ArticleBMC pregnancy and childbirth2026
Improving the accuracy of fetal growth restriction diagnosis by integrating fetal genetic growth potential: a proof of concept study.
Article in BMC pregnancy and childbirth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundFetal growth restriction (FGR) is a common obstetric complication where a fetus fails to reach its genetically determined growth potential. Current diagnostic methods rely on population-based fetal biometric percentiles, which struggle to distinguish pathological FGR from healthy small-for-gestational-age (SGA) infants and may miss cases of growth restriction in fetuses with a high genetic growth potential who fall above conventional SGA thresholds. This study aimed to develop a novel diagnostic framework for FGR by incorporating individualized genetic potential modeling to improve precision in identification and risk stratification.
methodsUsing data from the Shanghai Birth Cohort (1,806 mother-infant pairs), fetal growth potential was calculated using a polygenic risk score for birth weight derived from fetal genome-wide association studies. A new metric, “FGR_degree,” was developed as the difference between standardized genetic growth potential and actual birth weight Z-score. Fetuses were stratified into risk categories using a dual-threshold approach: the top 10% of FGR_degree values combined with SGA criteria (birth weight < 10th percentile). The high-risk “trueFGR” group included fetuses meeting both criteria. Maternal characteristics, pregnancy complications, neonatal outcomes, and neurodevelopmental outcomes at six months were analyzed using regression models.
resultsAmong 1,806 mother-child pairs, 181 newborns were classified into the top 10% FGR_degree group, including 46 trueFGR cases. Compared to SGA infants, trueFGR infants exhibited consistent growth impairments: lower birth weight (2,599.7 g vs. 2,720.9 g, P = 0.02), reduced GROW centiles (4.8% vs. 5.7%, P < 0.001), and disproportionate body proportionality. NICU admission rates were higher in trueFGR (17.4% vs. 12.5%, P = 0.59). Neurodevelopmental outcomes showed a dose-response relationship between FGR_degree and 6-month deficits, with trueFGR conferring the highest adjusted risk for gross motor delay (OR 5.04, 95% CI [2.17, 11.69] vs. 3.51, 95% CI [1.85, 6.67] in SGA). Sensitivity analyses confirmed enhanced risk prediction by combining Top10_FGR_degree with SGA.
conclusionsIntegrating fetal genomic data with birth weight enabled the development of a novel FGR severity metric. Combining FGR_degree with SGA classifications improved risk stratification, identifying high-risk fetuses more precisely. TrueFGR was associated with maternal complications, adverse outcomes, and neurodevelopmental delays at six months. Future research should explore non-invasive fetal DNA profiling and multi-ethnic validation.
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