As cognitive-driven worsening of activities of the daily living (ADL) in Parkinson's disease (PD) is the core feature of PD dementia (PDD), there is great need for sensitive quantitative assessment. ...Aim of our study was the evaluation of cognitive-driven worsening of ADL by the performance-based Multiple Object Test (MOT), offering an essential clinical advantage as it is quick and easy to apply in a clinical context even on severely impaired patients.
73 PD patients were assessed longitudinally over a period of 37 (6-49) months. According to their neuropsychological profile the sample was divided into two groups: PD patients with (n = 34, PD-CI) and without cognitive impairment (n = 39, PD-noCI). The MOT comprises five routine tasks (e.g. to make coffee) quick and easy to apply. Quantitative (total error number, processing time) and qualitative parameters (error type) were analyzed using non-parametric test statistic (e.g.Wilcoxon signed-rank test, binary logistic regression).
Median number of total errors (p = 0.001), processing time (p<0.001), perplexity (p = 0.035), and omission errors (p<0.001) increased significantly from baseline to follow-up in the total sample. Worsening of MOT performance was correlated to cognitive decline in the attention/ executive function and visuo-constructive domain. PD-CI showed an increase in omission errors (p = 0.027) compared to PD-noCI over time. This increase in omission errors between visits was further identified as a risk marker for PDD conversion.
The MOT, especially frequency of omission errors, is a promising tool to rate PD patients objectively and might help to identify patients with a high risk for having mild cognitive impairment or dementia.
Gait changes occur during all Parkinson's disease (PD) stages and wearable sensor-derived gait parameters may quantify PD progression. However, key aspects that may qualify quantitative gait ...parameters as progression markers in PD remain elusive.
Longitudinal changes in gait parameters from a lower-back sensor under convenient and challenging walking conditions in early- and mid-stage PD patients (E-PD, M-PD) compared to controls were investigated.
Normal- and fast-pace parameters (step: number, time, velocity, variability) were assessed every 6 months for up to 5 years in 22 E-PD (<4 years baseline disease duration), 18 M-PD (>5 years) and 24 controls. Parameter trajectories and associations with MDS-UPDRS-III were tested using generalized estimating equations.
Normal-pace step number (annual change in E-PD: 2.1%, Time
Group:
= 0.001) and step time variability (8.5%,
< 0.05) longitudinally increased in E-PD compared to controls (0.7%, -12%). For fast pace, no significant progression differences between groups were observed. Longitudinal changes in M-PD did not differ significantly from controls. MDS-UPDRS-III was largely associated with normal-pace parameters in M-PD.
Wearables can quantify progressive gait deficits indicated by increasing step number and step time variability in E-PD. In M-PD, and for fast-pace, gait parameters possess limited potential as PD progression markers.
Fecal calprotectin is an established marker of gut inflammation in inflammatory bowel disease (IBD). Elevated levels of fecal calprotectin as well as gut microbial dysbiosis have also been observed ...in other clinical conditions. However, systemic and multi-omics alterations linked to elevated fecal calprotectin in older individuals remain unclear. This study comprehensively investigated the relationship between fecal calprotectin levels, gut microbiome composition, serum inflammation and targeted metabolomics markers, and relevant lifestyle and medical data in a large sample of older individuals (n = 735; mean age ± SD: 68.7 ± 6.3) from the TREND cohort study. Low (0–50 μg/g; n = 602), moderate (> 50–100 μg/g; n = 64) and high (> 100 μg/g; n = 62) fecal calprotectin groups were stratified. Several pro-inflammatory gut microbial genera were significantly increased and short-chain fatty acid producing genera were decreased in high vs. low calprotectin groups. In serum, IL-17C, CCL19 and the toxic metabolite indoxyl sulfate were increased in high vs. low fecal calprotectin groups. These changes were partially mediated by the gut microbiota. Moreover, the high fecal calprotectin group showed increased BMI and a higher disease prevalence of heart attack and obesity. Our findings contribute to the understanding of fecal calprotectin as a marker of gut dysbiosis and its broader systemic and clinical implications in older individuals.
