Targeted Gene Sequencing Identifies Variants in the Protein C and Endothelial Protein C Receptor Genes in Patients With Unprovoked Venous Thromboembolism
Bibliographic record
Abstract
OBJECTIVE: The interaction of protein C (PC) with the endothelial PC receptor (EPCR) enhances activated PC generation. We performed targeted gene sequencing of the PC gene (PROC) and EPCR genes (PROCR) in patients with unprovoked venous thromboembolism (VTE) to determine whether mutations that impair PC-EPCR interactions are associated with an increased risk of VTE. APPROACH AND RESULTS: We sequenced exon 3 of PROC and exons 2 and 3 of PROCR (the exons that encode the protein-protein binding domains of PC and EPCR) in 653 patients with unprovoked VTE and in 627 healthy controls. Five single nucleotide variants, each in individual patients, were identified that result in abnormal PC (Arg9Cys, Val34Met, and Arg-1Cys) or abnormal EPCR proteins (Arg96Cys and Val170Leu). We did not detect any nonsynonymous coding variants in the controls. When the PC variants were expressed in human embryonic kidney 293 cells, all exhibited decreased synthesis, and 2 of the variants had reduced capacity for activated PC generation. When expressed on the surface of human embryonic kidney 293 cells, the EPCR variants showed reduced affinity for fluorescently labeled PC. In addition, the previously reported EPCR A3 haplotype, which promotes cellular shedding of EPCR, is over-represented in the patient group (P=0.001). CONCLUSIONS: This is the first targeted DNA sequencing analysis of PROC and PROCR in a large group of patients with unprovoked VTE. Our data suggest that mutations that impair PC-EPCR interactions may be associated with an increased risk of VTE.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".