AI Article Synopsis

  • About 90% of Parkinson's disease cases are idiopathic, and this study investigates the disease's multifactorial nature through metabolomics, which examines how genes and the environment interact at the cellular level.
  • The research compares the metabolomic profiles of whole blood from treated and de-novo (newly diagnosed) PD patients to healthy controls, focusing on how these profiles relate to disease duration, stage, and motor impairment.
  • Findings suggest that metabolomics can help identify potential biomarkers for Parkinson’s disease, but further large-scale studies are necessary for validation and comparison with other neurodegenerative diseases.*

Article Abstract

Introduction: About 90% of cases of Parkinson's disease (PD) are idiopathic and attempts to understand pathogenesis typically assume a multifactorial origin. Multifactorial diseases can be studied using metabolomics, since the cellular metabolome reflects the interplay between genes and environment.

Objective: The aim of our case-control study is to compare metabolomic profiles of whole blood obtained from treated PD patients, de-novo PD patients and controls, and to study the perturbations correlated with disease duration, disease stage and motor impairment.

Methods: We collected blood samples from 16 drug naïve parkinsonian patients, 84 treated parkinsonian patients, and 42 age matched healthy controls. Metabolomic profiles have been obtained using gas chromatography coupled to mass spectrometry. Multivariate statistical analysis has been performed using supervised models; partial least square discriminant analysis and partial least square regression.

Results: This approach allowed separation between discrete classes and stratification of treated patients according to continuous variables (disease duration, disease stage, motor score). Analysis of single metabolites and their related metabolic pathways revealed unexpected possible perturbations related to PD and underscored existing mechanisms that correlated with disease onset, stage, duration, motor score and pharmacological treatment.

Conclusion: Metabolomics can be useful in pathogenetic studies and biomarker discovery. The latter needs large-scale validation and comparison with other neurodegenerative conditions.

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Source
http://dx.doi.org/10.1007/s11306-019-1554-xDOI Listing

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