Exposure to high doses of selenium in the Amazon riverside population: Use of omics tools to evaluate mechanisms associated with toxicity

• Grant number: 23/14336-2
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: June 01, 2024
• End date: November 30, 2025
• Field of knowledge: Health Sciences - Nutrition
• Principal Investigator: Fernando Barbosa Júnior
• Grantee: Lígia Moriguchi Watanabe
• Host Institution: Faculdade de Ciências Farmacêuticas de Ribeirão Preto (FCFRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated research grant: 18/24069-3 - ReSEARCH: Recognizing Signatures of the Exposome to Anticipate the Risks for a Continuous Health, AP.TEM

Abstract

The Amazon riverside population is unique, considering its geographic location, culture, and lifestyle. Another specific characteristic of this population is the high selenium (Se) and other compounds concentration in blood, such as methylmercury (MeHg), without signs and symptoms of intoxication. Some previous studies formulated hypotheses about the mechanisms associated with the absence of Se toxicity in this population, mainly related to the connection with MeHg. However, such mechanisms are not fully understood, and other factors associated to Se metabolism, especially in the pathways of use and excretion of Se metabolites, could be relevant to explain the absence of toxicity in the Amazon riverside population. Therefore, the present study's aim will be to use omics tools (metabolomics, transcriptomics, genomics, and epigenomics) to identify possible influences on the Se metabolic pathway that could lead riverside populations to present high concentrations of blood Se, without symptoms of toxicity. For this, 300 adults, of both sexes, residing in riverside communities on Lake Tucuruí, State of Pará, Brazil, will be evaluated. Participants will be recruited door-to-door at two different times in order to collect sociodemographic, lifestyle, and health information, in addition to anthropometric indicators, food consumption, biochemical indicators, minerals/metals in blood and urine, including Se total and metabolites, genetic analysis including single nucleotide polymorphisms and expression of genes related to Se metabolism and epigenetics. All analyses will be performed using the R environment for statistical computing (V.4.3.0). A p-values <0.05 will be established as significant.