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References
Stevenson, D. K. et al. Transdisciplinary translational science and the case of preterm birth. J. Perinatol. 33, 251–258 (2013).
Iams, J. D. et al. The length of the cervix and the risk of spontaneous premature delivery. National Institute of Child Health and Human Development Maternal Fetal Medicine Unit Network. N. Engl. J. Med. 334, 567–572 (1996).
Meis, P. J. et al. Prevention of recurrent preterm delivery by 17 alpha-hydroxyprogesterone caproate. N. Engl. J. Med. 348, 2379–2385 (2003).
Hoffman, M. K. et al. Low-dose aspirin for the prevention of preterm delivery in nulliparous women with a singleton pregnancy (ASPIRIN): a randomised, double-blind, placebo-controlled trial. Lancet 39, 285–293 (2020).
Ghaemi, M. S. et al. Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy. Bioinformatics 35, 95–103 (2019).
Muglia, L. J. & Katz, M. The enigma of spontaneous preterm birth. N. Engl. J. Med 362, 529–535 (2010).
Romero, R., Dey, S. K. & Fisher, S. J. Preterm labor: one syndrome, many causes. Science 345, 760–765 (2014).
Stevenson, D. K. et al. Understanding health disparities. J. Perinatol. 39, 354–358 (2019).
Yudell, M., Roberts, D., DeSalle, R. & Tishkoff, S. Science and Society. Taking race out of human genetics. Science 351, 564–565 (2016).
Li, J. et al. Natural selection has differentiated the progesterone receptor among human populations. Am. J. Hum. Genet. 103, 45–57 (2018).
Stevenson, D. K. et al. The contributions of genetics to premature birth. Pediatr. Res. 85, 416–417 (2019).
Gracie, S. et al. An integrated systems biology approach to the study of preterm birth using “-omic” technology—a guideline for research. BMC Pregnancy Childbirth 11, 71 (2011).
Goldenberg, R. L., Culhane, J. F., Iams, J. D. & Romero, R. Epidemiology and causes of preterm birth. Lancet 371, 75–84 (2008).
Wallenstein, M. B., Shaw, G. M. & Stevenson, D. K. Preterm birth as a calendar event or immunologic anomaly. JAMA Pediatr. 170, 525–526 (2016).
Zhao, H., Ozen, M., Wong, R. J. & Stevenson, D. K. Heme oxygenase-1 in pregnancy and cancer: similarities in cellular invasion, cytoprotection, angiogenesis, and immunomodulation. Front. Pharm. 5, 295 (2014).
Trowsdale, J. & Betz, A. G. Mother’s little helpers: mechanisms of maternal-fetal tolerance. Nat. Immunol. 7, 241–246 (2006).
Ozen, M., Zhao, H., Lewis, D. B., Wong, R. J. & Stevenson, D. K. Heme oxygenase and the immune system in normal and pathological pregnancies. Front. Pharm. 6, 84 (2015).
Druckmann, R. & Druckmann, M. A. Progesterone and the immunology of pregnancy. J. Steroid Biochem. Mol. Biol. 97, 389–396 (2005).
Bygren, L. O., Kaati, G. & Edvinsson, S. Longevity determined by paternal ancestors’ nutrition during their slow growth period. Acta Biotheor. 49, 53–59 (2001).
Maric, I. et al. Data-driven queries between medications and spontaneous preterm birth among 2.5 million pregnancies. Birth Defects Res. 111, 1145–1153 (2019).
Greenberg, D. R. et al. Disease burden in offspring is associated with changing paternal demographics in the United States. Andrology https://doi.org/10.1111/andr.12700 (2019).
Mayo, J. A., Lu, Y., Stevenson, D. K., Shaw, G. M. & Eisenberg, M. L. Parental age and stillbirth: a population-based cohort of nearly 10 million California deliveries from 1991 to 2011. Ann. Epidemiol. 31, 32–37 e32 (2019).
Khandwala, Y. S. et al. Association of paternal age with perinatal outcomes between 2007 and 2016 in the United States: population based cohort study. BMJ 363, k4372 (2018).
Northstone, K., Golding, J., Davey Smith, G., Miller, L. L. & Pembrey, M. Prepubertal start of father’s smoking and increased body fat in his sons: further characterisation of paternal transgenerational responses. Eur. J. Hum. Genet. 22, 1382–1386 (2014).
