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Conference Proceeding

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BACKGROUND: The complex and heterogeneous nature of Parkinson’s disease (PD) and variability in their progression hampers its early diagnosis and treatment. Consequently, there is much interest in developing models that can predict PD progression and help to deepen our understanding of PD pathology. Metabolomics might shed light on the PD imprint seeking a broader view of the biochemical remodeling induced by this disease in an early and pre-symptomatic stage, unveiling potential biomarkers and developing new novel therapeutic targets

METHODS: In this novel study utilizing ¹H NMR and DI-LC-MS/MS we conducted metabolomics investigation on the serum samples from a clinically well characterized, longitudinally followed Michael J. Fox Foundation cohort of PD patients with (n=101) and without (n=78) the common leucine-rich repeat kinase 2 (LRRK2) mutation, as well as on corresponding control samples (n=56 and n=88). Further, we systematically evaluated the utility of several machine learning techniques for the diagnosis of PD.

RESULTS: Multi-platform metabolomics, in combination with artificial intelligence, revealed the significant metabolites in response to progression of PD, and characterized the affected pathways involved in the metabolic mechanism accompanying development and progression of the idiopathic PD and PD with LRRK2 mutation. Results of this metabolomics study provided additional validation of our group’s earlier finding, which identified Bile Acid metabolism as a prominent abnormal biochemical pathway in individuals with PD.

CONCLUSION: This study demonstrates great potential of longitudinal metabolomics to better interpret biochemical changes underlying PD development and progression, and early prediction of PD. Dysregulation in amino acid and lipid metabolism, mitochondrial dysfunction, and imbalanced gut–brain axis seems to be important contributors in the development of this disease. Therefore, the metabolic pathways highlighted in this study might be considered as worthy potential therapeutic targets.


The19th Annual International Metabolomics Society Conference, Niagara Falls, Canada, June 2023