Integrated metabolic and inflammatory biomarkers for early association and prediction of adverse pregnancy outcomes: a multicenter validation study

Clinical Snapshot

Key Findings

• P Value: Not reported in abstract

• Effect Size: Highest TyNIR quartile: OR 3.86 for GDM, OR 3.05 for GH, OR 3.45 for PB

• Primary Outcome: Composite adverse pregnancy outcomes (GDM, GH, PB)

• Nnt Or Sensitivity: PREMIER model AUC: 0.710±0.031 (GDM), 0.736±0.040 (GH), 0.742±0.073 (PB)

• Confidence Interval: GDM: 95% CI 2.33-6.39; GH: 95% CI 1.74-5.36; PB: 95% CI 1.24-9.66

Clinical Application

Requires early pregnancy metabolic and inflammatory biomarker testing, feasible in routine antenatal care Relevant to Australian antenatal care with potential integration into existing screening protocols. Would require validation in Australian population and consideration of PBS funding for additional biomarker testing Pregnant women in early pregnancy seeking risk stratification for adverse outcomes

Abstract

BACKGROUND: Adverse pregnancy outcomes (APOs) affect long-term maternal and offspring health. Conventional metabolic markers, including the triglyceride-glucose (TyG) index, inadequately capture pregnancy-related immuno-inflammatory dysregulation. We propose a composite index, TyNIR, integrating metabolic and inflammatory parameters, and assess its associations with APOs and predictive performance using machine learning. METHODS: Data were collected from two tertiary centers in Fujian, China (2023-2025), including 1,741 pregnancies and an external validation cohort of 300. Early-pregnancy parameters were used to derive TyNIR. Primary outcomes were gestational diabetes mellitus (GDM), gestational hypertension (GH), preterm birth (PB), low birth weight (LBW), and premature rupture of membranes (PROM). Multivariable regression, subgroup, and interaction analyses assessed associations between TyNIR and APOs. A feature selection approach developed the PREMIER model, which was compared with TyG and other models and externally validated. RESULTS: TyNIR was positively associated with GDM, GH, and PB. After adjustment, the highest quartile showed increased risks, with odds ratios (ORs) of 3.86 (95% CI 2.33-6.39) for GDM, 3.05 (1.74-5.36) for GH, and 3.45 (1.24-9.66) for PB. No associations were observed for LBW or PROM. The PREMIER model achieved area under the curve (AUC) values of 0.710 ± 0.031, 0.736 ± 0.040, and 0.742 ± 0.073, outperforming TyG and other models. External validation confirmed consistent associations and superior predictive performance. CONCLUSIONS: TyNIR consistently predicts risks of GDM, GH, and PB. The TyNIR-based PREMIER model shows robust predictive performance with external validation. These findings support early identification of high-risk pregnancies and may guide personalized management of APOs.

References

1. 1.Wu, X., Wang, B., Li, W., Gan, B., He, L., Weng, Z., & Wu, J. (2026). Integrated metabolic and inflammatory biomarkers for early association and prediction of adverse pregnancy outcomes: a multicenter validation study. The Journal of Maternal-Fetal & Neonatal Medicine, 1-12. https://doi.org/10.1080/14767058.2026.2661440