Evidence map›Paper›PMID 40695786›Full record

ArticleInternational journal of oral science2025

Saliva as a non-invasive matrix for assessing xenobiotic metabolites and metabolomes: implications for maternal health and preeclampsia.

Preethi Balan, Junfeng Zhang, Kok Hian Tan, Upul Cooray, Ryan Wk Lee, Mah Lay Ong, Chaminda Jaya Seneviratne

Abstract read
In one paragraph

Article in International journal of oral science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Preethi BalanSingapore Oral Multiomics Initiative, National Dental Research Institute Singapore (NDRIS), National Dental Centre, Singapore, Singapore. preethi.prajod@duke-nus.edu.sg.
Junfeng ZhangNicholas School of the Environment & Duke Global Health Institute, Duke University, Durham, NC, USA.
Kok Hian TanDepartment of Maternal & Fetal Medicine, KK Women's and Children's Hospital, Singapore, Singapore.
Upul CooraySingapore Oral Population Health Initiative, National Dental Research Institute Singapore (NDRIS), National Dental Centre, Singapore, Singapore.
Ryan Wk LeeDepartment of Maternal & Fetal Medicine, KK Women's and Children's Hospital, Singapore, Singapore.
Mah Lay OngDepartment of Maternal & Fetal Medicine, KK Women's and Children's Hospital, Singapore, Singapore.
Chaminda Jaya SeneviratneSingapore Oral Multiomics Initiative, National Dental Research Institute Singapore (NDRIS), National Dental Centre, Singapore, Singapore. jaya.seneviratne@uq.edu.au.

Funding

MOH | National Medical Research Council (NMRC) (CNIG20nov-0003SingHealth Foundation AM/SU035/2020
6 · The paper itself

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.

Indexed as

Maternal HealthMetabolomePre-EclampsiaSalivaXenobioticsAdultFemaleHumansMass SpectrometryPregnancyXenobiotics

Identifiers

PMID40695786
PMCPMC12283956

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.