Palaniswamy, SaranyaAbass, KhaledRysa, JaanaGrimalt, Joan O.Odland, Jon OyvindRautio, ArjaJarvelin, Marjo-Riitta2024-06-252024-06-252023-10-11Palaniswamy, S., Abass, K., Rysä, J., Grimalt, J.O., Odland, J.Ø., Rautio, A. & Järvelin, M.-R. (2023) Investigating the relationship between non-occupational pesticide exposure and metabolomic biomarkers. Frontiers in Public Health 11:1248609. DOI: 10.3389/fpubh.2023.1248609.2296-2565 (online)10.3389/fpubh.2023.1248609http://hdl.handle.net/2263/96646DATA AVAILABILITY STATEMENT : The datasets presented in this article are not readily available because NFBC data is available from the University of Oulu, Infrastructure for Population Studies. Permission to use the data can be applied for research purposes via an electronic material request portal. In the use of data, we follow the EU general data protection regulation (679/2016) and Finnish Data Protection Act. The use of personal data is based on cohort participant’s written informed consent at his/her latest follow-up study, which may cause limitations to its use. Please, contact the NFBC project center (NFBCprojectcenter@oulu.fi) and visit the cohort website (www.oulu.fi/nfbc) or Fairdata.fi (http://urn.fi/urn:nbn:fi:att:bc1e5408-980e-4a62-b899-43bec3755243) for additional information. Requests to access the datasets should be directed to NFBC project center (NFBCprojectcenter@oulu.fi).The relationship between pesticide exposures and metabolomics biomarkers is not well understood. We examined the changes in the serum metabolome (early biomarkers) and the metabolic pathways associated with various pesticide exposure scenarios (OPE: overall exposure, PEM: exposure in months, PEY: exposure in years, and PEU: reported specific pesticides use) using data from the Northern Finland Birth Cohort 1966 31-year cross-sectional examination. We utilized questionnaire data on pesticide exposures and serum samples for nuclear magnetic resonance (NMR)-based metabolomics analyses. For exposures and metabolites associations, participants size varied between 2,361 and 5,035. To investigate associations between metabolomics biomarkers and exposure to pesticide scenarios compared to those who reported no exposures multivariable regression analyses stratified by sex and adjustment with covariates (season of pesticide use, socioeconomic position (SEP), alcohol consumption, BMI, and latitude of residence) were performed. Multiple testing by Benjamini–Hochberg false discovery rate (FDR) correction applied. Pesticide exposures differed by sex, season of pesticide use, alcohol, SEP, latitude of residence. Our results showed that all pesticide exposure scenarios were negatively associated with decreased HDL concentrations across all lipoprotein subclasses in women. OPE, PEY, and PEU were associated with decreased branched-chain amino acid concentrations in men and decreased albumin concentrations in women. OPE, PEY and PEU were also associated with changes in glycolysis metabolites and ketone bodies in both sexes. Specific pesticides exposure was negatively associated with sphingolipids and inflammatory biomarkers in men. In women, OPE, PEM, and PEU were associated with decreased apolipoprotein A1 and increased apolipoprotein B/ apolipoprotein A1 ratio. Our findings suggest that identification of early biomarkers of disease risk related to pesticide exposures can inform strategies to reduce exposure and investigate causal pathways. Women may be more susceptible to non-occupational pesticide exposures when compared to men, and future sexspecific studies are warranted.en© 2023 Palaniswamy, Abass, Rysä, Grimalt, Odland, Rautio and Järvelin. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY).PesticidesMetabolomicsFinlandGeneral populationNon-occupational exposureNon-communicable diseases (NCDs)SDG-03: Good health and well-beingArticle