A multi-ethnic genome-wide association study identifies novel loci for non-syndromic cleft lip with or without cleft palate on 2p24.2, 17q23 and 19q13
Bibliographic record
Abstract
Orofacial clefts (OFCs), which include non-syndromic cleft lip with or without cleft palate (CL/P), are among the most common birth defects in humans, affecting approximately 1 in 700 newborns. CL/P is phenotypically heterogeneous and has a complex etiology caused by genetic and environmental factors. Previous genome-wide association studies (GWASs) have identified at least 15 risk loci for CL/P. As these loci do not account for all of the genetic variance of CL/P, we hypothesized the existence of additional risk loci. We conducted a multiethnic GWAS in 6480 participants (823 unrelated cases, 1700 unrelated controls and 1319 case-parent trios) with European, Asian, African and Central and South American ancestry. Our GWAS revealed novel associations on 2p24 near FAM49A, a gene of unknown function (P 4.22 10 8 ), and 19q13 near RHPN2, a gene involved in organizing the actin cytoskeleton (P 4.17 10 8 ). Other regions reaching genome-wide significance were 1p36 (PAX7), 1p22 (ARHGAP29), 1q32 (IRF6), 8q24 and 17p13 (NTN1), all reported in previous GWASs. Stratification by ancestry group revealed a novel association with a region on 17q23 (P 2.92 10 8 ) among individuals with European ancestry. This region included several promising candidates including TANC2, an oncogene required for development, and DCAF7, a scaffolding protein required for craniofacial development. In the Central and South American ancestry group, significant associations with loci previously identified in Asian or European ancestry groups reflected their admixed ancestry. In summary, we have identified novel CL/P risk loci and suggest new genes involved in craniofacial development, confirming the highly heterogeneous etiology 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".