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The association of maternal factors with the neonatal microbiota and health

Author

Listed:
  • Bin Zhu

    (Virginia Commonwealth University
    Virginia Commonwealth University)

  • David J. Edwards

    (Virginia Commonwealth University
    Virginia Commonwealth University)

  • Katherine M. Spaine

    (Virginia Commonwealth University
    Virginia Commonwealth University)

  • Laahirie Edupuganti

    (Virginia Commonwealth University
    Virginia Commonwealth University)

  • Andrey Matveyev

    (Virginia Commonwealth University
    Virginia Commonwealth University)

  • Myrna G. Serrano

    (Virginia Commonwealth University
    Virginia Commonwealth University)

  • Gregory A. Buck

    (Virginia Commonwealth University
    Virginia Commonwealth University
    Virginia Commonwealth University
    Virginia Commonwealth University)

Abstract

The human microbiome plays a crucial role in human health. However, the influence of maternal factors on the neonatal microbiota remains obscure. Herein, our observations suggest that the neonatal microbiotas, particularly the buccal microbiota, change rapidly within 24–48 h of birth but begin to stabilize by 48–72 h after parturition. Network analysis clustered over 200 maternal factors into thirteen distinct groups, and most associated factors were in the same group. Multiple maternal factor groups were associated with the neonatal buccal, rectal, and stool microbiotas. Particularly, a higher maternal inflammatory state and a lower maternal socioeconomic position were associated with a higher alpha diversity of the neonatal buccal microbiota and beta diversity of the neonatal stool microbiota was influenced by maternal diet and cesarean section by 24–72 h postpartum. The risk of admission of a neonate to the newborn intensive care unit was associated with preterm birth as well as higher cytokine levels and probably higher alpha diversity of the maternal buccal microbiota.

Suggested Citation

  • Bin Zhu & David J. Edwards & Katherine M. Spaine & Laahirie Edupuganti & Andrey Matveyev & Myrna G. Serrano & Gregory A. Buck, 2024. "The association of maternal factors with the neonatal microbiota and health," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49160-w
    DOI: 10.1038/s41467-024-49160-w
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    References listed on IDEAS

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    1. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    2. Andrew D Fernandes & Jean M Macklaim & Thomas G Linn & Gregor Reid & Gregory B Gloor, 2013. "ANOVA-Like Differential Expression (ALDEx) Analysis for Mixed Population RNA-Seq," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-15, July.
    3. Tommi Vatanen & Eric A. Franzosa & Randall Schwager & Surya Tripathi & Timothy D. Arthur & Kendra Vehik & Åke Lernmark & William A. Hagopian & Marian J. Rewers & Jin-Xiong She & Jorma Toppari & Anette, 2018. "The human gut microbiome in early-onset type 1 diabetes from the TEDDY study," Nature, Nature, vol. 562(7728), pages 589-594, October.
    4. N. Best & U. Rolle-Kampczyk & F. G. Schaap & M. Basic & S. W. M. Olde Damink & A. Bleich & P. H. M. Savelkoul & M. Bergen & J. Penders & M. W. Hornef, 2020. "Bile acids drive the newborn’s gut microbiota maturation," Nature Communications, Nature, vol. 11(1), pages 1-13, December.
    5. Yan Shao & Samuel C. Forster & Evdokia Tsaliki & Kevin Vervier & Angela Strang & Nandi Simpson & Nitin Kumar & Mark D. Stares & Alison Rodger & Peter Brocklehurst & Nigel Field & Trevor D. Lawley, 2019. "Stunted microbiota and opportunistic pathogen colonization in caesarean-section birth," Nature, Nature, vol. 574(7776), pages 117-121, October.
    6. Tanya Yatsunenko & Federico E. Rey & Mark J. Manary & Indi Trehan & Maria Gloria Dominguez-Bello & Monica Contreras & Magda Magris & Glida Hidalgo & Robert N. Baldassano & Andrey P. Anokhin & Andrew C, 2012. "Human gut microbiome viewed across age and geography," Nature, Nature, vol. 486(7402), pages 222-227, June.
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