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  • Clinical Research Article
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Composition of the maternal gastrointestinal microbiome as a predictor of neonatal birth weight

Pediatric Research volume 94, pages 1158–1165 (2023)Cite this article

Abstract

Background

The biological mechanism by which the maternal gastrointestinal microbiota contributes to fetal growth and neonatal birth weight is currently unknown. The purpose of this study was to explore how the composition of the maternal microbiome in varying pre-gravid body mass index (BMI) groups are associated with neonatal birth weight adjusted for gestational age.

Methods

Retrospective, cross-sectional metagenomic analysis of bio-banked fecal swab biospecimens (n = 102) self-collected by participants in the late second trimester of pregnancy.

Results

Through high-dimensional regression analysis using principal components (PC) of the microbiome, we found that the best performing multivariate model explained 22.9% of the variation in neonatal weight adjusted for gestational age. Pre-gravid BMI (p = 0.05), PC3 (p = 0.03), and the interaction of the maternal microbiome with maternal blood glucose on the glucose challenge test (p = 0.01) were significant predictors of neonatal birth weight after adjusting for potential confounders including maternal antibiotic use during gestation and total gestational weight gain.

Conclusions

Our results indicate a significant association between the maternal gastrointestinal microbiome in the late second trimester and neonatal birth weight adjusted for gestational age. Moderated by blood glucose at the time of the universal glucose screening, the gastrointestinal microbiome may have a role in the regulation of fetal growth.

Impact

  • Maternal blood glucose in the late second trimester significantly moderates the relationship between the maternal gastrointestinal microbiome and neonatal size adjusted for gestational age.

  • Our findings provide preliminary evidence for fetal programming of neonatal birth weight through the maternal gastrointestinal microbiome during pregnancy.

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Fig. 1: Top 30 microbial taxa in the composition of principal component 3 (PC3).

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Data availability

The raw sequencing reads used in this study are publically available through the National Center for Biotechnology Information (NCBI) under the accession identifier PRJNA862188. The clinical metadata are available upon reasonable request from the Obstetric and Neonatal Outcomes Study (ONOS) research team at the University of Virginia Health System.

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Acknowledgements

We would like to thank Briana Cortez Chronister and Wuxing Yuan for their contributions to this study. Further, we thank Research Computing at The University of Virginia for providing computational resources and technical support that have contributed to the results reported within this publication (URL: https://rc.virginia.edu).

Funding

This research was supported with funding from F31NR017821 (to C.D.), the Association for Women’s Health, Obstetric, and Neonatal Nurses 2018 March of Dimes Margaret Comerford Freda “Saving Babies, Together®” Award (to C.D.).

Author information

Authors and Affiliations

  1. School of Nursing, University of Virginia, Charlottesville, VA, USA

    Caitlin Dreisbach, Laura Habermeyer & Jeanne Alhusen

  2. Data Science Institute, Columbia University, New York, NY, USA

    Caitlin Dreisbach

  3. School of Nursing, University of Rochester, Rochester, NY, USA

    Caitlin Dreisbach

  4. College of Nursing, University of South Florida, Tampa, FL, USA

    Stephanie Prescott

  5. Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA

    Stephanie Prescott, John McCulloch & Giorgio Trinchieri

  6. School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, USA

    Anna Maria Siega-Riz

  7. Division of Maternal-Fetal Medicine, University of Virginia Health System, Charlottesville, VA, USA

    Donald Dudley

  8. Department of Pediatrics, Division of Developmental Medicine, Boston Children’s Hospital, Boston, MA, USA

    Caroline Kelsey

  9. Department of Pediatrics, Harvard Medical School, Boston, MA, USA

    Caroline Kelsey

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  1. Caitlin Dreisbach
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Contributions

C.D., A.M.S.-R., and J.A. designed and conceptualized the study; A.M.S.-R. and D.D. oversaw the data repository and parent study; S.P. and G.T. supported the sequencing of the biospecimens; C.D., J.M., and C.K. completed the data analysis with clinical data support from L.H. C.D. drafted the manuscript with all other authors providing substantive feedback and final approval.

Corresponding author

Correspondence to Caitlin Dreisbach.

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The authors declare no competing interests.

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Participants gave consent for use of their biospecimens and medical record data for the purposes of research in the Obstetric and Neonatal Outcomes Study. No new consent was required.

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Dreisbach, C., Prescott, S., Siega-Riz, A.M. et al. Composition of the maternal gastrointestinal microbiome as a predictor of neonatal birth weight. Pediatr Res 94, 1158–1165 (2023). https://doi.org/10.1038/s41390-023-02584-4

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