Carriers of GBA1 gene variants have a significant risk of developing Parkinson’s disease (PD). A cohort study of GBA carriers between 40−75 years of age was initiated to study the presence of ...prodromal PD features. Participants underwent non-invasive tests to assess different domains of PD. Ninety-eight unrelated GBA carriers were enrolled (43 males) at a median age (range) of 51 (40−74) years; 71 carried the N370S variant (c.1226A > G) and 25 had a positive family history of PD. The Montreal Cognitive Assessment (MoCA) was the most frequently abnormal (23.7%, 95% CI 15.7−33.4%), followed by the ultrasound hyperechogenicity (22%, 95% CI 14−32%), Unified Parkinson’s Disease Rating Scale part III (UPDRS-III) (17.2%, 95% CI 10.2−26.4%), smell assessment (12.4%, 95% CI 6.6−20.6%) and abnormalities in sleep questionnaires (11%, 95% CI 5.7−19.4%). Significant correlations were found between tests from different domains. To define the risk for PD, we assessed the bottom 10th percentile of each prodromal test, defining this level as “abnormal”. Then we calculated the percentage of “abnormal” tests for each subject; the median (range) was 4.55 (0−43.5%). Twenty-two subjects had more than 15% “abnormal” tests. The limitations of the study included ascertainment bias of individuals with GBA-related PD in relatives, some incomplete data due to technical issues, and a lack of well-characterized normal value ranges in some tests. We plan to enroll additional participants and conduct longitudinal follow-up assessments to build a model for identifying individuals at risk for PD and investigate interventions aiming to delay the onset or perhaps to prevent full-blown PD.
•Using a three-step screening approach, candidates with possible idiopathic RBD can be identified from the general community with >60% positive predictive value.•Compared to sleep center controls, ...newspaper-screened patients have similar neurodegeneration profile, although short-latency Parkinson's disease markers are slightly less common.•Approximately 60% of idiopathic RBD patients meet the criteria for prodromal PD.
Neuroprotective therapy for Parkinson's disease (PD) is most likely to be effective if provided in its prodromal stages. However, identifying prodromal PD is difficult because PD is relatively uncommon, and most markers are nonspecific. Rapid eye movement (REM) sleep behavior disorder (RBD) is by far the strongest clinical marker of prodromal PD, but most patients do not seek out medical attention. Developing an efficient way of diagnosing RBD from the general community may be the most practical method to detect prodromal PD.
We developed a screening strategy that began with a newspaper advertisement containing a single-question screen for RBD. All screen-positive subjects underwent an interview based on the Innsbruck RBD inventory aimed to optimize the positive predictive value. Those who passed both screens underwent confirmatory polysomnography. The proportion of screened RBD patients who met the International Parkinson and Movement Disorder Society (MDS) criteria for prodromal PD was assessed. A broad array of clinical markers of neurodegeneration was compared between newspaper-screened RBD patients and 130 RBD patients clinically referred to the sleep center.
Of 111 RBD-screen-positive participants, 40 (36%) passed the secondary screen, and 29 underwent full polysomnography. Of these 29 patients, 19 were ultimately proven to have RBD (PPV = 66%), 12 (63%) of whom met the criteria for prodromal PD. Compared to patients referred to the sleep center, newspaper-screened patients had similar age, sex, olfaction, autonomic function, and color vision. However, motor and cognitive assessments were slightly better in newspaper-screened patients.
A multistep screening approach using RBD screening questionnaires and telephone follow-up can efficiently identify prodromal PD in the general community.
Parkinson’s disease (PD) is marked by different kinds of pathological features, one hallmark is the aggregation of α-synuclein (aSyn). The development of aSyn pathology in the substantia nigra is ...associated to the manifestation of motor deficits at the time of diagnosis. However, most of the patients suffer additionally from non-motor symptoms, which may occur already in the prodromal phase of the disease years before PD is diagnosed. Many of these symptoms manifest in the gastrointestinal system (GIT) and some data suggest a potential link to the occurrence of pathological aSyn forms within the GIT. These clinical and pathological findings lead to the idea of a gut-brain route of aSyn pathology in PD. The identification of pathological aSyn in the intestinal system, e.g., by GIT biopsies, is therefore of highest interest for early diagnosis and early intervention in the phase of formation and propagation of aSyn. However, reliable methods to discriminate between physiological and pathological forms of enteral aSyn on the cellular and biochemical level are still missing. Moreover, a better understanding of the physiological function of aSyn within the GIT as well as its structure and pathological aggregation pathways are crucial to understand its role within the enteric nervous system and its spreading from the gut to the brain. In this review, we summarize clinical manifestations of PD in the GIT, and discuss biochemical findings from enteral biopsies. The relevance of pathological aSyn forms, their connection to the gut-brain axis and new developments to identify pathologic forms of aSyn by structural features are critically reviewed.
