Open medicine
A multi-dataset associative analysis of single-cell and bulk transcriptomic profiles in preeclampsia
Par Liu B, Cui X, Wang X et 2 autres.
Contenu en anglais
Résumé
Objectives
Preeclampsia is a multifactorial disease involving diverse pathological mechanisms and signaling pathways. However, the specific mechanism of PE is not yet completely elucidated.
Methods
The scRNA-seq dataset GSE173193 and the bulk transcriptomic dataset GSE74341 were obtained from the Gene Expression Omnibus and analyzed separately as complementary datasets. The single-cell dataset was used to explore cellular heterogeneity, inferred intercellular communication, pathway activity, candidate regulons, and transcriptional-state trajectories. The bulk dataset was analyzed using CIBERSORT, GSEA, and GSVA to estimate immune-cell fractions and assess their associations with candidate regulators. Cross-dataset findings were interpreted as complementary association-level evidence rather than direct validation.