Temporal trajectory of biofluid markers in Parkinson's disease.
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ABSTRACT:
SUBMITTER: Baek MS
PROVIDER: S-EPMC8292456 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Accurate early diagnosis of Parkinson's disease is essential. Using data available from the Parkinson's Progression Markers Initiative study, we identified a multivariate logistic regression model including cerebrospinal fluid α-synuclein, olfactory function, age, and gender that achieved a high degree of discrimination between patients with Parkinson's disease and healthy control or scan without evidence of dopaminergic deficit participants. Additionally, the model could predict the conversion of scan without evidence of dopaminergic deficit to Parkinson's disease, as well as discriminate between normal and impaired subjects with leucine-rich repeat kinase 2 mutations. Although further validation is needed, this model may serve as an alternative method to neuroimaging screening in Parkinson's disease studies.
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Project description:Parkinson's disease (PD) is the most frequent of all Lewy body diseases, a family of progressive neurodegenerative disorders characterized by intra-neuronal cytoplasmic inclusions of ?-synuclein. Its most defining features are bradykinesia, tremor, rigidity and postural instability. By the time PD manifests with motor signs, 70% of dopaminergic midbrain neurons are lost, and the disease is already in the middle or late stage. However, there are various non-motor symptoms occurring up to 20 years before the actual parkinsonism that are closely associated with profound deficiency of myocardial noradrenaline content and peripheral sympathetic denervation, as evidenced by neuroimaging experiments in recent years. Additionally, there is an inherent autotoxicity of catecholamines in the neuronal cells in which they are produced, forming toxic catecholaldehyde intermediates that make ?-synuclein prone to aggregation, initiating a cascade of events that ultimately leads to neuronal death. The etiopathogenesis of PD and related synucleinopathies thus may well be a prototypical example of a catecholamine-regulated neurodegeneration, given that the synucleinopathy in PD spreads in synergy with central and peripheral catecholaminergic dysfunction from the earliest phases onward. That is why catecholamines and their metabolites, precursors, or derivatives in cerebrospinal fluid or plasma could be of particular interest as biomarkers for prodromal and de novo PD. Because there is great demand for such markers, this mini-review summarizes all catecholamine-related studies to date, in addition to providing profound neurochemical evidence on a systemic and cellular level to further emphasize this hypothesis and with emphasis on extracellular vesicles as a novel diagnostic and therapeutic incentive.
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Project description:Temporal orienting of attention can affect multiple stages of processing to guide adaptive behaviour. We tested whether temporal expectation in different task contexts is compromised in individuals with Parkinson's disease (PD). In Experiment 1 two temporal-orienting tasks were used: a speeded task emphasizing motor preparation and a non-speeded task emphasizing perceptual discrimination using rapid serial visual presentation. In both tasks, auditory cues indicated the likelihood of a target appearing after a short or long interval. In the speeded-response task, participants used the cues to anticipate an easily detectable target stimulus. In the non-speeded perceptual-discrimination task, participants used the cues to help discriminate a target letter embedded in a stream of letters. Relative to healthy participants, participants with PD did not show altered temporal orienting effects in the speeded-response task. However, they were impaired in using temporal cues to improve perceptual discrimination. In Experiment 2, we tested whether the temporal-orienting deficits in the perceptual-discrimination task depended on the requirement to ignore temporally distracting stimuli. We replicated the impaired temporal orienting for perceptual discrimination in an independent group of individuals with PD, and showed the impairment was abolished when individuals were on their dopaminergic medication. In a task without any distracting letters, however, patients off or on medication benefited normally from temporal orienting cues. Our findings suggest that deficits in temporal orienting in individuals with PD interact with specific task demands, such as the requirement to select target from temporally competing distractors.