Moss, J. L. & Harris, K. M. Impact of maternal and paternal preconception health on birth outcomes using prospective couples’ data in Add Health. Arch. Gynecol. Obstet. 291, 287–298 (2015).
Shaw, G. M. et al. Residential agricultural pesticide exposures and risks of preeclampsia. Environ. Res. 164, 546–555 (2018).
Shaw, G. M. et al. Residential agricultural pesticide exposures and risks of spontaneous preterm birth. Epidemiology 29, 8–21 (2018).
Sirota, M. et al. Enabling precision medicine in neonatology, an integrated repository for preterm birth research. Sci. Data 5, 180219 (2018).
Callahan, B. J. 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 114, 9966–9971 (2017).
DiGiulio, D. B. et al. Temporal and spatial variation of the human microbiota during pregnancy. Proc. Natl. Acad. Sci. USA 112, 11060–11065 (2015).
Ngo, T. T. M. et al. Noninvasive blood tests for fetal development predict gestational age and preterm delivery. Science 360, 1133–1136 (2018).
Pan, W. et al. Simultaneously monitoring immune response and microbial infections during pregnancy through plasma cfRNA sequencing. Clin. Chem. 63, 1695–1704 (2017).
Goltsman, D. S. A. et al. Metagenomic analysis with strain-level resolution reveals fine-scale variation in the human pregnancy microbiome. Genome Res. 28, 1467–1480 (2018).
Fan, H. C. & Quake, S. R. Sensitivity of noninvasive prenatal detection of fetal aneuploidy from maternal plasma using shotgun sequencing is limited only by counting statistics. PLoS ONE 5, e10439 (2010).
Koh, W. et al. Single cell gene transcriptomes derived from human cervical and uterine tissue during pregnancy. Adv. Biosyst. 3, 1800336 (2019).
Aghaeepour, N. et al. An immune clock of human pregnancy. Sci. Immunol. 2, eaan2946 (2017).
Peterson, L. S. et al. Multiomic immune clockworks of pregnancy. Semin. Immunopathol. https://doi.org/10.1007/s00281-019-00772-1 (2020).
Bandura, D. R. et al. Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Anal. Chem. 81, 6813–6822 (2009).
Bendall, S. C. et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332, 687–696 (2011).
Gaudilliere, B. 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. Cytom. A 87, 817–829 (2015).
Nadeau-Vallee, M. et al. Novel noncompetitive IL-1 receptor-biased ligand prevents infection- and inflammation-induced preterm birth. J. Immunol. 195, 3402–3415 (2015).
Quiniou, C. et al. Development of a novel noncompetitive antagonist of IL-1 receptor. J. Immunol. 180, 6977–6987 (2008).
Han, X. et al. Differential dynamics of the maternal immune system in healthy pregnancy and preeclampsia. Front. Immunol. 10, 1305 (2019).
Rosenzwajg, M. et al. Immunological and clinical effects of low-dose interleukin-2 across 11 autoimmune diseases in a single, open clinical trial. Ann. Rheum. Dis. 78, 209–217 (2019).
Klatzmann, D. & Abbas, A. K. The promise of low-dose interleukin-2 therapy for autoimmune and inflammatory diseases. Nat. Rev. Immunol. 15, 283–294 (2015).
Ferrero, D. M. et al. Cross-country individual participant analysis of 4.1 million singleton births in 5 countries with very high human development index confirms known associations but provides no biologic explanation for 2/3 of all preterm births. PLoS ONE 11, e0162506 (2016).
Akolekar, R., Syngelaki, A., Poon, L., Wright, D. & Nicolaides, K. H. Competing risks model in early screening for preeclampsia by biophysical and biochemical markers. Fetal Diagn. Ther. 33, 8–15 (2013).
Francisco, C., Wright, D., Benko, Z., Syngelaki, A. & Nicolaides, K. H. Competing-risks model in screening for pre-eclampsia in twin pregnancy according to maternal factors and biomarkers at 11-13 weeks’ gestation. Ultrasound Obstet. Gynecol. 50, 589–595 (2017).
Oskovi Kaplan, Z. A. & Ozgu-Erdinc, A. S. Prediction of preterm birth: maternal characteristics, ultrasound markers, and biomarkers: an updated overview. J. Pregnancy 2018, 8367571 (2018).
Stout, M. J. et al. First trimester serum analytes, maternal characteristics and ultrasound markers to predict pregnancies at risk for preterm birth. Placenta 34, 14–19 (2013).
