Heterozygous CAV1 frameshift mutations (MIM 601047) in patients with atypical partial lipodystrophy and hypertriglyceridemia
Bibliographic record
Abstract
BACKGROUND: Mice with a deleted Cav1 gene encoding caveolin-1 develop adipocyte abnormalities and insulin resistance. From genomic DNA of patients with atypical lipodystrophy and hypertriglyceridemia who had no mutations in any known lipodystrophy gene, we used DNA sequence analysis to screen the coding regions of human CAV1 (MIM 601047). RESULTS: We found a heterozygous frameshift mutation in CAV1, designated I134fsdelA-X137, in a female patient who had atypical partial lipodystrophy, with subcutaneous fat loss affecting the upper part of her body and face, but sparing her legs, gluteal region and visceral fat stores. She had severe type 5 hyperlipoproteinemia, with recurrent pancreatitis. In addition, she had some atypical features, including congenital cataracts and neurological findings. Her father was also heterozygous for this mutation, and had a similar pattern of fat redistribution, hypertriglyceridemia and congenital cataracts, with milder neurological involvement. An unrelated patient had a different heterozygous frameshift mutation in the CAV1 gene, designated -88delC. He also had a partial lipodystrophy phenotype, with subcutaneous fat loss affecting the arms, legs and gluteal region, but sparing his face, neck and visceral fat stores. He also had severe type 5 hyperlipoproteinemia, with recurrent pancreatitis; however he had no clinically apparent neurological manifestations. The mutations were absent from the genomes of 1063 healthy individuals. CONCLUSION: Thus, very rare CAV1 frameshift mutations appear to be associated with atypical lipodystrophy and hypertriglyceridemia.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".