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Project description:Phosphorylated ?-synuclein accounts for more than 90% of ?-synuclein found in Lewy bodies of Parkinson's disease (PD). We aimed to examine whether plasma Ser129-phosphorylated ?-synuclein (pS129-?-synuclein) is a surrogate marker of PD progression. This prospective study enrolled 170 participants (122 PD patients, 68 controls). We measured plasma levels of total and pS129-?-synuclein using immunomagnetic reduction-based immunoassay. PD patients received evaluations of motor and cognition at baseline and at a mean follow-up interval of three years. Changes in the Movement Disorder Society revision of the Unified Parkinson's Disease Rating Scale motor score (MDS-UPDRS part III) and Mini-Mental State Examination (MMSE) score were used to assess motor and cognition progression. Our results showed that plasma levels of total and pS129-?-synuclein were significantly higher in PD patients than controls (total: 1302.3 ± 886.6 fg/mL vs. 77.8 ± 36.6 fg/mL, p < 0.001; pS129-?-synuclein: 12.9 ± 8.7 fg/mL vs. 0.8 ± 0.6 fg/mL, p < 0.001), as was the pS129-?-synuclein/total ?-synuclein ratio (2.8 ± 1.1% vs. 1.1 ± 0.6%, p = 0.01). Among PD patients, pS129-?-synuclein levels were higher with advanced motor stage (p < 0.001) and correlated with MDS-UPDRS part III scores (r = 0.27, 95% CI: 0.09-0.43, p = 0.004). However, we found no remarkable difference between PD patients with and without dementia (p = 0.75). After a mean follow-up of 3.5 ± 2.1 years, PD patients with baseline pS129-?-synuclein > 8.5 fg/mL were at higher risk of motor symptom progression of at least 3 points in the MDS-UPDRS part III scores than those with pS129-?-synuclein < 8.5 fg/mL (p = 0.03, log rank test). In conclusion, our data suggest that plasma pS129-?-synuclein levels correlate with motor severity and progression, but not cognitive decline, in patients with PD.
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Project description:Background: Motor progression varies even among those with a single diagnosis such as Parkinson's disease (PD) and little is known about the trajectory of motor signs prior to death. Understanding deterioration patterns may help clinicians counsel patients and proactively plan interdisciplinary care, including palliative care. The objective of this study was to examine and describe Unified Parkinson's Disease Rating Scale motor score (UPDRS-III) trajectories at the end of life in PD. Methods: A retrospective chart review was performed for deceased PD patients who attended the Parkinson and Movement Disorders Program at the University of Alberta for at least 5 years between 1999 and 2018. UPDRS-III scores were recorded for all visits. Trajectory patterns were visualized with Loess curves stratified by sex and age at diagnosis. Piecewise linear models were used to individually model the UPDRS-III scores, and the trajectories obtained were clustered based on their features. Results: Among the 202 charts reviewed, 84 meeting inclusion criteria were analyzed. The UPDRS-III increased over time regardless of sex and age. Distinct trajectory variations present in PD (e.g., Consistent Deterioration, Stability-Deterioration, Improvement-Deterioration, Deterioration-Improvement-Deterioration) were identified. Twenty-five percent of the patients were classified as Undetermined/Irregular trajectories. In addition, regardless of trajectory type, many patients experienced a steep increase in UPDRS-III approaching death. Those with disease diagnosis after age 65 years had a shorter survival time, compared to PD patients with a younger age of onset. Conclusion: Our study identified dominant types of motor trajectory in PD that can help clinicians understand their patients' course of illness. This information can help counsel patients regarding the variability in motor deterioration and should alert physicians to recognize a terminal decline. Age of disease onset was correlated with survival time.
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Project description:Chronic medical conditions show substantial heterogeneity in their clinical features and progression. We develop the novel data-driven, network-based Trajectory Profile Clustering (TPC) algorithm for 1) identification of disease subtypes and 2) early prediction of subtype/disease progression patterns. TPC is an easily generalizable method that identifies subtypes by clustering patients with similar disease trajectory profiles, based not only on Parkinson's Disease (PD) variable severity, but also on their complex patterns of evolution. TPC is derived from bipartite networks that connect patients to disease variables. Applying our TPC algorithm to a PD clinical dataset, we identify 3 distinct subtypes/patient clusters, each with a characteristic progression profile. We show that TPC predicts the patient's disease subtype 4 years in advance with 72% accuracy for a longitudinal test cohort. Furthermore, we demonstrate that other types of data such as genetic data can be integrated seamlessly in the TPC algorithm. In summary, using PD as an example, we present an effective method for subtype identification in multidimensional longitudinal datasets, and early prediction of subtypes in individual patients.
