Predictive Precision of First-Trimester Cell-Free RNA Expression Profiles for Spontaneous Preterm Birth Risk Stratification

International Journal of Obstetrics and Gynecology | Vol. 14, No. 9, September 2026 | pp. 939–950

DOI: 10.46882/2026/IJOG/000559

Original Research Article

Title: Predictive Precision of First-Trimester Cell-Free RNA Expression Profiles for Spontaneous Preterm Birth Risk Stratification

Names of Authors: Sarah L. Jenkins¹, Hiroshi Tanaka²

Authors’ Affiliations:
¹ Institute of Reproductive and Developmental Biology, Imperial College London, London, United Kingdom
² Department of Obstetrics and Gynecology, University of Tokyo Hospital, Tokyo, Japan

Abstract:
Early identification of asymptomatic women predisposed to spontaneous preterm birth (sPTB) remains an unmet challenge in maternal-fetal surveillance. This prospective observational cohort study investigated the predictive accuracy of utilizing first-trimester maternal plasma cell-free RNA (cfRNA) transcriptomic profiles to forecast spontaneous delivery prior to 34 weeks of gestation. Blood samples were collected from 650 nulliparous singleton pregnancies between 11 and 13⁺⁶ weeks. High-throughput total cell-free RNA sequencing mapped circulating fetal and placental transcript boundaries. All participants were followed longitudinally until delivery, where 58 cases (8.9%) were complicated by spontaneous preterm birth before 34 weeks. Differential expression analysis revealed a distinct, early transcriptomic signature in women who subsequently delivered preterm. A panel of four specific placenta-associated transcripts (PSG9, CRH, CGB3, and PLAC4) demonstrated significant upregulation at early gestation (p < 0.001). A machine learning classification model utilizing this 4-gene cfRNA profile achieved an exceptional predictive performance, yielding a sensitivity of 86.2%, a specificity of 91.2%, and an Area Under the Curve (AUC) of 0.93. This liquid biopsy molecular index significantly outperformed standard screening models based on maternal risk history and transvaginal cervical length (p < 0.001). Tracking first-trimester maternal plasma cell-free RNA signatures provides a non-invasive screening platform capable of tracking subclinical placental senescence markers to predict spontaneous preterm birth.

Keywords: Spontaneous Preterm Birth; Cell-Free RNA; Transcriptomics; Liquid Biopsy; Placental Senescence; Early Screening.

Manuscript Timeline: Received: June 18, 2026; Revised: August 12, 2026; Accepted: September 04, 2026; Published: September 07, 2026.

Citation: Jenkins SL, Tanaka H. Predictive Precision of First-Trimester Cell-Free RNA Expression Profiles for Spontaneous Preterm Birth Risk Stratification. International Journal of Obstetrics and Gynecology. 2026; 14(9): 939–950.

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