M2 Macrophages are Major Mediators of Germline Risk of Endometriosis and Explain Pleiotropy With Comorbid Traits
Bibliographic record
Abstract
Endometriosis is a common gynecologic condition that causes chronic, life-altering symptoms including pain and infertility. There is an urgent need for new non-hormonal targeted therapeutics to treat endometriosis, but until very recently, the cellular and molecular signatures of endometriotic lesions are undefined, hindering the development of clinical advances. Integrating inherited risk data from analyses of >45 0000 individuals with ≈35 0000 single-cell transcriptomes from 21 patients, M2-macrophages as candidate drivers of disease susceptibility are uncovered, and nominating IL1 signaling as a central hub impacted by germline genetic variation associated with endometriosis risk. Extensive functional follow-up confirmed these associations and revealed a pleiotropic role for this pathway in endometriosis. Population-scale expression quantitative trait locus analysis demonstrates that genetic variation controlling IL1A expression is associated with endometriosis risk variants. Manipulation of IL1 signaling in state-of-the-art in vitro decidualized endometrial organoids impacts epithelial differentiation, and in an in vivo endometriosis model, treatment with anakinra (an interleukin-1 receptor antagonist) results in a significant, dose-dependent reduction in spontaneous and evoked pain and dampened pro-angiogenic signaling. Together, these studies highlight non-diagnostic cell types as central to endometriosis susceptibility and support IL1 signaling as an important actionable pathway for this disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".