Cell type markers indicate distinct contributions of decidual stromal cells and natural killer cells in preeclampsia

Preeclampsia is commonly classified as early-onset preeclampsia (EOP) (before week 34) and late-onset preeclampsia (LOP). EOP is characterized by defective placentation and spiral remodeling, whereas in LOP, normal placentation has apparently taken place, but placental capacity is exceeded and/or other factors contribute to the symptoms. Recent studies suggest that maternal cell types, such as endometrial stromal cells, have a more critical role in the etiology of preeclampsia than previously anticipated (Conrad et al. 2017, Garrido-Gomez et al. 2017). However, the current models of preeclampsia only loosely explain their relative contributions and the cell type-specific molecular mechanisms.

Here, we conduct an analysis that combines decidual bulk transcriptomic data from preeclampsia with recently published single-cell sequencing (scRNA-seq) data from healthy women. Specifically, we utilized the previously detected differentially expressed genes for severe EOP and severe LOP from decidua samples from term pregnancies (Tong et al. 2018), and from secretory phase of the menstrual cycle of women that previously experienced severe preeclampsia (Garrido-Gomez et al. 2021). These were intersected with the cell type marker lists from scRNA-seq transcriptomic atlases from endometrium taken during the secretory phase of menstrual cycle (Wang et al. 2020), decidua from women undergoing selective pregnancy termination during the first trimester (Vento-Tormo et al. 2018), and decidua from women at term pregnancy (Pique-Regi et al. 2019). With this integrative analysis, we were able to predict distinct cell type-specific contributions to the pathogenesis of both EOP and LOP.

We first re-ran the cluster analysis for the three scRNA-seq datasets using Seurat 4.0 (Hao et al. 2021), re-annotated the main uterine cell types concordantly (Fig. 1A, B and C), identified cell type-specific marker genes and combined these from the three studies to an extended cell type marker list. To search for the presence of cell type-specific markers among the preeclampsia-regulated genes, we intersected scRNA-seq marker lists and disease genesets and conducted Fisher’s exact tests (Fig. 1D). We discovered two robust overrepresentation signals: LOP downregulated genes were enriched with endometrial/decidual stromal cell (dS) markers (combined uterine markers P = 1.5 × 10⁻³², 5.1-fold) and EOP upregulated genes were enriched with uterine natural killer cell (uNK) markers (P = 1.3 × 10⁻²², 8.6-fold) (Fig. 1D). This suggests that LOP and EOP have distinct cell type-specific etiological characteristics. While LOP is associated with transcriptomic changes in stromal cells, EOP is more closely associated with transcriptomic changes in uNKs. As decidualization takes place spontaneously during the non-pregnant menstrual cycle, these results also suggest that the defects in uterine differentiation that contribute to preeclampsia may be detectable already in the non-pregnant menstrual cycle. However, in the analyzed dataset of genes differentially expressed in the secretory phase of the menstrual cycle from women that previously had preeclampsia (Garrido-Gomez et al. 2021), the most significant signature was observed for perivascular cells with less striking enrichment (P = 2.0 × 10⁻¹⁰, 3.7-fold) compared to those we observed with EOP and LOP (Tong et al. 2018).

