GATA2 deficiency in children and adults with severe pulmonary alveolar proteinosis and hematologic disorders
Bibliographic record
Abstract
BACKGROUND: The majority of cases with severe pulmonary alveolar proteinosis (PAP) are caused by auto-antibodies against GM-CSF. A multitude of genetic and exogenous causes are responsible for few other cases. Goal of this study was to determine the prevalence of GATA2 deficiency in children and adults with PAP and hematologic disorders. METHODS: Of 21 patients with GM-CSF-autoantibody negative PAP, 13 had no other organ involvement and 8 had some form of hematologic disorder. The latter were sequenced for GATA2. RESULTS: Age at start of PAP ranged from 0.3 to 64 years, 4 patients were children. In half of the subjects GATA2-sequence variations were found, two of which were considered disease causing. Those two patients had the typical phenotype of GATA2 deficiency, one of whom additionally showed a previously undescribed feature - a cholesterol pneumonia. Hematologic disorders included chronic myeloic leukemia, juvenile myelo-monocytic leukemia, lymphoblastic leukemia, sideroblastic anemia and two cases of myelodysplastic syndrome (MDS). A 4 year old child with MDS and DiGeorge Syndrome Type 2 was rescued with repetitive whole lung lavages and her PAP was cured with heterologous stem cell transplant. CONCLUSIONS: In children and adults with severe GM-CSF negative PAP a close cooperation between pneumologists and hemato-oncologists is needed to diagnose the underlying diseases, some of which are caused by mutations of transcription factor GATA2. Treatment with whole lung lavages as well as stem cell transplant may be successful.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".