Abstract

Based upon our recent insights into the determinants of preterm birth, which is the leading cause of death in children under five years of age worldwide, we describe potential analytic frameworks that provides both a common understanding and, ultimately the basis for effective, ameliorative action. Our research on preterm birth serves as an example that the framing of any human health condition is a result of complex interactions between the genome and the exposome. New discoveries of the basic biology of pregnancy, such as the complex immunological and signaling processes that dictate the health and length of gestation, have revealed a complexity in the interactions (current and ancestral) between genetic and environmental forces. Understanding of these relationships may help reduce disparities in preterm birth and guide productive research endeavors and ultimately, effective clinical and public health interventions.

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References

  1. 1.

    Li J, Hong X, Mesiano S, Muglia LJ, Wang X, Snyder M, et al. Natural selection has differentiated the progesterone receptor among human populations. Am J Hum Genet. 2018;103:45–57.

  2. 2.

    Liu L, Oza S, Hogan D, Chu Y, Perin J, Zhu J, et al. Global, regional, and national causes of under-5 mortality in 2000-15: an updated systematic analysis with implications for the Sustainable Development Goals. Lancet. 2016;388:3027–35.

  3. 3.

    Timpson NJ, Greenwood CMT, Soranzo N, Lawson DJ, Richards JB. Genetic architecture: the shape of the genetic contribution to human traits and disease. Nat Rev Genet. 2018;19:110–24.

  4. 4.

    Wise PH, Shaw GM, Druzin ML, Darmstadt GL, Quaintance C, Makinen E, et al. Risky business: meeting the structural needs of transdisciplinary science. J Pediatr. 2017;191:255–8.

  5. 5.

    Stevenson DK, Shaw GM, Wise PH, Norton ME, Druzin ML, Valantine HA, et al. Transdisciplinary translational science and the case of preterm birth. J Perinatol. 2013;33:251–8.

  6. 6.

    Muglia LJ, Katz M. The enigma of spontaneous preterm birth. N Engl J Med. 2010;362:529–35.

  7. 7.

    Ghaemi MS, DiGiulio DB, Contrepois K, Callahan BJ, Ngo TTM, Lee-McMullen B, et al. Multiomics modeling of the immunome, transcriptome, microbiome, proteome, and metabolome adaptations during human pregnancy. Bioinformatics. 2018; https://doi.org/10.1093/bioinformatics/bty537.

  8. 8.

    Sirota M, Thomas CG, Liu R, Zuhl M, Banerjee P, Wong RJ, et al. Enabling precision medicine in neonatology, an integrated repository for preterm birth research. Sci Data. 2018;5:180219.

  9. 9.

    Fan HC, Blumenfeld YJ, Chitkara U, Hudgins L, Quake SR. Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood. Proc Natl Acad Sci USA. 2008;105:16266–71.

  10. 10.

    Pan W, Ngo TTM, Camunas-Soler J, Song CX, Kowarsky M, Blumenfeld YJ, et al. Simultaneously monitoring immune response and microbial infections during pregnancy through plasma cfRNA sequencing. Clin Chem. 2017;63:1695–704.

  11. 11.

    Ngo TTM, Moufarrej MN, Rasmussen MH, Camunas-Soler J, Pan W, Okamoto J, et al. Noninvasive blood tests for fetal development predict gestational age and preterm delivery. Science. 2018;360:1133–6.

  12. 12.

    Bandura DR, Baranov VI, Ornatsky OI, Antonov A, Kinach R, Lou X, et al. Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Anal Chem. 2009;81:681322.

  13. 13.

    Bendall SC, Simonds EF, Qiu P, Amir el AD, Krutzik PO, Finck R, et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science. 2011;332:687–96.

  14. 14.

    Fragiadakis GK, Baca QJ, Gherardini PF, Ganio EA, Gaudilliere DK, Tingle M, et al. Mapping the fetomaternal peripheral immune system at term pregnancy. J Immunol. 2016;197:4482–92.

  15. 15.

    Gaudilliere B, Ganio EA, Tingle M, Lancero HL, Fragiadakis GK, Baca QJ, et al. Implementing mass cytometry at the bedside to study the immunological basis of human diseases: distinctive immune features in patients with a history of term or preterm birth. Cytometry A. 2015;87:817–29.

  16. 16.

    Bengsch B, Ohtani T, Khan O, Setty M, Manne S, O’Brien S, et al. Epigenomic-guided mass cytometry profiling reveals disease-specific features of exhausted CD8 T cells. Immunity. 2018;48:1029-45–e1025.

