Precision medicine approaches to understand and prevent stillbirth

Stillbirth (i.e., fetal demise after 20 weeks’ gestation) is a common and devastating adverse pregnancy outcome that affects 1 in 160 pregnancies (~23,600 pregnancies in the US each year) and has lifelong medical and psychosocial impacts for affected individuals and their families. Rates of stillbirth are alarmingly disparate among US populations—non-Hispanic Black, American Indian/Alaskan Native, and Pacific Islander-identifying individuals have a 2-fold higher stillbirth rate compared to other racial groups. Available data does not explain the basis for these disparities and lacks fundamental social determinants of health (SDOH) information. While placental pathology, fetal autopsy, and genetic testing are the highest yield tests for determining the cause of fetal demise, many patients do not have a complete workup due to patient, provider, and systems-level issues. Finally, despite advances in non-invasive technologies to assess placental function and overall pregnancy health across gestation, the mechanisms underlying placental dysfunction at the maternal-fetal interface remain poorly understood, stillbirth remains difficult to predict, and preventative measures are limited. Multi-disciplinary interventions at all levels are urgently needed to address stillbirth outcomes. In recognition of this urgent need, the NIH-NICHD released the NOSI, “The Road to Prevention of Stillbirth” to support transdisciplinary stillbirth research efforts. In response to this NOSI, we leverage the international infrastructure of the Fetal Genomics Consortium (FCG) and the local infrastructure of the University of Washington Pregnancy Biorepository (WPR) to launch a multi-faceted initiative to: improve clinical evaluation and data collection for stillbirth, advance tools to evaluate maternal-fetal interface immune biology and detect placenta dysfunction, and develop novel models to predict an individual’s risk of stillbirth. Specifically, we aim to: (1) standardize clinical evaluation, genetic testing, and data collection from patients with stillbirth by implementing a Stillbirth Evaluation Pathway across the University of Washington (UW) hospital network; (2) delineate maternal-fetal interface genomic and immune signatures associated with placental dysfunction and stillbirth using paired maternal-fetal whole genome sequencing data, cell-free DNA/RNA metrics, and placental immune signatures; and (3) develop a personalized, high-fidelity tool using machine learning approaches to predict the risk for stillbirth in pregnant individuals longitudinally. Taken together, these aims will facilitate a precision medicine approach for stillbirth and advance equity in care. The rich dataset of integrated clinical, SDOH, and genomic information harmonized within the larger infrastructure of the FGC network will create an invaluable tool for the research community for future investigations. Ultimately, these insights will enable the development of novel interventions, therapeutics, and prevention strategies with the potential to dramatically improve reproductive health. Project Number: 1R01HD117802-01 | Fiscal Year: 2025 | NIH Institute/Center: Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) | Principal Investigator: Kathryn Gray | Institution: UNIVERSITY OF WASHINGTON, SEATTLE, WA | Award Amount: $661,258 | Activity Code: R01 | Study Section: Reproductive, Perinatal and Pediatric Health Study Section[RPPH] View on NIH RePORTER: https://reporter.nih.gov/project-details/1R01HD11780201