Genome-Wide Investigation of DNA Methylation Marks Associated with FV Leiden Mutation
Bibliographic record
Abstract
In order to investigate whether DNA methylation marks could contribute to the incomplete penetrance of the FV Leiden mutation, a major genetic risk factor for venous thrombosis (VT), we measured genome-wide DNA methylation levels in peripheral blood samples of 98 VT patients carrying the mutation and 251 VT patients without the mutation using the dedicated Illumina HumanMethylation450 array.The genome-wide analysis of 388,120 CpG probes identified three sites mapping to the SLC19A2 locus whose DNA methylation levels differed significantly (p,3 10 28 ) between carriers and noncarriers.The three sites replicated (p,2 10 27 ) in an independent sample of 214 individuals from five large families ascertained on VT and FV Leiden mutation among which 53 were carriers and 161 were non-carriers of the mutation.In both studies, these three CpG sites were also associated (2.33 10 211 ,p,3.02 10 24 ) with biomarkers of the Protein C pathway known to be influenced by the FV Leiden mutation.A comprehensive linkage disequilibrium (LD) analysis of the whole locus revealed that the original associations were due to LD between the FV Leiden mutation and a block of single nucleotide polymorphisms (SNP) located in SLC19A2.After adjusting for this block of SNPs, the FV Leiden mutation was no longer associated with any CpG site (p.0.05).In conclusion, our work clearly illustrates some promises and pitfalls of DNA methylation investigations on peripheral blood DNA in large epidemiological cohorts.DNA methylation levels at SLC19A2 are influenced by SNPs in LD with FV Leiden, but these DNA methylation marks do not explain the incomplete penetrance of the FV Leiden mutation.
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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 | 0.001 |
| 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) | 0.001 | 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".