Recurrent pregnancy loss is associated with a pro-senescent decidual response during the peri-implantation window

Abstract

During the implantation window, the endometrium becomes poised to transition to a pregnant state, a process driven by differentiation of stromal cells into decidual cells (DC). Perturbations in this process, termed decidualization, leads to breakdown of the feto-maternal interface and miscarriage, but the underlying mechanisms are poorly understood. Here, we reconstructed the decidual pathway at single-cell level in vitro and demonstrate that stromal cells first mount an acute stress response before emerging as DC or senescent DC (snDC). In the absence of immune cell-mediated clearance of snDC, secondary senescence transforms DC into progesterone-resistant cells that abundantly express extracellular matrix remodelling factors. Additional single-cell analysis of midluteal endometrium identified DIO2 and SCARA5 as marker genes of a diverging decidual response in vivo. Finally, we report a conspicuous link between a pro-senescent decidual response in peri-implantation endometrium and recurrent pregnancy loss, suggesting that pre-pregnancy screening and intervention may reduce the burden of miscarriage.

Conflict of interest statement

The authors declare no competing non-financial interests but the following competing financial interests: Patent application, The University of Warwick, Professor Jan Brosens, application no. 1911947.8, pending, identification of SCARA5 and DIO2 as marker genes of decidual cells and senescent decidual cells, respectively. The remaining authors declare no competing financial interests.

Figures

Fig. 1. Single-cell reconstruction of the decidual pathway in culture.

a Schematic representation of in vitro time-course experiment. bt-SNE projection of 4580 EnSC, colour-coded according to days of decidualization (D0-8) and upon withdrawal (WD) of the differentiation signal for 48 h. D0 represents undifferentiated EnSC. c The same t-SNE plot now colour-coded according to transcriptional state (S1–7). d Violin plots showing log-transformed, normalized expression levels for indicated genes in decidual cells (DC, state S5) and senescent decidual cells (snDC, state S6). e Relative proportion of total cells assigned to states S5 (DC), S6 (snDC) and S7 at each experimental timepoint. f Decidualizing EnSC were placed in pseudotime to reconstruct the trajectory of differentiation, revealing a continuous trajectory towards senescence with a single branch point marking the divergence of DC. g Heatmap showing gene dynamics during cell state transition at the branch point shown in panel (f). Columns are points in pseudotime while rows represent the 50 most dynamic genes at the branch point. The beginning of pseudotime is in the middle of the heatmap and the trajectory towards DC and snDC are indicated by the arrows. Hierarchical clustering visualizes modules of genes with similar lineage-dependent expression patterns.

Fig. 2. K-means cluster analysis identifies co-regulated decidual gene networks.

Analysis of 1748 DEG across the decidual pathway (D0–D8) yielded seven networks of uniquely co-regulated genes. Networks are annotated for selected transcription factor genes with core roles in decidualization.

Fig. 3. Coordinated expression of decidual immune surveillance genes.

a Decidual gene network B2 annotated to highlight genes implicated in uNK-cell activation and immune surveillance of senescence cells. b Primary EnSC cultures were decidualized with 8-bromo-cAMP and MPA (C+M) for the indicated days. ELISAs were performed on spent medium collected at 48 h intervals to examine secreted levels of CXCL14, IL-15 and TIMP-3. Grey dotted lines indicate secreted levels in individual cultures (n = 4). Black solid lines indicate the median level of secretion. c Four independent primary EnSC cultures were decidualized with 8-bromo-cAMP and MPA (C+M) for the indicated days. ELISAs were performed on spent medium collected at 48 h intervals to examine secreted levels of clusterin (CLU) and sST2. Cultures established from the same biopsy are colour matched between plots (dotted lines). Black solid lines indicate the median level of secretion. d Schematic representation of uNK-cell co-culture experiments. A total of 5000 primary uNK cells were co-cultured for 48 h from the indicated timepoint with 50,000 decidualized cells seeded in 96-well plates. Four independent EnSC cultures were used. e SAβG activity in undifferentiated and decidualized (C+M) cells co-cultured with or without uNK cells. Four independent EnSC cultures were used. f Secretion of CLU in decidualized (C+M) cells co-cultured with uNK cells relative to decidualized cells cultured without uNK cells. g Secreted sST2 levels in the same culture. Four independent EnSC cultures were used; lines connect paired samples.

