Evaluation of 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) effects on mental health: longitudinal metabolomic study using a chemical concatenated approach

• Grant number: 24/04606-5
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: December 01, 2024
• End date: November 30, 2026
• Field of knowledge: Physical Sciences and Mathematics - Chemistry - Organic Chemistry
• Principal Investigator: João Henrique Ghilardi Lago
• Grantee: Albert Katchborian Neto
• Host Institution: Centro de Ciências Naturais e Humanas (CCNH). Universidade Federal do ABC (UFABC). Santo André , SP, Brazil

Abstract

At the forefront of modern psychiatry, studies on psychedelic chemicals are opening newavenues for the treatment of mental disorders such as depression, refractory anxiety, and PostTraumatic Stress Disorder (PTSD). Recent studies involving 5-methoxy-N,Ndimethyltryptamine (5-MeO-DMT) have shown its effectiveness for depression that is resistantto conventional treatment. The aim of this project is to map biomarkers and the metabolicchanges induced by the administration of 5-MeO-DMT, using an innovative methodology thatcombines data acquired by Ultra-Performance Liquid Chromatography (UPLC) coupled withMass Spectrometry (MS), and Nuclear Magnetic Resonance (NMR) data. Additionally,advanced machine learning techniques will be applied to develop robust predictive models,such as artificial neural networks. We intend to establish a solid foundation for the use ofmetabolic signatures in predicting the therapeutic and/or adverse effects of psychedelics,thereby contributing to the development of more personalized treatments for psychiatricdisorders. The research involves the analysis of human biological samples to assess metabolicchanges and potential correlations with cardiovascular and psychometric measures, before andafter the use of 5-MeO-DMT. It is expected to map biomarkers and metabolic pathwaysinvolved to gain insights into the therapeutic effects and to establish relationships betweenaffected pathways and variations in the metabolic profiles studied. Thus, contributing to theadvancement of clinical psychiatry, where a third of the world's depression patients (~350million of people) do not respond to any conventional medication

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

MIRANDA, DANIEL DE OLIVEIRA; FERREIRA, MILLER SANTOS; KATCHBORIAN-NETO, ALBERT; DE OLIVEIRA, RENATO ALMEIDA; BALDIM, JOAO L.; OLIVEIRA, TIAGO BRANQUINHO; DIAS, DANIELLE FERREIRA; CHAGAS-PAULA, DANIELA A.; SOARES, MARISI GOMES. Machine learning decision tree-based models for predicting the antibacterial activity of Lamiaceae essential oils against Staphylococcus aureus. JOURNAL OF MOLECULAR GRAPHICS & MODELLING, v. 140, p. 9-pg., 2025-07-09. (24/04606-5)