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Updated: Jun 8, 2026

Mouse In Vivo Placental Targeted CRISPR Manipulation
Published on: April 14, 2023
SLC6A8-centered placental molecular signature predicts fetal growth restriction via machine learning and single-cell
Qing Hua1, Xiaoyan You1, Xujing Yan1
1Department of Obstetrics and Gynecology, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Abstract:
Fetal growth restriction (FGR) is a common and severe complication during pregnancy, serving as a primary cause of intrauterine fetal distress and perinatal mortality. Its pathogenesis involves placental insufficiency, impaired nutrient transport, and metabolic disturbances, yet key molecular regulators remain incompletely understood. Using machine learning, we identified a 5-placental gene signature (CLDN9, GCNT4, PIM3, SLC6A8 and TPBG) for robustly predicting FGR and validated its performances in multiple datasets. Among those, SLC6A8 expression was significantly upregulated in of FGR placentas and confirmed by experiments. Further we revealed an elevated cell subpopulation of decidual stromal cells (DSCs), characterized by high expression of SLC6A8, which participated in abnormal decidualization associated with FGR. This study establishes a predictive model and identifies SLC6A8 as a potential placental regulator of FGR. Our finding provides novel insights into the cellular and molecular pathogenesis of FGR.
