Traditional clinical observation methods often result in misdiagnosis, highlighting the need for biomarker-based diagnostic approaches. This study utilizes UPLC-ESI-QTOF untargeted metabolomics combined with biochemometrics to identify novel serum biomarkers for PD. Analyzing a Brazilian cohort of serum samples from 39 PD patients and 15 healthy controls, we identified fifteen metabolites significantly associated with PD
[doi:10.25345/C5GB1XT9Z]
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: Metabolomics ; Parkinson's disease ; Biomarkers ; Caffeine metabolism ; Multivariate analysis ; Machine learning.
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Albert Katchborian Neto, Federal University of Alfenas, Brazil |
Submitting User: | albert_katch |
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