Clinical delineation and natural history of the <i>PIK3CA</i>‐related overgrowth spectrum
Bibliographic record
Abstract
Somatic mutations in the phosphatidylinositol/AKT/mTOR pathway cause segmental overgrowth disorders. Diagnostic descriptors associated with PIK3CA mutations include fibroadipose overgrowth (FAO), Hemihyperplasia multiple Lipomatosis (HHML), Congenital Lipomatous Overgrowth, Vascular malformations, Epidermal nevi, Scoliosis/skeletal and spinal (CLOVES) syndrome, macrodactyly, and the megalencephaly syndrome, Megalencephaly-Capillary malformation (MCAP) syndrome. We set out to refine the understanding of the clinical spectrum and natural history of these phenotypes, and now describe 35 patients with segmental overgrowth and somatic PIK3CA mutations. The phenotypic data show that these previously described disease entities have considerable overlap, and represent a spectrum. While this spectrum overlaps with Proteus syndrome (sporadic, mosaic, and progressive) it can be distinguished by the absence of cerebriform connective tissue nevi and a distinct natural history. Vascular malformations were found in 15/35 (43%) and epidermal nevi in 4/35 (11%) patients, lower than in Proteus syndrome. Unlike Proteus syndrome, 31/35 (89%) patients with PIK3CA mutations had congenital overgrowth, and in 35/35 patients this was asymmetric and disproportionate. Overgrowth was mild with little postnatal progression in most, while in others it was severe and progressive requiring multiple surgeries. Novel findings include: adipose dysregulation present in all patients, unilateral overgrowth that is predominantly left-sided, overgrowth that affects the lower extremities more than the upper extremities and progresses in a distal to proximal pattern, and in the most severely affected patients is associated with marked paucity of adipose tissue in unaffected areas. While the current data are consistent with some genotype-phenotype correlation, this cannot yet be confirmed.
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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 | 0.000 | 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) | 0.001 | 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".