Hastie, T., Tibshirani, R. & Freidman, J. The Elements of Statistical Learning 2nd edn (Springer-Verlag, Switzerland, 2009).
Stone, M. Cross-validatory choice and assessment of statistical predictions. J. R. Stat. Soc.: Ser. B (Methodol.) 38, 102 (1976).
Wolpert, D. H. Stacked generalization. Neural Netw. 5, 241–259 (1992).
Breiman, L. Stacked regressions. Mach. Learn. 24, 49–64 (1996).
Vapnik, V. N. The Nature of Statistical Learning Theory 2nd edn. (Springer, New York, 1995).
Koller, D. Probabilistic Graphical Models Principles and Techniques (Massachusetts Institute of Technology, Boston, 2009).
Sinoquet, C. in Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics (ed. Mourad, R.) 3−49 (Oxford University Press, London, 2014).
Tibshirani, R. & Friedman, J. A pliable lasso. Preprint at https://arxiv.org/abs/1712.00484 (2018).
Tibshirani, R. Regression shrinkage and selection via the lasso. J. R. Stat. Soc.: Ser. B (Methodol.) 58, 267 (1996).
Hastie, T. & Tibshirani, R. Varying-coefficient models. J. R. Stat. Soc.: Ser. B (Methodol.) 55, 757 (1993).
Lewis, C., Hoggatt, K. J. & Ritz, B. The impact of different causal models on estimated effects of disinfection by-products on preterm birth. Environ. Res. 111, 371–376 (2011).
Koopman, J. S. & Lynch, J. W. Individual causal models and population system models in epidemiology. Am. J. Public Health 89, 1170–1174 (1999).
Barlas, Y. & Carpenter, S. Philosophical roots of model validation: two paradigms. Syst. Dyn. Rev. 6, 148–166 (1990).
Le, B. L., Iwatani, S., Wong, R. J., Stevenson, D. K. & Sirota, M. Computational discovery of therapeutic candidates for preventing preterm birth. JCI Insight 5, 133761 (2020).
Beck, A. F. et al. The color of health: how racism, segregation, and inequality affect the health and well-being of preterm infants and their families. Pediatr. Res. 87, 227–234 (2020).
Wise, P. H. The anatomy of a disparity in infant mortality. Annu. Rev. Public Health 24, 341–362 (2003).
Owen, C. M., Goldstein, E. H., Clayton, J. A. & Segars, J. H. Racial and ethnic health disparities in reproductive medicine: an evidence-based overview. Semin. Reprod. Med. 31, 317–324 (2013).
Goetz, L. H. & Schork, N. J. Personalized medicine: motivation, challenges, and progress. Fertil. Steril. 109, 952–963 (2018).
Weil, A. R. Precision medicine. Health Aff. (Millwood) 37, 687 (2018).
Minor, L. & Rees, M. Discovering Precision Health: Predict, Prevent, and Cure to Advance Health and Well-Being (Wiley-Blackwell, New Jersey, 2020).
Leon, L. J. et al. Preeclampsia and cardiovascular disease in a large uk pregnancy cohort of linked electronic health records: a CALIBER study. Circulation 140, 1050–1060 (2019).
Acknowledgements
We thank Laura Hedli for her critical review of the manuscript. This work was supported in part by the Bill and Melinda Gates Foundation, the March of Dimes Prematurity Research Center at Stanford University, the Charles and Marie Robertson Foundation, the Christopher Hess Research Fund, the Charles B. and Ann L. Johnson Endowed Fund, and the Prematurity Research Fund.
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D.K.S., R.J.W., N.A., I.M., M.S.A., K.C., G.L.D., M.L.D., M.L.E., B.G., R.S.G., I.H.G., J.B.G., H.C.L., X.B.L., J.A.M., M.N.M., C.C.Q., S.R.Q., D.A.R., M.S., M.P.S., K.G.S., S.H., P.H.W., G.M.S., and M.K. contributed to the writing and approval of the final version of the manuscript.
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Stevenson, D.K., Wong, R.J., Aghaeepour, N. et al. Towards personalized medicine in maternal and child health: integrating biologic and social determinants. Pediatr Res 89, 252–258 (2021). https://doi.org/10.1038/s41390-020-0981-8
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DOI: https://doi.org/10.1038/s41390-020-0981-8
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