A coagulation defect arising from heterozygous premature termination of tissue factor
Bibliographic record
Abstract
Tissue factor (TF) is the primary initiator of blood coagulation in vivo and the only blood coagulation factor for which a human genetic defect has not been described. As there are no routine clinical assays that capture the contribution of endogenous TF to coagulation initiation, the extent to which reduced TF activity contributes to unexplained bleeding is unknown. Using whole genome sequencing, we identified a heterozygous frameshift variant (p.Ser117HisfsTer10) in F3, the gene encoding TF, causing premature termination of TF (TFshort) in a woman with unexplained bleeding. Routine hematological laboratory evaluation of the proposita was normal. CRISPR-edited human induced pluripotent stem cells recapitulating the variant were differentiated into vascular smooth muscle and endothelial cells that demonstrated haploinsufficiency of TF. The variant F3 transcript is eliminated by nonsense-mediated decay. Neither overexpression nor addition of exogenous recombinant TFshort inhibited factor Xa or thrombin generation, excluding a dominant-negative mechanism. F3+/- mice provide an animal model of TF haploinsufficiency and exhibited prolonged bleeding times, impaired thrombus formation, and reduced survival following major injury. Heterozygous TF deficiency is present in at least 1 in 25,000 individuals and could limit coagulation initiation in undiagnosed individuals with abnormal bleeding but a normal routine laboratory evaluation.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".