Investigating the relationship between non-occupational pesticide exposure and metabolomic biomarkers
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: ex...
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| Format: | Article |
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Frontiers Media S.A.
2023-10-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1248609/full |
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| author | Saranya Palaniswamy Saranya Palaniswamy Saranya Palaniswamy Khaled Abass Khaled Abass Jaana Rysä Joan O. Grimalt Jon Øyvind Odland Jon Øyvind Odland Arja Rautio Arja Rautio Marjo-Riitta Järvelin Marjo-Riitta Järvelin Marjo-Riitta Järvelin Marjo-Riitta Järvelin Marjo-Riitta Järvelin |
| author_facet | Saranya Palaniswamy Saranya Palaniswamy Saranya Palaniswamy Khaled Abass Khaled Abass Jaana Rysä Joan O. Grimalt Jon Øyvind Odland Jon Øyvind Odland Arja Rautio Arja Rautio Marjo-Riitta Järvelin Marjo-Riitta Järvelin Marjo-Riitta Järvelin Marjo-Riitta Järvelin Marjo-Riitta Järvelin |
| author_sort | Saranya Palaniswamy |
| collection | DOAJ |
| description | 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 sex-specific studies are warranted. |
| first_indexed | 2024-03-11T18:36:37Z |
| format | Article |
| id | doaj.art-26f5e3c785a1444192fb1271be390288 |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-03-11T18:36:37Z |
| publishDate | 2023-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-26f5e3c785a1444192fb1271be3902882023-10-12T17:13:08ZengFrontiers Media S.A.Frontiers in Public Health2296-25652023-10-011110.3389/fpubh.2023.12486091248609Investigating the relationship between non-occupational pesticide exposure and metabolomic biomarkersSaranya Palaniswamy0Saranya Palaniswamy1Saranya Palaniswamy2Khaled Abass3Khaled Abass4Jaana Rysä5Joan O. Grimalt6Jon Øyvind Odland7Jon Øyvind Odland8Arja Rautio9Arja Rautio10Marjo-Riitta Järvelin11Marjo-Riitta Järvelin12Marjo-Riitta Järvelin13Marjo-Riitta Järvelin14Marjo-Riitta Järvelin15Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, FinlandDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United KingdomArctic Health, Faculty of Medicine, University of Oulu, Oulu, FinlandArctic Health, Faculty of Medicine, University of Oulu, Oulu, FinlandDepartment of Environmental Health Sciences, College of Health Sciences, University of Sharjah, Sharjah, United Arab EmiratesSchool of Pharmacy, University of Eastern Finland, Kuopio, FinlandInstitute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Barcelona, SpainThe Norwegian University of Science and Technology, Trondheim, NorwaySchool of Health Systems and Public Health, Faculty of Health Sciences, University of Pretoria, Pretoria, South AfricaDepartment of Environmental Health Sciences, College of Health Sciences, University of Sharjah, Sharjah, United Arab EmiratesThule Institute, University of Arctic, University of Oulu, Oulu, FinlandCenter for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, FinlandDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom0Unit of Primary Care, Oulu University Hospital, Oulu, Finland1MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom2Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, United KingdomThe 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 sex-specific studies are warranted.https://www.frontiersin.org/articles/10.3389/fpubh.2023.1248609/fullpesticidesmetabolomicsFinlandgeneral populationnon-occupational exposurenon-communicable diseases |
| spellingShingle | Saranya Palaniswamy Saranya Palaniswamy Saranya Palaniswamy Khaled Abass Khaled Abass Jaana Rysä Joan O. Grimalt Jon Øyvind Odland Jon Øyvind Odland Arja Rautio Arja Rautio Marjo-Riitta Järvelin Marjo-Riitta Järvelin Marjo-Riitta Järvelin Marjo-Riitta Järvelin Marjo-Riitta Järvelin Investigating the relationship between non-occupational pesticide exposure and metabolomic biomarkers Frontiers in Public Health pesticides metabolomics Finland general population non-occupational exposure non-communicable diseases |
| title | Investigating the relationship between non-occupational pesticide exposure and metabolomic biomarkers |
| title_full | Investigating the relationship between non-occupational pesticide exposure and metabolomic biomarkers |
| title_fullStr | Investigating the relationship between non-occupational pesticide exposure and metabolomic biomarkers |
| title_full_unstemmed | Investigating the relationship between non-occupational pesticide exposure and metabolomic biomarkers |
| title_short | Investigating the relationship between non-occupational pesticide exposure and metabolomic biomarkers |
| title_sort | investigating the relationship between non occupational pesticide exposure and metabolomic biomarkers |
| topic | pesticides metabolomics Finland general population non-occupational exposure non-communicable diseases |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1248609/full |
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