Metabolic effects of chemical exposure in wildland firefighters from the State of Pará - A metabolomics approach applied to health technology

• Grant number: 24/17990-8
• Support Opportunities: Scholarships in Brazil - Support Program for Fixating Young Doctors
• Start date: December 01, 2024
• End date: November 30, 2025
• Field of knowledge: Physical Sciences and Mathematics - Chemistry - Analytical Chemistry
• Principal Investigator: Kelly Polido Kaneshiro Olympio
• Grantee: Alda Neis Miranda de Araújo
• Host Institution: Faculdade de Saúde Pública (FSP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 24/01326-1 - Metabolic effects of chemical exposure in forest firefighters from the Pará State: a metabolomic approach applied to health technology, AP.R

Abstract

The growing impact of climate change has triggered an alarming increase in wildfires in the Brazilian Amazon region, making it imperative to investigate the metabolic effects of exposure to the smoke from these fires. The emissions from these fires contain a complex mixture of particles and chemicals, such as polycyclic aromatic hydrocarbons (PAHs). In the state of Pará, the epicenter of many of these events, wildland firefighters routinely face this exposure. However, little is known about the health impacts of this exposure on the affected individuals and its potential effects on their health and metabolism. Therefore, this project aims to conduct a metabolomic analysis of the blood of firefighters exposed daily to wildfire smoke. Gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance (NMR) techniques will be used to obtain the metabolomic profiles of individuals exposed to the fires. The metabolomes of the firefighters will be compared with those of non-occupationally exposed participants, such as administrative workers within the organization. The results obtained will be used to investigate potential biomarkers of exposure/effect and to predict clinical complications before the onset of symptoms of possible diseases caused by chemical intoxication. Additionally, artificial intelligence (AI) will be trained to assess the similarity between the participants' metabolic profiles and those of various diseases related to exposure to compounds present in the smoke. The AI will be built using publicly available data from multiple metabolomics studies. Applying the trained AI to the participants' metabolomics data will enable an evaluation of their predisposition to various diseases. The combination of analytical chemistry, omics tools, and data science makes this proposal innovative, with high potential to generate new health technology applicable to public and community health.