Three cases of multi-generational Gaucher disease and colon cancer from an Ashkenazi Jewish family: A lesson for cascade screening
Bibliographic record
Abstract
Gaucher disease (GD) is one of the commonest lysosomal storage diseases that is inherited in an autosomal recessive manner and affects 1 in 50,000 to 100,000 people in the general population. The frequency is much higher (1 in 500 to 1000) in people of Ashkenazi Jewish heritage due to a founder effect. GD is caused by decreased or absent activity of β-glucosidase with subsequent accumulation of the substrate glucosylceramide in macrophages due to genetic alterations in the GBA gene. These often accumulate in the spleen, liver and bone marrow. Three types exist, with type 1 being the most common, also referred to as non-neuronopathic GD. A broad clinical spectrum exists; patients of any age may manifest with hepatosplenomegaly, anaemia, thrombocytopenia, lung disease, bone abnormalities or may remain asymptomatic throughout their lifespan. Multi-generational disease does not usually occur because the risk of disease with each pregnancy, presuming both parents are carriers of the condition, is 25%. Herein, we report an Ashkenazi Jewish family with multi-generational GD type 1 and multigenerational colon cancer in the same three individuals, and reinforce the importance of cascade screening in families with genetic conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".