Genetic Interactions in Nonsyndromic Orofacial Clefts in Europe—EUROCRAN Study
Bibliographic record
Abstract
BACKGROUND: Nonsyndromic cleft lip with or without cleft palate (nsCL±P) and nonsyndromic cleft palate (nsCP) are caused by a combination of genetic and environmental risk factors. We investigated gene-environment and gene-gene joint effects in a large multicenter study of case-parent triads. METHODS: The nsCL±P or nsCP triads were recruited in 11 European countries between 2001 and 2005. We collected DNA samples from infants and from their mothers and fathers, and mothers completed a questionnaire on exposures, including smoking and folic acid supplement use during pregnancy. We used log-linear regression to estimate relative risks (RRs) and 95% confidence intervals (CIs) for associations between nsCL±P or nsCP and variants in MTHFR, MTHFD1, TGFA, SATB2, and MSX1, stratifying by environmental or genetic factors. RESULTS: We obtained genotype and exposure data for 728 nsCL±P triads and 292 nsCP triads. In male infants, there was no association between the mother's homozygous MSX1 p(CA) *4/*4 genotype and nsCL±P (RR, 0.98; 95% CI, 0.63-1.54), but this maternal genotype resulted in a doubling of risk for female infants (RR, 2.21; 95% CI, 1.13-4.34). There was evidence suggestive of gene-gene joint-effects between MTHFR-TGFA for nsCP but not for nsCL±P. CONCLUSION: Although we chose the genes and their variants and putative joint effects based on associations previously reported in the literature, we replicated few associations. These results do not provide evidence supporting associations between these genes and oral clefts in European populations, although gene-environment and gene-gene interactions could play a role in oral cleft etiology.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".