Fibrinogen-Like Protein 2-Associated Transcriptional and Histopathological Features of Immunological Preeclampsia
Bibliographic record
Abstract
Preeclampsia is a multifactorial hypertensive disorder of pregnancy, with variable presentation in both maternal and fetal factors, such that no treatment or marker is currently universal to all cases. Here, we demonstrate that the prothrombinase and immunomodulatory secreted factor FGL-2 (fibrinogen-like protein 2) is differentially expressed across previously characterized gene expression clusters containing clinically relevant disease subtypes. FGL2 is low in a cluster consistent with the traditional paradigm of the pathology of preeclampsia (canonical preeclampsia) and high in a cluster exhibiting evidence of immune activation (immunological preeclampsia). We show that it is part of an immunoregulatory gene module integral to the transcriptional profile and placental pathology specific to immunological preeclampsia. We determine that FGL2 associates positively with chronic inflammation lesions of the placenta while associating negatively with maternal vascular malperfusion lesions. The transcriptional profiles of maternal vascular malperfusion lesions show downregulation of FGL2 and upregulation of previously investigated preeclampsia biomarkers, such as FLT1 (Fms Related Receptor Tyrosine Kinase 1) and ENG (endoglin). Conversely, the profiles of chronic inflammation lesions show an interesting downregulation of these genes, but an upregulation of FGL2 and of FGL2 -correlated immunoregulatory genes, suggesting it is upregulated downstream of major inflammatory mediators such as TNF (tumor necrosis factor)-α and IFN (interferon)-γ, hallmarks of the immunological preeclampsia subtype. This work, overall, demonstrates that FGL-2 expression levels in the term placenta reflect the unique pathophysiology that leads to immunological preeclampsia, leading to its potential as a subtype-specific biomarker.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".