Variation in the methylenetetrahydrofolate dehydrogenase 1‐like (MTHFD1L) gene and cardiovascular disease (CVD) risk
Bibliographic record
Abstract
Two recent genome‐wide association (GWA) studies identified an intronic SNP (rs6922269) in a region of high linkage disequilibrium (LD) in the MTHFD1L gene that was associated with an increased heart disease risk. The present study explored joint genotypes across 6 variants in this LD block in relation to CVD using a nested case‐control design (378 cases, 425 noncases). OR and 95% CI for the joint genotypes were estimated with conditional logistic regression. In HapMap CEU data, certain joint genotypes were found to be unambiguous proxies for the rs6922269 and rs9767752 SNPs, thus these genotypes could be inferred. Participants with combinations that were unambiguous proxies for genotype rs6922269 AA had a 1.27‐fold increased CVD risk vs. genotype GG (95% CI 0.75, 2.1), a finding similar in magnitude to GWA findings, albeit with lower power. The rs9767752 SNP is proximal to an exon, and joint genotypes that were an unambiguous proxy for the CC genotype (vs. TT genotype) at this locus showed the strongest association with CVD (OR 2.28; 95% CI 1.0, 5.1). Joint genotypes representing the rs9767752 CT genotype were associated with a reduced CVD risk (0.79; 95% CI 0.5, 1.3). Overall the results serve as an adequate replication of association between variation in MTHFD1L and CVD. Funding: NIH T32 DK007158 ‐33 (SMW), G105 NHLBI Resequencing and Genotyping Service (PAC). Grant Funding Source NIH T32 DK007158 ‐33 (SMW)
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".