 22, n2 = 21), multiple system atrophy (MSA) (n1 = 31, n2 = 26), and healthy control (HC) (n1 = 48, n2 = 30) participants, as well as Alzheimer's disease (AD) (n2 = 23) patients in the second cohort.

Results: Across both cohorts, lower levels of the neuronal pentraxins (NPTX; 1, 2, and receptor) were found in PD, MSA, and PSP, compared with HC. In MSA and PSP, lower neurogranin, AP2B1, and complexin-2 levels compared with HC were observed. In AD, levels of 14-3-3 zeta/delta, beta- and gamma-synuclein were higher compared with the parkinsonian disorders. Lower pentraxin levels in PD correlated with Mini-Mental State Exam scores and specific cognitive deficits (NPTX2; rho = 0.25–0.32, P < 0.05) and reduced dopaminergic pre-synaptic integrity as measured by DaTSCAN (NPTX2; rho = 0.29, P = 0.023). Additionally, lower levels were associated with the progression of postural imbalance and gait difficulty symptoms (All NPTX; β-estimate = −0.025 to −0.038, P < 0.05) and cognitive decline (NPTX2; β-estimate = 0.32, P = 0.021).

Conclusions: These novel findings show different alterations of synaptic proteins in parkinsonian disorders compared with AD and HC. The neuronal pentraxins may serve as prognostic CSF biomarkers for both cognitive and motor symptom progression in PD. 

Background: There is a need to better understand the rate of cognitive and motor decline of Dementia with Lewy bodies (DLB) and Parkinson's disease Dementia (PDD).

Objectives: To compare the rate of cognitive and motor decline in patients with DLB and PDD from the E-DLB Consortium and the Parkinson's Incidence Cohorts Collaboration (PICC) Cohorts.

Methods: The annual change in MMSE and MDS-UPDRS part III was estimated using linear mixed regression models in patients with at least one follow-up (DLB n = 837 and PDD n = 157).

Results: When adjusting for confounders, we found no difference in the annual change in MMSE between DLB and PDD (−1.8 [95% CI −2.3, −1.3] vs. −1.9 [95% CI −2.6, −1.2] [P = 0.74]). MDS-UPDRS part III showed nearly identical annual changes (DLB 4.8 [95% CI 2.1, 7.5]) (PDD 4.8 [95% CI 2.7, 6.9], [P = 0.98]).

Conclusions: DLB and PDD showed similar rates of cognitive and motor decline. This is relevant for future clinical trial designs.

Purpose: This study estimated epilepsy prevalence, psychiatric co-morbidity and annual costs associated with epilepsy.

Methods: We used Danish national health registers to identify persons diagnosed with epilepsy and psychiatric disorders, and persons using antiseizure medication and persons using drugs for psychiatric disorders. We calculated the prevalence of epilepsy and co-morbid psychiatric disorders in Denmark on December 31, 2016, using information on epilepsy and psychiatric disorders based on combinations of hospital contacts and use of antiseizure and psychoactive medication. Further, direct and indirect annual costs associated with epilepsy were calculated using individual-level data from a range of socioeconomic registers.

Results: There were 5,044,367 persons alive and living in Denmark on December 31, 2016, including 33,628 persons with at least one hospital contact with epilepsy in the previous five years (epilepsy prevalence 0.67% (0.69% males; 0.65% females)). Among these persons with epilepsy, we identified 12,562 (37.4%) persons with a psychiatric disorder or use of drugs used for psychiatric disorders as compared with 801,052 (15.9%) persons in the general population. The estimated total annual individual net costs associated with epilepsy was €30,683. Compared with prevalence estimates on December 31, 2006, the prevalence of epilepsy on December 31, 2016, was slightly higher in the older population and slightly lower in children

Conclusions: Population estimates from national registers provide epilepsy prevalence estimates of approximately 0.6–0.7% - similar to previous reviews of epilepsy prevalence. In addition, the national sample allowed idenitfication of high prevalence of psychiatric disorders and high societal costs associated with epielspy.

Background: Parkinson's disease (PD), progressive supranuclear palsy (PSP), and multiple system atrophy (MSA) present with similar movement disorder symptoms but distinct protein aggregates upon pathological examination.

Objective: Discovery and validation of candidate biomarkers in parkinsonian disorders for differential diagnosis of subgroup molecular etiologies.

Methods: Untargeted liquid chromatography (LC)-mass spectrometry (MS) proteomics was used for discovery profiling in cerebral spinal fluid (CSF) followed by LC-MS/MS based multiple reaction monitoring for validation of candidates. We compared clinical variation within the parkinsonian cohort including PD subgroups exhibiting tremor dominance (TD) or postural instability gait disturbance and those with detectable leukocytes in CSF.

Results: We have identified candidate peptide biomarkers and validated related proteins with targeted quantitative multiplexed assays. Dopamine-drug naïve patients at first diagnosis exhibit reduced levels of signaling neuropeptides, chaperones, and processing proteases for packaging of self-aggregating peptides into dense core vesicles. Distinct patterns of biomarkers were detected in the parkinsonian disorders but were not robust enough to offer a differential diagnosis. Different biomarker changes were detected in male and female patients with PD. Subgroup specific candidate biomarkers were identified for TD PD and PD patients with leukocytes detected in CSF.

Conclusion: PD, MSA, and PSP exhibit overlapping as well as distinct protein biomarkers that suggest specific molecular etiologies. This indicates common sensitivity of certain populations of selectively vulnerable neurons in the brain, and distinct therapeutic targets for PD subgroups. Our report validates a decrease in CSF levels of self-aggregating neuropeptides in parkinsonian disorders and supports the role of native amyloidogenic proteins in etiologies of neurodegenerative diseases.