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Preeclampsia regulated genes are enriched with decidual stromal cell and uterine natural killer cell marker genes. The uterine cell types in (A) secretory phase menstrual cycle (Wang et al. 2020), (B) first trimester pregnancy (Vento-Tormo et al. 2018) and (C) term not in labor pregnancy (Pique-Regi et al. 2019) single-cell transcriptomes with harmonized annotation. For (A) and (B), the preprocessed scRNA-seq UMI counts were extracted from ArrayExpress accession E-MTAB-6701 (Vento-Tormo et al. 2018), including 6 decidua samples (6–12 weeks of gestation) with a total of 36,186 cells, and GEO accession GSE111976 (Wang et al. 2020), including 10 endometrial samples (cycle days 16–26) with a total of 71,032 cells, respectively. For (C), the raw data were extracted from dbGaP accession phs001886.v1.p1 (Pique-Regi et al. 2019) with consent, only term no labor (basal plate, chorioamniotic membranes) samples were selected with a total of 13,730 cells. All three datasets were produced using 10× Genomics scRNA-seq. Samples were pre-processed using cellranger-3.1.0’s count function with default parameters and prebuilt reference genome (hg38). We used the standard analysis protocol of Seurat 4.0 (Hao et al. 2021) and the annotation of the clusters was harmonized to follow the one from the first trimester study (Vento-Tormo et al. 2018). (D) A heatmap of Fisher’s exact test P values for the overlaps of uterine cell type marker genes and preeclampsia differentially expressed genes. The arrows mark the subsets that are up- or downregulated genes in the original studies. The marker gene lists used for each main cell type were combined lists from the condition-specific cell type markers from A, B and C. Early-onset (before week 34) severe preeclampsia (EOP) (n  = 3), late-onset severe preeclampsia (LOP) (n  = 3) and control (n  = 3) samples were from term deciduas delivered by cesarean section (Tong et al. 2018). Samples for women with previous severe preeclampsia (M-PP) (n  = 17) together with controls (n  = 12) were from late secretory menstrual cycle (days 22–32) endometrium (Garrido-Gomez et al. 2021). Statistical significance of the enrichment was determined using Fisher’s exact test in R, with all Refseq protein-coding genes (n  = 20,203) as the background. (E) A heatmap of Fisher’s exact test P values for the overlaps of the preeclampsia differentially expressed genes and the subpopulations of endometrial/decidual stromal cells (dS1, dS2 and dS3) from the first trimester study. (F) Genes in the LOP downregulated – stromal dS3 marker intersection (first trimester). (G) Trajectory inference of differentiating dS cells using Slingshot (Street et al. 2018). Slingshot uses minimum spanning tree algorithm to reconstruct the lineage structure among differentiating cells from scRNA-seq data. In the 2D visualization, the axes represent the first principal components. The black dots represent the cells in the lower dimension, and the arrow-headed lines depict the suggested differentiation trajectories estimated by Slingshot. (H) Decorin (DCN) and (I) galectin 1 (LGALS1) expression across the dS cell trajectories. (J) Genes in the EOP upregulated – uNK cell type marker intersection. (K) Trajectory inference of uNK cell subpopulations from the first trimester study using Slingshot. (L) CD7 expression across the uNK trajectories. For (E-L) only the first trimester data was used. For (F) and (J), the top functional enrichment categories (GO, Hallmark) are displayed on the left. Functional enrichment analysis was done using the Metascape tool with all available pathway databases (GO biological processes, Reactome Gene Sets, Canonical Pathways, Biocarta Gene Sets, WikiPathways, KEGG Pathways and Hallmark Gene Sets). Trajectory inference was done using the infer_trajectory function of Slingshot in the ‘dyno’ version ‘0.1.2’ (Saelens et al. 2019).

Citation: Reproduction 164, 5; 10.1530/REP-22-0079

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We next focused on the cell subpopulations among stromal cells in the first trimester data (Vento-Tormo et al. 2018). The three annotated subpopulations (dS1, dS2 and dS3) of stromal cells reflect the stages of the decidualization (differentiation), and dS3 represents decidualized cells with high prolactin expression (Vento-Tormo et al. 2018). We repeated the Fisher’s exact tests separately for dS1, dS2 and dS3 (Fig. 1E) and observed enrichment of dS3 markers among the LOP downregulated genes (P = 3.7 × 10⁻³⁸, 16-fold). This suggests that in LOP the normal decidualization of maternal stromal cells is defected, further supporting the recent observation by others on severe preeclampsia (Rabaglino et al. 2015, Garrido-Gomez et al. 2017, 2021). These dS3 – LOP downregulated genes had progressively higher expression during decidualization in healthy donors (Fig. 1F), and they were functionally enriched with terms such as ‘epithelial–mesenchymal transition’ (EMT) (Hallmark, P = 6.1 × 10⁻⁸) and ‘wounding’ (GO, P = 5.9 × 10⁻⁵). To visualize the decidualization trajectory and the expression of selected genes associated with these terms in healthy donors, we used Slingshot (Street et al. 2018) (Fig. 1G, H and I). For instance, the expression levels of decorin (DCN) and galectin 1 (LGALS1) are markedly increased during the decidualization and have the highest expression in dS3 (Fig. 1H and I). DCN is a decidualization marker and LGALS1 enhances maternal immunotolerance during pregnancy. On the other hand, LOP upregulated genes were overrepresented with dS1 marker genes (P = 1.8 × 10⁻¹¹, 9.9-fold) (Fig. 1E), including fibroblast marker, actin alpha 2 (ACTA2), for the non-decidualized stage, being again in line with the prediction that decidualization defects contribute to LOP. We also observed that the EOP downregulated genes were similarly enriched with dS3 markers (P = 1.3 × 10⁻¹¹, 7.6-fold), suggesting that gene regulatory changes associated with decidualization defects of stromal cells also contribute to EOP, but not to the same extent as in LOP.

