Assessment of genes involved in lysosomal diseases using the ClinGen Clinical Validity framework
Bibliographic record
Abstract
Lysosomal diseases (LDs) are a heterogeneous group of rare genetic disorders that result in impaired lysosomal function, leading to progressive multiorgan system dysfunction. Accurate diagnosis is paramount to initiating targeted therapies early in the disease process in addition to providing prognostic information and appropriate support for families. In recent years, genomic sequencing technologies have become the first-line approach in the diagnosis of LDs. Understanding the clinical validity of the role of a gene in a disease is critical for the development of genomic technologies, such as which genes to include on next generation sequencing panels, and the interpretation of results from exome and genome sequencing. To this aim, the ClinGen Lysosomal Diseases Gene Curation Expert Panel utilized a semi-quantitative framework incorporating genetic and experimental evidence to assess the clinical validity of the 56 LD-associated genes on the Lysosomal Disease Network's list. Here, we describe the results, and the key themes and challenges encountered.
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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 | 0.075 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".