Genetic and Epigenetic Dysregulation of CR1 is Associated with Catastrophic Antiphospholipid Syndrome (CAPS)
Bibliographic record
Abstract
Abstract Objective Catastrophic antiphospholipid syndrome (CAPS), characterized by widespread thrombosis and multi-organ failure, is associated with high morbidity and mortality. We previously established complement activation as a pathogenic driver of CAPS and identified rare germline variants in complement-regulatory genes including Complement Receptor 1 ( CR1 ) in 50% of CAPS. Methods We quantified CR1 expression by flow cytometry across hematopoietic cell types. CRISPR/Cas9 genome editing of TF-1 (erythroleukemia) cells was performed to generate CR1 “knock-out” and “knock-in” lines with patient-specific CR1 variants. Multiomics analysis was performed to investigate the role of methylation in CR1 expression in patients with reduced CR1 expression. Functional impact of low CR1 expression was assessed by complement-mediated cell killing using modified Ham (mHam) assay, cell-bound complement degradation products through flow cytometry and circulatory immune complexes (CIC) in serum samples through ELISA. Results CR1 expression in erythrocytes was markedly reduced on CAPS erythrocytes (n=9, 21.80%) compared to healthy controls (HC; n=32, 82.40%), with promoter hypermethylation emerging as a plausible epigenetic mechanism for CR1 downregulation. A novel germline variant ( CR1- V2125L; rs202148801 ) mitigated CR1 expression and increased complement-mediated cell death of knock-in cell lines. Erythrocytes from the patient with the CR1- V2125L variant had low CR1 expression. Levels of CIC, which are bound and cleared by CR1 on erythrocytes, were higher in acute CAPS (n=3, 25.55 µg Eq/ml) than healthy controls (n=3, 7.445 µg Eq/ml). Five patients were treated with C5 inhibition which mitigated thrombosis. Conclusion Genetic or epigenetic-mediated CR1 deficiency is a potential hallmark of CAPS and predicts response to C5 inhibition.
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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 | 0.000 |
| 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".