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Maternal and newborn metabolomic changes associated with urinary polycyclic aromatic hydrocarbon metabolite concentrations at delivery: an untargeted approach

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Abstract

Introduction

Prenatal exposure to polycyclic aromatic hydrocarbons (PAHs) has been associated with adverse human health outcomes. To explore the plausible associations between maternal PAH exposure and maternal/newborn metabolomic outcomes, we conducted a cross-sectional study among 75 pregnant people from Cincinnati, Ohio.

Method

We quantified 8 monohydroxylated PAH metabolites in maternal urine samples collected at delivery. We then used an untargeted high-resolution mass spectrometry approach to examine alterations in the maternal (n = 72) and newborn (n = 63) serum metabolome associated with PAH metabolites. Associations between individual maternal urinary PAH metabolites and maternal/newborn metabolome were assessed using linear regression adjusted for maternal and newborn factors while accounting for multiple testing with the Benjamini-Hochberg method. We then conducted functional analysis to identify potential biological pathways.

Results

Our results from the metabolome-wide associations (MWAS) indicated that an average of 1% newborn metabolome features and 2% maternal metabolome features were associated with maternal urinary PAH metabolites. Individual PAH metabolite concentrations in maternal urine were associated with maternal/newborn metabolome related to metabolism of vitamins, amino acids, fatty acids, lipids, carbohydrates, nucleotides, energy, xenobiotics, glycan, and organic compounds.

Conclusion

In this cross-sectional study, we identified associations between urinary PAH concentrations during late pregnancy and metabolic features associated with several metabolic pathways among pregnant women and newborns. Further studies are needed to explore the mediating role of the metabolome in the relationship between PAHs and adverse pregnancy outcomes.

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Data Availability

Raw data would be available upon request to the corresponding authors. The R code to perform the analyses are available via a GitHub repository: https://github.com/jagadeeshpuvvula/PAH_MWAS.

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Acknowledgements

We acknowledge the staff assistance from Department of Obstetrics and Gynecology at University of Cincinnati in participant recruitment. We are thankful to our study participants for their time and efforts.

Funding

This research was funded by pilot projects from the National Institute of Environmental Health Sciences (NIEHS) and supported by the Center of Environmental Genetics (P30ES006096) at the University of Cincinnati. This project was also supported by grants from the Veteran Affairs [VA-I01BX005395 (SMH, YKL), VA‐IK6BX006182 (SMH)], NIEHS [R01ES032675 (SMH, YKL), P30ES013508, R01ES028277 (AC), R01ES033054 (AC), R01ES032836 (JMB)], Department of Defense [DoD‐W81XWH‐22‐1‐0152 (SMH, YKL, AC)], and National Science Foundation [RII Track‐2 FEC, Award #2217824 (SMH, YKL)].

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Authors and Affiliations

  1. Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Jagadeesh Puvvula & Aimin Chen

  2. School of Engineering, Brown University, Providence, RI, USA

    Kathrine E. Manz & Kurt D. Pennell

  3. Department of Epidemiology, Brown University, Providence, RI, USA

    Joseph M. Braun

  4. Department of Obstetrics and Gynecology, College of Medicine, University of Cincinnati, Cincinnati, OH, USA

    Emily A. DeFranco

  5. Department of Pharmacology and Toxicology, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA

    Shuk-Mei Ho & Yuet-Kin Leung

  6. Department of Environmental & Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, OH, USA

    Shouxiong Huang & Zana P. Percy

  7. Department of Epidemiology and Biostatistics, School of Public Health, University of Nevada Las Vegas, Las Vegas, NV, USA

    Ann M. Vuong

  8. Health Research, Battelle Memorial Institute, Columbus, OH, USA

    Stephani S. Kim

  9. College of Arts & Sciences, University of Pennsylvania, Philadelphia, PA, USA

    Priyanka Bhashyam & Raymund Lee

  10. Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University, Atlanta, GA, USA

    Dean P. Jones & Vilinh Tran

  11. Immunology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Dasom V. Kim

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  1. Jagadeesh Puvvula
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Contributions

AC, JP, KEM, JMB, AMV, SMH, YKL, SSK, ZPP, EAD, and SH conceptualized the study. EDF collected maternal urine, for exposure assessment; and blood (maternal and cord) for metabolomics. DK processed blood samples for metabolomics. KEM, KDP, DPJ, and VT provided metabolomics expertise and performed untargeted metabolome assays. JP performed statistical analysis with guidance from AC, JMB, and KEM. JP drafted the manuscript. All authors reviewed, edited, and approved the final version of the manuscript.

Corresponding authors

Correspondence to Jagadeesh Puvvula or Aimin Chen.

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All procedures performed in this study involve human subjects were in compliance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all the subjects included in this study.

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The authors declare no competing interests.

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Puvvula, J., Manz, K.E., Braun, J.M. et al. Maternal and newborn metabolomic changes associated with urinary polycyclic aromatic hydrocarbon metabolite concentrations at delivery: an untargeted approach. Metabolomics 20, 6 (2024). https://doi.org/10.1007/s11306-023-02074-y

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