Biallelic variants in ARHGAP19 cause a progressive inherited motor-predominant neuropathy
Bibliographic record
Abstract
Charcot-Marie-Tooth (CMT) disease is a clinically and genetically heterogeneous group of hereditary neuropathies. Despite progress in genetic sequencing, for around a quarter of patients the disease has lacked a genetic explanation. Here, we identified 16 recessive variants in the RhoGTPase activating protein 19 gene (ARHGAP19) causing motor-predominant neuropathy in 25 individuals from 20 unrelated families. The ARHGAP19 protein acts as a negative regulator of the RhoA GTPase. In vitro biochemical and cellular assays revealed that patient variants impair the GTPase-activating protein (GAP) activity of ARHGAP19 and reduce ARHGAP19 protein levels. Through the use of patient lines, in vitro GAP assays and in silico molecular modeling, we provided evidence that CMT-associated ARHGAP19 variants act through a loss-of-function (LOF) mechanism. LOF in ARHGAP19 orthologues in Drosophila melanogaster and Danio rerio induced motor defects in axonal and synaptic morphology. Similar cellular phenotypes were observed in ARHGAP19 patient-derived motoneurons. Transcriptomic studies further demonstrated that ARHGAP19 regulates cellular pathways associated with motor proteins and the cell cycle. Taken together, our findings establish ARHGAP19 variants as a cause of inherited neuropathy acting through a LOF mechanism.
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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 | 0.000 |
| 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) | 0.002 | 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".