Genetic Predictors of Fibrin D-Dimer Levels in Healthy Adults
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Bibliographic record
Abstract
BACKGROUND: Fibrin fragment D-dimer, one of several peptides produced when crosslinked fibrin is degraded by plasmin, is the most widely used clinical marker of activated blood coagulation. To identity genetic loci influencing D-dimer levels, we performed the first large-scale, genome-wide association search. METHODS AND RESULTS: A genome-wide investigation of the genomic correlates of plasma D-dimer levels was conducted among 21 052 European-ancestry adults. Plasma levels of D-dimer were measured independently in each of 13 cohorts. Each study analyzed the association between ≈2.6 million genotyped and imputed variants across the 22 autosomal chromosomes and natural-log–transformed D-dimer levels using linear regression in additive genetic models adjusted for age and sex. Among all variants, 74 exceeded the genome-wide significance threshold and marked 3 regions. At 1p22, rs12029080 (P=6.4×10(-52)) was 46.0 kb upstream from F3, coagulation factor III (tissue factor). At 1q24, rs6687813 (P=2.4×10(-14)) was 79.7 kb downstream of F5, coagulation factor V. At 4q32, rs13109457 (P=2.9×10(-18)) was located between 2 fibrinogen genes: 10.4 kb downstream from FGG and 3.0 kb upstream from FGA. Variants were associated with a 0.099-, 0.096-, and 0.061-unit difference, respectively, in natural-log–transformed D-dimer and together accounted for 1.8% of the total variance. When adjusted for nonsynonymous substitutions in F5 and FGA loci known to be associated with D-dimer levels, there was no evidence of an additional association at either locus. CONCLUSIONS: Three genes were associated with fibrin D-dimer levels. Of these 3, the F3 association was the strongest, and has not been previously reported.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it