Identification of 16q21 as a modifier of nonsyndromic orofacial cleft phenotypes
Bibliographic record
Abstract
ABSTRACT Orofacial clefts (OFCs) are common, complex birth defects with extremely heterogeneous phenotypic presentations. Two common subtypes—cleft lip alone (CL) and CL plus cleft palate (CLP)—are typically grouped into a single phenotype for genetic analysis (i.e., CL with or without cleft palate, CL/P). However, mounting evidence suggests there may be unique underlying pathophysiology and/or genetic modifiers influencing expression of these two phenotypes. To this end, we performed a genome‐wide scan for genetic modifiers by directly comparing 450 CL cases with 1,692 CLP cases from 18 recruitment sites across 13 countries from North America, Central or South America, Asia, Europe, and Africa. We identified a region on 16q21 that is strongly associated with different cleft type (P = 5.611 × 10−8). We also identified significant evidence of gene–gene interactions between this modifier locus and two recognized CL/P risk loci: 8q21 and 9q22 (FOXE1) (P = 0.012 and 0.023, respectively). Single nucleotide polymorphism (SNPs) in the 16q21 modifier locus demonstrated significant association with CL over CLP. The marker alleles on 16q21 that increased risk for CL were found at highest frequencies among individuals with a family history of CL (P = 0.003). Our results demonstrate the existence of modifiers for which type of OFC develops and suggest plausible elements responsible for phenotypic heterogeneity, further elucidating the complex genetic architecture of OFCs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".