PIK3CA-associated developmental disorders exhibit distinct classes of mutations with variable expression and tissue distribution
Bibliographic record
Abstract
Mosaicism is increasingly recognized as a cause of developmental disorders with the advent of next-generation sequencing (NGS). Mosaic mutations of PIK3CA have been associated with the widest spectrum of phenotypes associated with overgrowth and vascular malformations. We performed targeted NGS using 2 independent deep-coverage methods that utilize molecular inversion probes and amplicon sequencing in a cohort of 241 samples from 181 individuals with brain and/or body overgrowth. We identified PIK3CA mutations in 60 individuals. Several other individuals ( n = 12) were identified separately to have mutations in PIK3CA by clinical targeted-panel testing ( n = 6), whole-exome sequencing ( n = 5), or Sanger sequencing ( n = 1). Based on the clinical and molecular features, this cohort segregated into three distinct groups: (a) severe focal overgrowth due to low-level but highly activating (hotspot) mutations, (b) predominantly brain overgrowth and less severe somatic overgrowth due to less-activating mutations, and (c) intermediate phenotypes (capillary malformations with overgrowth) with intermediately activating mutations. Sixteen of 29 PIK3CA mutations were novel. We also identified constitutional PIK3CA mutations in 10 patients. Our molecular data, combined with review of the literature, show that PIK3CA -related overgrowth disorders comprise a discontinuous spectrum of disorders that correlate with the severity and distribution of mutations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".