Saliva as a non-invasive matrix for assessing xenobiotic metabolites and metabolomes: implications for maternal health and preeclampsia.
10.1038/s41368-025-00390-8
- Author:
Preethi BALAN
1
;
Junfeng ZHANG
2
;
Kok Hian TAN
3
;
Upul COORAY
4
;
Ryan Wk LEE
3
;
Mah Lay ONG
3
;
Chaminda Jaya SENEVIRATNE
5
Author Information
1. Singapore Oral Multiomics Initiative, National Dental Research Institute Singapore (NDRIS), National Dental Centre, Singapore, Singapore. preethi.prajod@duke-nus.edu.sg.
2. Nicholas School of the Environment & Duke Global Health Institute, Duke University, Durham, NC, USA.
3. Department of Maternal & Fetal Medicine, KK Women's and Children's Hospital, Singapore, Singapore.
4. Singapore Oral Population Health Initiative, National Dental Research Institute Singapore (NDRIS), National Dental Centre, Singapore, Singapore.
5. Singapore Oral Multiomics Initiative, National Dental Research Institute Singapore (NDRIS), National Dental Centre, Singapore, Singapore. jaya.seneviratne@uq.edu.au.
- Publication Type:Journal Article
- MeSH:
Humans;
Female;
Pregnancy;
Saliva/metabolism*;
Pre-Eclampsia/metabolism*;
Xenobiotics/analysis*;
Adult;
Metabolome;
Maternal Health;
Mass Spectrometry
- From:
International Journal of Oral Science
2025;17(1):55-55
- CountryChina
- Language:English
-
Abstract:
Chemical exposure during prenatal development has significant implications for both maternal and child health. Compared to blood, saliva is a non-invasive and less resource-intensive, alternative. Given the temporal variability of xenobiotic metabolites (XM), repeated sampling is essential. Therefore, saliva offers a valuable tool for the longitudinal assessment of prenatal exposomes. Despite its potential, no studies have explored saliva for XM measurement. This study pioneered using saliva to assess XM detectability and investigate the associations between prenatal XM and endogenous metabolomes in pregnant women. Saliva samples were analysed using mass spectrometry from 80 pregnant women at 24-34 weeks gestation. Metabolomes and exposomes were annotated using the Human Metabolome and U.S. Environmental Protection Agency databases. Metabolome-XM associations were clustered using Glay community clustering. Linear regression models, adjusted for age, estimated associations between catecholamines and XMs. XM levels were validated in a cohort of women (n = 14) with and without preeclampsia. Our study identified 582 metabolomes and 125 XM in saliva, demonstrating its potential as a matrix for exposure measurement. After false discovery rate correction, 18 109 significant metabolome-XM associations were identified. Community clustering revealed 37 connected clusters, with the largest cluster (238 nodes) enriched in tyrosine and catecholamine metabolism. Food-contact-chemicals and food-additives were significantly associated with higher catecholamine and their metabolite levels. Subgroup analyses revealed higher concentrations of these chemicals in women with preeclampsia compared to healthy controls. This study demonstrates that saliva contains valuable molecular data for measuring exposomes. Food-related chemicals were associated with higher catecholamine levels, which may be relevant to the prevalence of hypertensive crises in pregnancy.
