Dataset Information

Serum metabolomics of slow vs. rapid motor progression Parkinson's disease: a pilot study.

ABSTRACT: Progression of Parkinson's disease (PD) is highly variable, indicating that differences between slow and rapid progression forms could provide valuable information for improved early detection and management. Unfortunately, this represents a complex problem due to the heterogeneous nature of humans in regards to demographic characteristics, genetics, diet, environmental exposures and health behaviors. In this pilot study, we employed high resolution mass spectrometry-based metabolic profiling to investigate the metabolic signatures of slow versus rapidly progressing PD present in human serum. Archival serum samples from PD patients obtained within 3 years of disease onset were analyzed via dual chromatography-high resolution mass spectrometry, with data extraction by xMSanalyzer and used to predict rapid or slow motor progression of these patients during follow-up. Statistical analyses, such as false discovery rate analysis and partial least squares discriminant analysis, yielded a list of statistically significant metabolic features and further investigation revealed potential biomarkers. In particular, N8-acetyl spermidine was found to be significantly elevated in the rapid progressors compared to both control subjects and slow progressors. Our exploratory data indicate that a fast motor progression disease phenotype can be distinguished early in disease using high resolution mass spectrometry-based metabolic profiling and that altered polyamine metabolism may be a predictive marker of rapidly progressing PD.

SUBMITTER: Roede JR

PROVIDER: S-EPMC3805572 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Serum metabolomics of slow vs. rapid motor progression Parkinson's disease: a pilot study.

Roede James R JR Uppal Karan K Park Youngja Y Lee Kichun K Tran Vilinh V Walker Douglas D Strobel Frederick H FH Rhodes Shannon L SL Ritz Beate B Jones Dean P DP

PloS one 20131022 10

Progression of Parkinson's disease (PD) is highly variable, indicating that differences between slow and rapid progression forms could provide valuable information for improved early detection and management. Unfortunately, this represents a complex problem due to the heterogeneous nature of humans in regards to demographic characteristics, genetics, diet, environmental exposures and health behaviors. In this pilot study, we employed high resolution mass spectrometry-based metabolic profiling to ...[more]

PMID: 24167579

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Project description:ObjectiveIdentifying neural activity biomarkers of brain disease is essential to provide objective estimates of disease burden, obtain reliable feedback regarding therapeutic efficacy, and potentially to serve as a source of control for closed-loop neuromodulation. In Parkinson's disease (PD), microelectrode recordings (MER) are routinely performed in the basal ganglia to guide electrode implantation for deep brain stimulation (DBS). While pathologically-excessive oscillatory activity has been observed and linked to PD motor dysfunction broadly, the extent to which these signals provide quantitative information about disease expression and fluctuations, particularly at short timescales, is unknown. Furthermore, the degree to which informative signal features are similar or different across patients has not been rigorously investigated. We sought to determine the extent to which motor error in PD across patients can be decoded on a rapid timescale using spectral features of neural activity.ApproachHere, we recorded neural activity from the subthalamic nucleus (STN) of subjects with PD undergoing awake DBS surgery while they performed an objective, continuous behavioral assessment that synthesized heterogenous PD motor manifestations to generate a scalar measure of motor dysfunction at short timescales. We then leveraged natural motor performance variations as a 'ground truth' to identify corresponding neurophysiological biomarkers.Main resultsSupport vector machines using multi-spectral decoding of neural signals from the STN succeeded in tracking the degree of motor impairment at short timescales (as short as one second). Spectral power across a wide range of frequencies, beyond the classic 'β' oscillations, contributed to this decoding, and multi-spectral models consistently outperformed those generated using more isolated frequency bands. While generalized decoding models derived across subjects were able to estimate motor impairment, patient-specific models typically performed better.SignificanceThese results demonstrate that quantitative information about short-timescale PD motor dysfunction is available in STN neural activity, distributed across various patient-specific spectral components, such that an individualized approach will be critical to fully harness this information for optimal disease tracking and closed-loop neuromodulation.

Project description:BackgroundAsymmetric hemispheric loss of dopaminergic neurons is one of the characteristic features of Parkinson's disease (PD). However, it is still debated if right or left asymmetry differently affects cognitive and motor progression.ObjectivesThe objective of this study was to investigate, for the first time, the relevance of dopamine transporter (DAT) asymmetry on cognitive and motor manifestations at onset and at 4-year progression in drug-naïve PD.MethodsFrom the Parkinson's Progression Markers Initiative multicenter cohort, we identified 249 right-handed patients with PD with baseline asymmetry greater than 20% in putamen DAT binding at single-photon emission computed tomography. A predominant putamen asymmetry was found on the left in 143 patients (PD-left), and on the right side in 106 patients (PD-right); we compared them with 196 healthy controls. Patients were followed longitudinally (2-year and 4-year visits), examining their clinical, cognitive, and imaging data.ResultsAt baseline, the PD-left group showed worse performance on the Symbol Digit Modality Test, an attention and processing-speed test, and lower cerebrospinal fluid β-amyloid levels than the PD-right group. These differences were maintained at follow-up, declining over time in both groups. By contrast, the PD-right group showed greater motor impairment at baseline, which increased over 4 years. Striatal DAT binding decreased over time in both groups, but the PD-right group showed a steeper decline, particularly during the first 2-year follow-up. Putaminal asymmetry assessed at baseline was maintained over time.ConclusionsThese findings suggest that hemispheric asymmetric dopaminergic denervation influences PD cognitive and motor performance as well as progression. Predominant right hemisphere nigrostriatal dopaminergic loss is associated with greater motor severity, whereas more pronounced left hemisphere denervation affects cognitive manifestations at onset and their progression. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Dataset Information

Serum metabolomics of slow vs. rapid motor progression Parkinson's disease: a pilot study.

Publications

Serum metabolomics of slow vs. rapid motor progression Parkinson's disease: a pilot study.

Similar Datasets

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