Circulating Immune Cells from Early- and Late-onset Pre-eclampsia Displays Distinct Profiles with Differential Impact on Endothelial Activation
Bibliographic record
Abstract
Pre-eclampsia (PE) affects 5-8% of pregnancies and has detrimental effects on maternal-fetal health. PE is characterized by de novo hypertension after 20 wk of gestation and end-organ damage. Systemic inflammatory imbalance has been associated with PE, but its contribution to the pathology is poorly understood. Our objective was to investigate maternal systemic immune changes in early-onset PE (EOPE) and late-onset PE (LOPE) versus uncomplicated pregnancies (control [CTRL]), and their contribution to endothelial activation, hallmark of hypertension. Blood samples were analyzed by flow cytometry, multiplex assay, intracellular cytokine staining, and single-cell RNA sequencing. We performed cocultures between circulating immune cells and HUVECs to assess endothelial activation. We found that EOPE had decreased regulatory T cells (4.64±0.33, p < 0.05) and monocytes (33.92±3.08, p < 0.01), whereas LOPE had decreased regulatory T cells (4.60±0.30, p < 0.05) and Th2 cells (7.50±0.62, p < 0.01) versus CTRL. Compared to CTRL, elevated cytokines/chemokines, and growth factors were observed in LOPE, whereas EOPE primarily showed decreased levels. Using intracellular cytokine staining, we observed more monocytes producing IL-12, TNF-α, and IL-1β (all p < 0.05) in LOPE versus CTRL. At the transcriptomic level, we found differentially expressed genes between EOPE and CTRL, predominantly related to upregulation of immune activation pathways. Lastly, EOPE PBMCs induced heightened endothelial activation in vitro observed by increased ICAM-1 and ET-1 (p < 0.05), whereas LOPE PBMCs required LPS stimulation. Although significant proteomic changes are observed in the LOPE group, the EOPE displayed changes mostly at the transcriptomic levels and could induce endothelial activation in vitro.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".