For uNK subpopulations (dNK1, dNK2 and dNK3) (Vento-Tormo et al. 2018), we did not detect robust subpopulation-specific overrepresentation among EOP or LOP regulated genes. We hypothesized that this is because the subpopulation clusters are only moderately separated from each other. Thus, we conducted a functional enrichment analysis of all the uNK cell type marker genes that were upregulated in EOP (Fig. 1D) and found terms such as ‘Allograft rejection’ (Hallmark, P = 4.9 × 10⁻⁸) and ‘Leukocyte activation’ (GO, P = 5.1 × 10⁻⁸) (Fig. 1J), which are generally associated with reduced maternal immunotolerance. Although in healthy donors these uNK marker genes did not present as clear differentiation trajectory associated expression patterns as observed in stromal cells, we observed a modest trend of genes in ‘Allograft rejection’ to be more expressed in the dNK2 and dNK3 populations compared to uNK1 (Fig. 1J), including, e.g. CD7 (Fig. 1K and L). This suggests that uNK markers upregulated in the more differentiated subpopulations (dNK2 and dNK3) may associate with reduced immunotolerance and preeclampsia.

Finally, for the top overrepresentation gene intersect for women with previous preeclampsia (Garrido-Gomez et al. 2021), the perivascular cells – preeclampsia downregulated signature, we also conducted a functional enrichment analysis. The detected top terms were ‘EMT’ (Hallmark, P = 4.4 × 10⁻⁹) and ‘blood vessel development’ (GO, P = 7.8 × 10⁻⁹). Notably, EMT term was also detected for the stromal dS3 – LOP downregulated intersect, and the perivascular cell clusters have been associated with endometrial stromal stem cells (Queckbörner et al. 2021) that have previously been reported to underlie reproductive disorders.

The main limitations of this study involve the temporal specificity in the dataset intersections. First, EOP and LOP data (Tong et al. 2018) were collected upon delivery and the transcriptomic signatures upon delivery may be different from the initial signatures for EOP and LOP earlier during the pregnancy (Rabaglino & Conrad 2019). Second, we selected to combine the scRNA-seq cell type-specific markers from the three different time points in order to have more comprehensive cell type marker lists, but this inevitably decreased the temporal specificity of these lists for a given one time point.

In conclusion, our analysis with single-cell data-derived marker genes extends the resolution of previous heterogenous EOP vs LOP comparisons. We observed that preeclampsia downregulated genes (especially in LOP) are enriched with the markers of decidualized stromal cells (dS3) indicating a critical role for decidualization defects in the etiology of preeclampsia. Our results support previous observations on the importance of decidualization defects (Rabaglino et al. 2015, Garrido-Gomez et al. 2017, 2021). Notably, these studies collected severe preeclampsia samples without classification to EOP and LOP, whereas our analysis presents a novel observation that the overrepresentation signal for stromal cell decidualization defects is stronger in LOP rather than EOP. Curiously, decidual stromal cells have been suggested to have independently evolved two of their main functions; first, the anti-inflammatory reaction associated with implantation in the stem of placental mammals, and secondly, the ability to support extended maintenance of pregnancy in Euarchontoglires (supraprimates) including humans (Chavan et al. 2016). The robust LOP-specific signal may be associated with the function of decidual stromal cells to support the maintenance of pregnancy rather than the initial anti-inflammatory role in implantation and early placentation. These results, therefore, emphasize the abovementioned dual role of stromal cells in reproductive health. On the other hand, uNK markers linked with reduced immunotolerance were specifically enriched in the EOP upregulated genes which is in line with the critical role of uNK cells to promote immunotolerance during spiral artery modeling and placentation. Overall, our analysis highlights the potential of and motivates future single-cell studies on preeclampsia.