Clinical Genetic Risk Variants Inform a Functional Protein Interaction Network for Tetralogy of Fallot
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Tetralogy of Fallot (TOF)—the most common cyanotic heart defect in newborns—has evidence of multiple genetic contributing factors. Identifying variants that are clinically relevant is essential to understand patient-specific disease susceptibility and outcomes and could contribute to delineating pathomechanisms. Methods: Using a clinically driven strategy, we reanalyzed exome sequencing data from 811 probands with TOF, to identify rare loss-of-function and other likely pathogenic variants in genes associated with congenital heart disease. Results: We confirmed a major contribution of likely pathogenic variants in FLT4 (VEGFR3 [vascular endothelial growth factor receptor 3]; n=14) and NOTCH1 (n=10) and identified 1 to 3 variants in each of 21 other genes, including ATRX , DLL4 , EP300 , GATA6 , JAG1 , NF1 , PIK3CA , RAF1 , RASA1 , SMAD2 , and TBX1 . In addition, multiple loss-of-function variants provided support for 3 emerging congenital heart disease/TOF candidate genes: KDR (n=4), IQGAP1 (n=3), and GDF1 (n=8). In total, these variants were identified in 63 probands (7.8%). Using the 26 composite genes in a STRING protein interaction enrichment analysis revealed a biologically relevant network ( P =3.3×10 −16 ), with VEGFR2 (vascular endothelial growth factor receptor 2; KDR ) and NOTCH1 (neurogenic locus notch homolog protein 1) representing central nodes. Variants associated with arrhythmias/sudden death and heart failure indicated factors that could influence long-term outcomes. Conclusions: The results are relevant to precision medicine for TOF. They suggest considerable clinical yield from genome-wide sequencing, with further evidence for KDR (VEGFR2) as a congenital heart disease/TOF gene and for VEGF (vascular endothelial growth factor) and Notch signaling as mechanisms in human disease. Harnessing the genetic heterogeneity of single gene defects could inform etiopathogenesis and help prioritize novel candidate genes for TOF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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