  17. 17.

    Frei AP, Bava FA, Zunder ER, Hsieh EW, Chen SY, Nolan GP, et al. Highly multiplexed simultaneous detection of RNAs and proteins in single cells. Nat Methods. 2016;13:269–75.

  18. 18.

    Aghaeepour N, Ganio EA, McIlwain D, Tsai AS, Tingle M, Van Gassen S, et al. An immune clock of human pregnancy. Sci Immunol. 2017;2:eaan2946.

  19. 19.

    Owen CM, Goldstein EH, Clayton JA, Segars JH. Racial and ethnic health disparities in reproductive medicine: an evidence-based overview. Semin Reprod Med. 2013;31:317–24.

  20. 20.

    Ehn NL, Cooper ME, Orr K, Shi M, Johnson MK, Caprau D, et al. Evaluation of fetal and maternal genetic variation in the progesterone receptor gene for contributions to preterm birth. Pediatr Res. 2007;62:630–5.

  21. 21.

    Langmia IM, Apalasamy YD, Omar SZ, Mohamed Z. Progesterone Receptor (PGR) gene polymorphism is associated with susceptibility to preterm birth. BMC Med Genet. 2015;16:63.

  22. 22.

    Manuck TA, Lai Y, Meis PJ, Dombrowski MP, Sibai B, Spong CY, et al. Progesterone receptor polymorphisms and clinical response to 17-alpha-hydroxyprogesterone caproate. Am J Obstet Gynecol. 2011;205:135 e131–9.

  23. 23.

    Zachariades E, Mparmpakas D, Pang Y, Rand-Weaver M, Thomas P, Karteris E. Changes in placental progesterone receptors in term and preterm labour. Placenta. 2012;33:367–72.

  24. 24.

    Yudell M, Roberts D, DeSalle R, Tishkoff S. Science and society. Taking race out of human genetics. Science. 2016;351:564–5.

  25. 25.

    DiGiulio DB, Callahan BJ, McMurdie PJ, Costello EK, Lyell DJ, Robaczewska A, et al. Temporal and spatial variation of the human microbiota during pregnancy. Proc Natl Acad Sci USA. 2015;112:11060–5.

  26. 26.

    Callahan BJ, DiGiulio DB, Goltsman DSA, Sun CL, Costello EK, Jeganathan P, et al. Replication and refinement of a vaginal microbial signature of preterm birth in two racially distinct cohorts of US women. Proc Natl Acad Sci USA. 2017;114:9966–71.

  27. 27.

    Shachar BZ, Mayo JA, Lyell DJ, Baer RJ, Jeliffe-Pawlowski LL, Stevenson DK, et al. Interpregnancy interval after live birth or pregnancy termination and estimated risk of preterm birth: a retrospective cohort study. BJOG. 2016;123:2009–17.

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Funding

This work was supported in part by the Bill and Melinda Gates Foundation, the March of Dimes Prematurity Research Center at Stanford University, and the Charles and Marie Robertson Foundation.

Author information

Affiliations

  1. Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA

    • David K. Stevenson
    • , Ronald J. Wong
    • , Gary L. Darmstadt
    • , Jeffrey B. Gould
    • , Michael Katz
    • , Jingjing Li
    • , Cecele C. Quaintance
    • , Gary M. Shaw
    •  & Paul H. Wise
  2. Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA

    • Nima Aghaeepour
    • , Martin S. Angst
    •  & Brice Gaudilliere
  3. Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA

    • Daniel B. DiGiulio
    •  & David A. Relman
  4. Infectious Diseases Section, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, 94306, USA

    • Daniel B. DiGiulio
    •  & David A. Relman
  5. Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, 94305, USA

    • Maurice L. Druzin
    •  & Ronald S. Gibbs
  6. Department of Genetics, Stanford Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA

    • Jingjing Li
    •  & Michael P. Snyder
  7. Departments of Bioengineering and Applied Physics, Stanford University and Chan Zuckerberg Biohub, Stanford, CA, 94305, USA

    • Mira N. Moufarrej
    •  & Stephen R. Quake
  8. Center on the Early Life Origins of Disease, Department of Population, Family and Reproductive Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, 21205, USA

    • Xiaobin Wang
  9. Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA

    • Xiaobin Wang

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Conflict of interest

The authors declare that they have no conflict of interest.

Corresponding author

Correspondence to David K. Stevenson.

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https://doi.org/10.1038/s41372-018-0298-1