Predicting Spontaneous Preterm Birth Using the Immunome

Dorien Feyaerts¹, Ivana Marić², Petra C Arck³, Jelmer R Prins⁴, Nardhy Gomez-Lopez⁵, Brice Gaudillière⁶, Ina A Stelzer⁷

Affiliations

¹ Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA.
² Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, 453 Quarry Road, Palo Alto, CA 94304, USA.
³ Department of Obstetrics and Fetal Medicine and Hamburg Center for Translational Immunology, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20251 Hamburg, Germany.
⁴ Department of Obstetrics and Gynecology, University of Groningen, University Medical Center Groningen, Postbus 30.001, 9700RB, Groningen, The Netherlands.
⁵ Department of Obstetrics and Gynecology, Washington University School of Medicine, 425 S. Euclid Avenue, St. Louis, MO 63110, USA; Department of Pathology and Immunology, Washington University School of Medicine, 425 S. Euclid Avenue, St. Louis, MO 63110, USA.
⁶ Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA; Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, 300 Pasteur Drive, Palo Alto, CA 94304, USA.
⁷ Department of Pathology, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA. Electronic address: istelzer@health.ucsd.edu.

PMID: 38705651
PMCID: PMC12313258
DOI: 10.1016/j.clp.2024.02.013

Review

Predicting Spontaneous Preterm Birth Using the Immunome

Dorien Feyaerts et al. Clin Perinatol. 2024 Jun.

. 2024 Jun;51(2):441-459.

doi: 10.1016/j.clp.2024.02.013. Epub 2024 Apr 4.

Authors

Dorien Feyaerts¹, Ivana Marić², Petra C Arck³, Jelmer R Prins⁴, Nardhy Gomez-Lopez⁵, Brice Gaudillière⁶, Ina A Stelzer⁷

Affiliations

¹ Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA.
² Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, 453 Quarry Road, Palo Alto, CA 94304, USA.
³ Department of Obstetrics and Fetal Medicine and Hamburg Center for Translational Immunology, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20251 Hamburg, Germany.
⁴ Department of Obstetrics and Gynecology, University of Groningen, University Medical Center Groningen, Postbus 30.001, 9700RB, Groningen, The Netherlands.
⁵ Department of Obstetrics and Gynecology, Washington University School of Medicine, 425 S. Euclid Avenue, St. Louis, MO 63110, USA; Department of Pathology and Immunology, Washington University School of Medicine, 425 S. Euclid Avenue, St. Louis, MO 63110, USA.
⁶ Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA; Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, 300 Pasteur Drive, Palo Alto, CA 94304, USA.
⁷ Department of Pathology, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA. Electronic address: istelzer@health.ucsd.edu.

PMID: 38705651
PMCID: PMC12313258
DOI: 10.1016/j.clp.2024.02.013

Abstract

Throughout pregnancy, the maternal peripheral circulation contains valuable information reflecting pregnancy progression, detectable as tightly regulated immune dynamics. Local immune processes at the maternal-fetal interface and other reproductive and non-reproductive tissues are likely to be the pacemakers for this peripheral immune "clock." This cellular immune status of pregnancy can be leveraged for the early risk assessment and prediction of spontaneous preterm birth (sPTB). Systems immunology approaches to sPTB subtypes and cross-tissue (local and peripheral) interactions, as well as integration of multiple biological data modalities promise to improve our understanding of preterm birth pathobiology and identify potential clinically actionable biomarkers.

Keywords: Maternal blood; Maternal immune system; Multiomics modeling; Single-cell cytometry; Spontaneous preterm birth; Spontaneous preterm labor; Whole blood transcriptome.

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Conflict of interest statement

The authors indicate no conflict of interest regarding a financial or non-financial interest in the subject matter discussed in this manuscript.

Figures

**Figure 1:**
Cohort design to evaluate the immunome as a predictor of spontaneous preterm birth (sPTB).

See this image and copyright information in PMC

References

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Predicting Spontaneous Preterm Birth Using the Immunome

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Predicting Spontaneous Preterm Birth Using the Immunome

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