Single-cell RNA sequencing reveals trophoblast and immune mechanisms in preeclampsia pathogenesisNew Sequencing Methods Reveal Hidden Mechanisms of Preeclampsia

Preeclampsia (PE) is a pregnancy-specific multisystem disorder and a leading cause of maternal and perinatal morbidity and mortality worldwide. Despite the widely accepted two-stage model involving placental dysfunction and maternal systemic inflammation, the precise cellular and molecular mechanisms underlying its pathogenesis remain incompletely understood. In recent years, single-cell RNA sequencing (scRNA-seq) has emerged as a transformative technology capable of resolving transcriptional heterogeneity at unprecedented resolution, offering new insights into the complex cellular landscape of the maternal-fetal interface. This review systematically summarizes the application of scRNA-seq in advancing the understanding of PE pathogenesis. We first introduce the technical principles and advantages of scRNA-seq over bulk sequencing methods. Subsequently, we highlight key findings from scRNA-seq studies of the normal placenta and decidua, establishing a reference for cellular composition and trophoblast differentiation trajectories. We then focus on studies of PE placentas, which have revealed distinct dysfunction in trophoblast subpopulations—including impaired differentiation, invasion, and accelerated senescence—and have identified novel regulatory molecules such as BHLHE40, NDRG1, and DAB2. Additionally, we discuss scRNA-seq-derived insights into immune dysregulation at the maternal-fetal interface, including altered NK cell subsets, macrophage polarization, and disruption of immune tolerance mediated by molecules such as HLA-F and JUNB. Finally, we explore the translational potential of scRNA-seq in identifying novel biomarkers, constructing predictive models, and enabling disease subtyping for precision medicine. By capturing cell-specific transcriptional changes, scRNA-seq provides a powerful framework for deciphering the complexity of PE and holds promise for improving its prediction, diagnosis, and therapy.