蜕膜
细胞滋养层
转录组
生物
间质细胞
表观基因组
计算生物学
计算机科学
生物信息学
细胞生物学
胎盘
胎儿
胎盘形成
细胞迁移
医学
罗亚
人工智能
绒毛间隙
发育不良
染色质
作者
Cheng Wang,Yan Zhou,Yuejun Wang,Tuhin K. Guha,Zhida Luo,Anxhela Mustafaraj,Tara I. McIntyre,Marisa E. Schwab,Brittany Davidson,Gabriella C. Reeder,Ronald J. Wong,Sarah K. England,Juan M. Gonzalez,Robert Blelloch,Alexis J. Combes,L.C. Giudice,Adrian Erlebacher,Tippi C. MacKenzie,David K. Stevenson,Gary M. Shaw
出处
期刊:Nature
[Nature Portfolio]
日期:2026-04-08
卷期号:653 (8113): 167-179
被引量:4
标识
DOI:10.1038/s41586-026-10316-x
摘要
Abstract The human maternal–fetal interface is characterized by mosaic intermingling of maternal and fetal cells 1 . Yet the underlying cellular, molecular and spatial programmes remain incompletely defined. Here we generate a comprehensive atlas of the human maternal–fetal interface across normal pregnancies from early gestation to term by integrating large-scale paired single-nucleus transcriptomic and chromatin accessibility profiling with submicrometre-resolution spatial transcriptomics and CODEX multiplex protein imaging 2 , substantially boosting the spatiotemporal resolution of prior research 3 . This framework delineates common and transient cell types, states and spatial niches across the fetal and maternal compartments, reconstructs transcriptional programmes that guide cytotrophoblast and decidual stromal cell differentiation, and resolves recurrent architecture structural units that build this interface. We identify previously unrecognized arterial endothelial state transitions during cytotrophoblast-mediated spiral artery remodelling and develop a machine learning model that predicts cytotrophoblast invasiveness from transcriptomic signatures. We further discover a decidual stromal cell subtype that suppresses cytotrophoblast invasion via endocannabinoid signalling at the human maternal–fetal interface. By integrating the atlas with genome-wide association data, we pinpoint maternal and fetal cells that are most vulnerable to pre-eclampsia, preterm birth or miscarriage. This resource provides a comprehensive spatially resolved single-cell multiomic reference of the human placenta and decidua and offers a framework for decoding their normal and disordered development.
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