Sex-specific DNA methylation marks associated with sex-biased risk of recurrence in unprovoked venous thromboembolism
Bibliographic record
Abstract
BACKGROUND: Whether to stop oral anticoagulants after a first unprovoked venous thromboembolism (VTE) is challenging, partially due to an intriguingly higher risk of VTE recurrence (rVTE) in men after therapy discontinuation. DNA methylation (DNAm) differences between men and women might underlie this sex-biased rVTE risk difference. OBJECTIVES: To investigate sex-specific associations between DNAm at cytosine-phosphate-guanine (CpG) sites and rVTE. METHODS: In 417 unprovoked VTE patients, including 101 experiencing recurrences over a 5-year follow-up (REcurrent VEnous thromboembolism Risk Stratification Evaluation [REVERSE] I), we analyzed blood DNAm using the Illumina EPIC array and performed a sex-stratified epigenome-wide association study. We further examined 181 major provoked VTE patients, including 36 recurrences over a 14-year follow-up (the MARseille THrombosis Association [MARTHA]), to investigate whether DNAm is a risk factor for rVTE after anticoagulation therapy. RESULTS: Hypomethylated CpGs at genes TBC1D22B-cg01060850 and ZHX2-cg07808424 in men and DIP2B-ch.12.1038646R and DENND3-cg03401656 in women were associated with rVTE at genome-wide level (P < 7x10-8). Though not statistically significant, DENND3-cg03401656 had the same direction of effect in MARTHA women. Sensitivity analysis confirmed the robustness of the estimates, including potential confounders, adaptations of the Cox model, non-Europeans, and proximal methylation quantitative trait loci in the association. The associated CpGs were situated at genes for membrane trafficking, corroborating the participation of Rab regulatory proteins in rVTE and transcription factors. CONCLUSION: We identified DNAm marks as potential risk factors for sex-biased recurrence in unprovoked VTE. Further replication and experimental validation could refine our understanding of the regulation of the identified DNAm sites and help optimize personalized decision-making for long-term anticoagulation after a first 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 | 0.000 | 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".