Prenatal Transcriptomic and Metabolomic Signatures of Infant Birth Outcomes: A Multiomics Investigation in an Agricultural Cohort

Abstract Prenatal environmental exposures may influence fetal growth by disrupting the maternal metabolome and placental function. This exploratory study integrates untargeted maternal serum metabolomics and placental transcriptomics to identify shared molecular pathways through which the maternal environment affects fetal development. Data were drawn from the SAWASDEE birth cohort in northern Thailand, comprising pregnant farmworkers living in an agricultural region with known environmental exposure concerns. Weighted gene coexpression network analysis (WGCNA) of placental transcriptomic data (n = 254) identified gene expression modules, which were analyzed for associations with neonatal outcomes in a subset with paired maternal metabolomics and birth data (n = 40). A placental gene module enriched for myogenesis-related genes was inversely associated with birth weight (β = −0.11, p = 0.03). Seventeen maternal serum metabolic features were associated with both this module and birth weight, including phospholipids related to membrane remodeling and putatively annotated quinoline-containing xenobiotic-like features with structural similarity to combustion-related or industrial compounds. Mediation analysis did not identify statistically significant indirect effects, although one putative xenobiotic-like feature showed a directionally consistent estimate. In this exploratory analysis, these findings identify maternal metabolomic patterns and placental gene networks that are associated with fetal growth and generate hypotheses regarding biologically relevant pathways linking maternal metabolism, placental function, and neonatal growth. Multiomics integration provides a useful exploratory framework for identifying candidate molecular pathways that warrant validation in larger studies.

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Publication Details

Journal
Environment & Health
Published
2026-09-04
DOI
https://doi.org/10.1021/envhealth.6c00125
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Prenatal Transcriptomic and Metabolomic Signatures of Infant Birth Outcomes: A Multiomics Investigation in an Agricultural Cohort

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Prenatal Transcriptomic and Metabolomic Signatures of Infant Birth Outcomes: A Multiomics Investigation in an Agricultural Cohort

Carmen J. Marsit, Volha Yakimavets, Warangkana Naksen, Duan Wang, Pimjuta Nimmapirat, Panrapee Suttiwan, Corina Lesseur, Donghai Liang, D. J. Barr, Tippawan Prapamontol, Nancy Fiedler, Supattra Sittiwang, Yewei Wang, Jia Chen, Parinya Panuwet, Amber Burt, Ke Hao, Karen Hermetz
article en

Abstract

Abstract Prenatal environmental exposures may influence fetal growth by disrupting the maternal metabolome and placental function. This exploratory study integrates untargeted maternal serum metabolomics and placental transcriptomics to identify shared molecular pathways through which the maternal environment affects fetal development. Data were drawn from the SAWASDEE birth cohort in northern Thailand, comprising pregnant farmworkers living in an agricultural region with known environmental exposure concerns. Weighted gene coexpression network analysis (WGCNA) of placental transcriptomic data (n = 254) identified gene expression modules, which were analyzed for associations with neonatal outcomes in a subset with paired maternal metabolomics and birth data (n = 40). A placental gene module enriched for myogenesis-related genes was inversely associated with birth weight (β = −0.11, p = 0.03). Seventeen maternal serum metabolic features were associated with both this module and birth weight, including phospholipids related to membrane remodeling and putatively annotated quinoline-containing xenobiotic-like features with structural similarity to combustion-related or industrial compounds. Mediation analysis did not identify statistically significant indirect effects, although one putative xenobiotic-like feature showed a directionally consistent estimate. In this exploratory analysis, these findings identify maternal metabolomic patterns and placental gene networks that are associated with fetal growth and generate hypotheses regarding biologically relevant pathways linking maternal metabolism, placental function, and neonatal growth. Multiomics integration provides a useful exploratory framework for identifying candidate molecular pathways that warrant validation in larger studies.

Environment & Health
Emory University (US), Chulalongkorn University (TH), University of Tennessee Health Science Center (US), Rutgers Sexual and Reproductive Health and Rights (NL), Chiang Mai University (TH), Icahn School of Medicine at Mount Sinai (US)
American Heart Association, National Institute of Environmental Health Sciences
Zero hunger
Openalex Percentile: Top 17%
Metabolomics and Mass Spectrometry Studies
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