Fig. 4. Identification of endometrial cell types and subsets during the implantation window.

at-SNE plot of 2847 cells isolated from six LH-timed biopsies, coloured to indicate reported cycle day (LH + 8 or LH + 10), captures all major endometrial cell types, including epithelial cells (EpC), immune cells (IC), endothelial cells (EC), stromal cells (EnSC) and a discrete but transcriptionally distinct proliferative (PC) stromal subpopulation. EpC segregated in four subpopulations (EpC1-4). * indicates EpC3 contributed predominantly by a single sample. b additional dimensionality reduction separated immune cells into three uNK-cell subsets (NK1-3), naive B-cells (IC1), monocytes (IC2) and macrophage/dendritic cells (IC3). c Heatmap showing relative expression (z-score) of markers defining cell types and EpC subpopulations. MYO6, RASD1 and ALCAM are included as pan-epithelial genes. d Heatmap showing relative expression of markers defining endometrial IC populations during the implantation window, including three uNK-cell subsets.

Fig. 5. SCARA5 and DIO2 as marker genes for divergent decidual states.

aSCARA5 and DIO2 belong to two distinct decidual gene networks with peak expression in DC and snDC, respectively. b, c Spatial and temporal expression of SCARA5 and DIO2 in cycling human endometrium: b violin plots showing expression of SCARA5 and DIO2 in vivo in EnSC, EC (endothelial cells), EpC (epithelial cells) and IC (immune cells) (Wilcoxon rank sum test with Bonferroni correction); c expression of SCARA5 and DIO2 in proliferative and early-, mid-, late-luteal phase endometrium. Each bar represents an individual biopsy. The data were retrieved from microarray data deposited in the Gene Expression Omnibus (GEO Profiles, GDS2052). dSCARA5 and DIO2 transcript levels quantified by RT-qPCR analysis in 250 endometrial biopsies obtained between LH + 6 and LH + 11. Centile calculations were performed on dCt values using R software and graphs were generated based on the distribution of expression on each day. The median number of samples for each day was 43 (range: 30–46). e Multiplexed single-molecule in situ hybridization (smISH) on three endometrial biopsies (LH + 10) deemed SCARA5HIGH/DIO2LOW (95th and 20th percentile, respectively), SCARA5AVERAGE/DIO2AVERAGE (60th and 52th percentile, respectively), and SCARA5LOW/DIO2HIGH (4th and 91st percentile, respectively). Insert in the left panel shows hybridization with a negative control probe. Insert in middle panel shows SCARA5+ cells (blue, closed arrows) and DIO2+ cells (pink, open arrows) in close proximity. Scale bar: 100 µM. Original magnification: ×40.

Fig. 6. Impaired fate divergence of decidual cells in RPL.

a Distribution of uNK cells and SCARA5 and DIO2 percentiles in timed endometrial biopsies of control subjects (n = 90) and RPL patients (n = 89) (Welch two-sided t-test). b Number of RPL and control subjects across four bins defined by the sum of SCARA5 and uNK-cell percentiles. c Diagram illustrating the decidual pathway. Fate divergence of EnSC upon decidualization relates to the level of replicative stress (indicating by nuclear shading) incurred by individual cells during the proliferative phase. Stress-resistant decidual cells recruit and activate uNK cells to eliminate stressed/senescent decidual cells through granule exocytosis. Different defects along the decidual pathway can be identified, including ‘decidualization failure’, ‘excessive decidual senescence’ and ‘uNK cell deficiency’. The frequency of each defect in RPL and control subjects is shown (χ2 test).