Metabolomics Unveils Disrupted Pathways in Parkinson's Disease: Toward Biomarker-Based Diagnosis.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by diverse symptoms, where accurate diagnosis remains challenging. Traditional clinical observation methods often result in misdiagnosis, highlighting the need for biomarker-based diagnostic approaches. This study utilizes ultraperformance liquid chromatography coupled to an electrospray ionization source and quadrupole time-of-flight 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 15 metabolites significantly associated with PD, with 11 reported as potential biomarkers for the first time. Key disrupted metabolic pathways include caffeine metabolism, arachidonic acid metabolism, and primary bile acid biosynthesis. Our machine learning model demonstrated high accuracy, with the Rotation Forest boosting model achieving 94.1% accuracy in distinguishing PD patients from controls. It is based on three new PD biomarkers (downregulated: 1-lyso-2-arachidonoyl-phosphatidate and hypoxanthine and upregulated: ferulic acid) and surpasses the general 80% diagnostic accuracy obtained from initial clinical evaluations conducted by specialists. Besides, this machine learning model based on a decision tree allowed for visual and easy interpretability of affected metabolites in PD patients. These findings could improve the detection and monitoring of PD, paving the way for more precise diagnostics and therapeutic interventions. Our research emphasizes the critical role of metabolomics and machine learning in advancing our understanding of the chemical profile of neurodegenerative diseases.

Neuroprotective potential of Ayahuasca and untargeted metabolomics analyses: applicability to Parkinson's disease.

ETHNOPHARMACOLOGY RELEVANCE: Ayahuasca is a tea produced through decoction of Amazonian plants. It has been used for centuries by indigenous people of South America. The beverage is considered to be an ethnomedicine, and it is traditionally used for the treatment of a wide range of diseases, including neurological illness. Besides, some scientific evidence suggests it may be applicable to Parkinson's disease (PD) treatment. Thus, Ayahuasca deserves in depth studies to clarify its potential role in this disease. AIM OF THE STUDY: This study aimed to use an untargeted metabolomics approach to evaluate the neuroprotective potential of the Ayahuasca beverage, the extracts from its matrix plants (Banisteriopsis caapi and Psychotria viridis), its fractions and its main alkaloids on the viability of SH-SY5Y neuroblastoma cells in an in vitro PD model. MATERIAL AND METHODS: The cytotoxicity of Ayahuasca, crude extracts, and fractions of B. caapi and P. viridis, as well as neuroprotection promoted by these samples in a 6-hydroxydopamine (6-OHDA)-induced neurodegeneration model, were evaluated by the MTT assay at two time-points: 48 h (T1) and 72 h (T2). The main alkaloids from Ayahuasca matrix plants, harmine (HRE) and N,N-dimethyltryptamine (DMT), were also isolated and evaluated. An untargeted metabolomics approach was developed to explore the chemical composition of samples with neuroprotective activity. Ultra-Performance Liquid Chromatography coupled to Electrospray Ionisation and Time-of-Flight (UPLC-ESI-TOF) metabolome data was treated and further analysed using multivariate statistical analyses (MSA): principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). The metabolites were dereplicated using the Dictionary of Natural Products and an in house database. The main alkaloids were also quantified by UPLC-MS/MS. RESULTS: The samples did not cause cytotoxicity in vitro and three of samples intensely increased cell viability at T1. The crude extracts, alkaloid fractions and HRE demonstrated remarkable neuroprotective effect at T2 while the hydroalcoholic fractions demonstrated this neuroprotective effect at T1 and T2. Several compounds from different classes, such as ß-carbolines and monoterpene indole alkaloids (MIAs) were revealed correlated with this property by MSA. Additionally, a total of 2419 compounds were detected in both ionisation modes. HRE showed potent neuroprotective action at 72 h, but it was not among the metabolites positively correlated with the most efficacious neuroprotective profile at either time (T1 and T2). Furthermore, DMT was statistically important to differentiate the dataset (VIP value > 1), although it did not exhibit sufficient neuroprotective activity by in vitro assay, neither a positive correlation with T1 and T2 neuroprotective profile, which corroborated the MSA results. CONCLUSION: The lower doses of the active samples stimulated neuronal cell proliferation and/or displayed the most efficacious neuroprotection profile, namely by preventing neuronal damage and improving cell viability against 6-OHDA-induced toxicity. Intriguingly, the hydroalcoholic fractions exhibited enhanced neuroprotective effects when compared to other samples and isolated alkaloids. This finding corroborates the significance of a holistic approach. The results demonstrate that Ayahuasca and its base plants have potential applicability for PD treatment and to prevent its progression differently from current drugs to treat PD.