New biomarkers for the detection of fetal death derived from large-scale proteomic analysis of maternal plasma

Authors

• Roberto Romero, Pregnancy Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, and Detroit, MI; Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI; Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI; George Washington University, School of Medicine and Health Sciences, Washington, DC, United States. Electronic address: [email protected].
• Gaurav Bhatti, Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI. Electronic address: [email protected].
• Tinnakorn Chaiworapongsa, Pregnancy Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, and Detroit, MI; Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI.
• Nardhy Gomez-Lopez, Pregnancy Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, and Detroit, MI; Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI; Center for Reproductive Health Sciences, Departments of Obstetrics and Gynecology and Pathology and Immunology, Washington University School of Medicine, St. Louis, MO.
• Arun Meyyazhagan, Pregnancy Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, and Detroit, MI; Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI; Department of Life Sciences, Christ University, Bengaluru, India.
• Piya Chaemsaithong, Pregnancy Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, and Detroit, MI; Department of Obstetrics and Gynecology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; Program in Translational Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
• Eunjung Jung, Pregnancy Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, and Detroit, MI; Department of Pathology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea.
• Awoniyi O. Awonuga, Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI.
• Yeon Mee Kim, Department of Pathology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea.
• Dereje W. Gudicha, Pregnancy Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services, Bethesda, MD, and Detroit, MI.
• Chong Jai Kim, Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
• David R. Bryant, Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI.
• Sonia S. Hassan, Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI; Department of Physiology, Wayne State University School of Medicine, Detroit, MI; Office of Women's Health, Wayne State University, Detroit, MI, USA.
• Adi L. Tarca, Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI; Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI; Department of Computer Science, Wayne State University College of Engineering, Detroit, MI. Electronic address: [email protected].

Document Type

Journal Article

Publication Date

4-2-2026

Journal

American journal of obstetrics and gynecology

DOI

10.1016/j.ajog.2026.03.029

Keywords

DNAJB9 protein; Glucose-6-phosphate 1-dehydrogenase; Glycoprotein hormones alpha chain; Hepcidin; Placental growth factor; RNA polymerase III subunit C10; Transcobalamin-2; Vascular endothelial growth factor receptor-1; angiogenesis; aptamer; biomarker; blood proteins; fetal death; high-throughput screening assay; proteome; soluble fms like tyrosine kinase 1

Abstract

BACKGROUND: Normal pregnancy involves modulation of thousands of maternal plasma proteins, and departures from the normal trajectories may be indicative of the development of adverse pregnancy outcomes. A decrease in placental growth factor (PlGF) and an increase in soluble fms-like tyrosine kinase 1 (sFlt-1) in maternal plasma were shown to be associated with fetal death at the time of diagnosis and to predict this devastating pregnancy outcome at 24-28 weeks of gestation. However, these proteomic dysregulations are also present in other obstetrical syndromes, and more specific and sensitive biomarkers are needed to implement preventive strategies. OBJECTIVE: To identify candidate protein biomarkers that can improve the prediction of fetal death relative to PlGF and sFlt-1. STUDY DESIGN: This retrospective case-control study included 38 patients who experienced fetal death (cases) and 23 with uncomplicated pregnancy (controls). Plasma samples were collected at the time of diagnosis (20-41 weeks of gestation) from cases and during routine care from gestational-age-matched controls. An aptamer-based multiplex assay was used to measure the abundance of >7000 protein analytes. Differential protein abundance was assessed by using linear models with adjustment for gestational age at sample collection. Significance was inferred using moderated t-test adjusted p-value <0.1 and a fold-change >1.25. Hypergeometric tests were performed to identify gene ontology biological processes enriched among proteins with significant change in abundance. Random forest models were trained and evaluated via cross-validation to distinguish between fetal death cases and controls and to pinpoint the most salient predictors. RESULTS: Among the 7146 protein assays tested, 97 assays (1.4%) corresponding to 87 unique proteins differed significantly in abundance between fetal death cases and controls: 63/87 proteins (72%) were less abundant and 24/87 (26%) were more abundant in fetal death cases. Dysregulated proteins were involved in pregnancy-related processes such as angiogenesis and lactation. Random forest models effectively differentiated fetal death cases from controls, achieving an area under the receiver operating characteristic curve of 72% for the combination of PlGF and sFlt-1, which increased to 86% when up to 50 additional proteins were included in the models (Delong's test, p=0.004). The point estimate of sensitivity also increased from 53% to 74% (false-positive rate about 10% for both). Glycoprotein hormones alpha chain (CGA), DnaJ homolog subfamily B member 9 (DNAJB9), and DNA-directed RNA polymerase III subunit RPC10 (POLR3K), emerged as the top three candidates to improve discrimination relative to PlGF and sFlt-1. The significant proteomic changes in a subset of fetal death cases diagnosed first with preeclampsia relative to controls were highly correlated (r=0.78, p<0.001) with those we reported in cases of late preeclampsia leading to live births. In average, for each 2-fold change in protein abundance in late preeclampsia leading to live birth there was an 8.6-fold change in preeclampsia leading to fetal death. Despite this overall correlation, Transcobalamin-2 (TCN2), Glucose-6-phosphate 1-dehydrogenase (G6PD) and Hepcidin (HAMP), among others, demonstrated dysregulation only in preeclampsia leading to fetal death, suggesting both shared and distinct pathways perturbed in the two syndromes. CONCLUSION: Our findings suggest that new maternal plasma proteins improve discrimination of fetal death from controls relative to known biomarkers, and that, although the signatures of fetal death and of preeclampsia are correlated, fetal death represents not only a much heightened disease state but also involves distinct perturbed pathways. Future studies will be needed to determine if the biomarkers predict fetal death.

APA Citation

Romero, Roberto; Bhatti, Gaurav; Chaiworapongsa, Tinnakorn; Gomez-Lopez, Nardhy; Meyyazhagan, Arun; Chaemsaithong, Piya; Jung, Eunjung; Awonuga, Awoniyi O.; Kim, Yeon Mee; Gudicha, Dereje W.; Jai Kim, Chong; Bryant, David R.; Hassan, Sonia S.; and Tarca, Adi L., "New biomarkers for the detection of fetal death derived from large-scale proteomic analysis of maternal plasma" (2026). GW Authored Works. Paper 9126.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/9126

Department

Obstetrics and Gynecology