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Project description:BackgroundCurrent methods for analyzing single-cell datasets have relied primarily on static gene expression measurements to characterize the molecular state of individual cells. However, capturing temporal changes in cell state is crucial for the interpretation of dynamic phenotypes such as the cell cycle, development, or disease progression. RNA velocity infers the direction and speed of transcriptional changes in individual cells, yet it is unclear how these temporal gene expression modalities may be leveraged for predictive modeling of cellular dynamics.ResultsHere, we present the first task-oriented benchmarking study that investigates integration of temporal sequencing modalities for dynamic cell state prediction. We benchmark ten integration approaches on ten datasets spanning different biological contexts, sequencing technologies, and species. We find that integrated data more accurately infers biological trajectories and achieves increased performance on classifying cells according to perturbation and disease states. Furthermore, we show that simple concatenation of spliced and unspliced molecules performs consistently well on classification tasks and can be used over more memory intensive and computationally expensive methods.ConclusionsThis work illustrates how integrated temporal gene expression modalities may be leveraged for predicting cellular trajectories and sample-associated perturbation and disease phenotypes. Additionally, this study provides users with practical recommendations for task-specific integration of single-cell gene expression modalities.
| S-EPMC9442962 | biostudies-literature
Project description:BackgroundParkinson's disease (PD) disrupts temporal processing, but the neuronal sources of deficits and their response to dopamine (DA) therapy are not understood. Though the striatum and DA transmission are thought to be essential for timekeeping, potential working memory (WM) and executive problems could also disrupt timing.Methodology/findingsThe present study addressed these issues by testing controls and PD volunteers 'on' and 'off' DA therapy as they underwent fMRI while performing a time-perception task. To distinguish systems associated with abnormalities in temporal and non-temporal processes, we separated brain activity during encoding and decision-making phases of a trial. Whereas both phases involved timekeeping, the encoding and decision phases emphasized WM and executive processes, respectively. The methods enabled exploration of both the amplitude and temporal dynamics of neural activity. First, we found that time-perception deficits were associated with striatal, cortical, and cerebellar dysfunction. Unlike studies of timed movement, our results could not be attributed to traditional roles of the striatum and cerebellum in movement. Second, for the first time we identified temporal and non-temporal sources of impaired time perception. Striatal dysfunction was found during both phases consistent with its role in timekeeping. Activation was also abnormal in a WM network (middle-frontal and parietal cortex, lateral cerebellum) during encoding and a network that modulates executive and memory functions (parahippocampus, posterior cingulate) during decision making. Third, hypoactivation typified neuronal dysfunction in PD, but was sometimes characterized by abnormal temporal dynamics (e.g., lagged, prolonged) that were not due to longer response times. Finally, DA therapy did not alleviate timing deficits.Conclusions/significanceOur findings indicate that impaired timing in PD arises from nigrostriatal and mesocortical dysfunction in systems that mediate temporal and non-temporal control-processes. However, time perception impairments were not improved by DA treatment, likely due to inadequate restoration of neuronal activity and perhaps corticostriatal effective-connectivity.
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Project description:The development of biomarkers to predict the progression of Parkinson's disease (PD) from its earliest stage through its heterogeneous course is critical for research and therapeutic development. The Parkinson's Progression Markers Initiative (PPMI) study is an ongoing international multicenter, prospective study to validate biomarkers in drug-naïve PD patients and matched healthy controls (HC). We quantified cerebrospinal fluid (CSF) alpha-synuclein (?-syn), amyloid-beta1-42 (A?1-42), total tau (t-tau), and tau phosphorylated at Thr181 (p-tau) in 660 PPMI subjects at baseline, and correlated these data with measures of the clinical features of these subjects. We found that CSF ?-syn, t-tau and p-tau levels, but not A?1-42, were significantly lower in PD compared with HC, while the diagnostic value of the individual CSF biomarkers for PD diagnosis was limited due to large overlap. The level of ?-syn, but not other biomarkers, was significantly lower in PD patients with non-tremor-dominant phenotype compared with tremor-dominant phenotype. In addition, in PD patients the lowest A?1-42, or highest t-tau/A?1-42 and t-tau/?-syn quintile in PD patients were associated with more severe non-motor dysfunction compared with the highest or lowest quintiles, respectively. In a multivariate regression model, lower ?-syn was significantly associated with worse cognitive test performance. APOE ?4 genotype was associated with lower levels of A?1-42, but neither with PD diagnosis nor cognition. Our data suggest that the measurement of CSF biomarkers in early-stage PD patients may relate to disease heterogeneity seen in PD. Longitudinal observations in PPMI subjects are needed to define their prognostic performance.
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