Characterizing immune variation and diagnostic indicators of preeclampsia by single-cell RNA sequencing and machine learning

Basic information
Cell
28,774
Sample
23

Technology
DNelabC4
Omics
scRNA-seq
Source
PBMCs

Dataset ID
38182876
Platform
BGISEQ-500
Species
Human
Disease
PE,Healthy/pregnant
Age range
24 - 34
Update date
2024-01-05
Summary

Preeclampsia is a multifactorial and heterogeneous complication of pregnancy. Here, we utilize single-cell RNA sequencing to dissect the involvement of circulating immune cells in preeclampsia. Our findings reveal downregulation of immune response in lymphocyte subsets in preeclampsia, such as reduction in natural killer cells and cytotoxic genes expression, and expansion of regulatory T cells. But the activation of naïve T cell and monocyte subsets, as well as increased MHC-II-mediated pathway in antigen-presenting cells were still observed in preeclampsia. Notably, we identified key monocyte subsets in preeclampsia, with significantly increased expression of angiogenesis pathways and pro-inflammatory S100 family genes in VCAN+ monocytes and IFN+ non-classical monocytes. Furthermore, four cell-type-specific machine-learning models have been developed to identify potential diagnostic indicators of preeclampsia. Collectively, our study demonstrates transcriptomic alternations of circulating immune cells and identifies immune components that could be involved in pathophysiology of preeclampsia.

Overall design

Single-Cell RNA sequencing data of 28774 circulating immune cells from 8 pregnant women diagnosed with preeclampsia (PE group, included one early-onset PE and seven late-onset PE) and 15 normal pregnant women (NP group)

Contributors

To be supplemented.

Contact

To be supplemented.

snRNA-Seq
Sample nameSample titleDiseaseGenderAgeSourceTreatmentTechnologyPlatformOmicsSample IDDataset IDAction
No data available