Parkinson's disease (PD) is characterized by a long prodromal phase with a multitude of markers indicating an increased PD risk prior to clinical diagnosis based on motor symptoms. Current PD ...prediction models do not consider interdependencies of single predictors, lack differentiation by subtypes of prodromal PD, and may be limited and potentially biased by confounding factors, unspecific assessment methods and restricted access to comprehensive marker data of prospective cohorts. We used prospective data of 18 established risk and prodromal markers of PD in 1178 healthy, PD-free individuals and 24 incident PD cases collected longitudinally in the Tübingen evaluation of Risk factors for Early detection of NeuroDegeneration (TREND) study at 4 visits over up to 10 years. We employed artificial intelligence (AI) to learn and quantify PD marker interdependencies via a Bayesian network (BN) with probabilistic confidence estimation using bootstrapping. The BN was employed to generate a synthetic cohort and individual marker profiles. Robust interdependencies were observed for BN edges from age to subthreshold parkinsonism and urinary dysfunction, sex to substantia nigra hyperechogenicity, depression, non-smoking and to constipation; depression to symptomatic hypotension and excessive daytime somnolence; solvent exposure to cognitive deficits and to physical inactivity; and non-smoking to physical inactivity. Conversion to PD was interdependent with prior subthreshold parkinsonism, sex and substantia nigra hyperechogenicity. Several additional interdependencies with lower probabilistic confidence were identified. Synthetic subjects generated via the BN based representation of the TREND study were realistic as assessed through multiple comparison approaches of real and synthetic data. Altogether our work demonstrates the potential of modern AI approaches (specifically BNs) both for modelling and understanding interdependencies between PD risk and prodromal markers, which are so far not accounted for in PD prediction models, as well as for generating realistic synthetic data.
•Parkinson's disease (PD) is associated with advanced structural brain aging.•Brain age predicts attention and working memory deficits in PD.•Alzheimer's-like atrophy predicts memory, language and ...executive dysfunction in PD.•Brain age and Alzheimer's-like atrophy predict cognitive status conversion in PD.
Recently, it was shown that patients with Parkinson's disease (PD) who exhibit an “Alzheimer's disease (AD)-like” pattern of brain atrophy are at greater risk for future cognitive decline. This study aimed to investigate whether this association is domain-specific and whether atrophy associated with brain aging also relates to cognitive impairment in PD. SPARE-AD, an MRI index capturing AD-like atrophy, and atrophy-based estimates of brain age were computed from longitudinal structural imaging data of 178 PD patients and 84 healthy subjects from the LANDSCAPE cohort. All patients underwent an extensive neuropsychological test battery. Patients diagnosed with mild cognitive impairment or dementia were found to have higher SPARE-AD scores as compared to patients with normal cognition and healthy controls. All patient groups showed increased brain age. SPARE-AD predicted impairment in memory, language and executive functions, whereas advanced brain age was associated with deficits in attention and working memory. Data suggest that SPARE-AD and brain age are differentially related to domain-specific cognitive decline in PD. The underlying pathomechanisms remain to be determined.
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Cerebrospinal fluid (CSF) has often been used as the source of choice for biomarker discovery with the goal to support the diagnosis of neurodegenerative diseases. For this study, we selected 15 CSF ...protein markers which were identified in previously published clinical investigations and proposed as potential biomarkers for PD diagnosis. We aimed at investigating and confirming their suitability for early stage diagnosis of the disease. The current study was performed in a two-fold confirmatory approach. Firstly, the CSF protein markers were analysed in confirmatory cohort I comprising 80 controls and 80 early clinical PD patients. Through univariate analysis we found significant changes of six potential biomarkers (α-syn, DJ-1, Aβ42, S100β, p-Tau and t-Tau). In order to increase robustness of the observations for potential patient differentiation, we developed-based on a machine learning approach-an algorithm which enabled identifying a panel of markers which would improve clinical diagnosis. Based on that model, a panel comprised of α-syn, S100β and UCHL1 were suggested as promising candidates. Secondly, we aimed at replicating our observations in an independent cohort (confirmatory cohort II) comprising 30 controls and 30 PD patients. The univariate analysis demonstrated Aβ42 as the only reproducible potential biomarker. Taking into account both technical and clinical aspects, these observations suggest that the large majority of the investigated CSF proteins currently proposed as potential biomarkers lack robustness and reproducibility in supporting diagnosis in the early clinical stages of PD.
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