Expanding the clinical and molecular spectrum of <scp><i>ATP6V1A</i></scp> related metabolic cutis laxa
Bibliographic record
Abstract
Several inborn errors of metabolism show cutis laxa as a highly recognizable feature. One group of these metabolic cutis laxa conditions is autosomal recessive cutis laxa type 2 caused by defects in v-ATPase components or the mitochondrial proline cycle. Besides cutis laxa, muscular hypotonia and cardiac abnormalities are hallmarks of autosomal recessive cutis laxa type 2D (ARCL2D) due to pathogenic variants in ATP6V1A encoding subunit A of the v-ATPase. Here, we report on three affected individuals from two families with ARCL2D in whom we performed whole exome and Sanger sequencing. We performed functional studies in fibroblasts from one individual, summarized all known probands' clinical, molecular, and biochemical features and compared them, also to other metabolic forms of cutis laxa. We identified novel missense and the first nonsense variant strongly affecting ATP6V1A expression. All six ARCL2D affected individuals show equally severe cutis laxa and dysmorphism at birth. While for one no information was available, two died in infancy and three are now adolescents with mild or absent intellectual disability. Muscular weakness, ptosis, contractures, and elevated muscle enzymes indicated a persistent myopathy. In cellular studies, a fragmented Golgi compartment, a delayed Brefeldin A-induced retrograde transport and glycosylation abnormalities were present in fibroblasts from two individuals. This is the second and confirmatory report on pathogenic variants in ATP6V1A as the cause of this extremely rare condition and the first to describe a nonsense allele. Our data highlight the tremendous clinical variability of ATP6V1A related phenotypes even within the same family.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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 | 0.000 |
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".