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Record W7117302272 · doi:10.1002/1545-5017.70023

Bone Marrow Failure as an Underrecognized Feature of KAT6A Syndrome

2025· article· en· W7117302272 on OpenAlexaffabout
Ye Jee Shim, Bruce Crooks, Hyoung Jin Kang, Kyung Taek Hong, Jung Yoon Choi, Hye Ra Jung, Chang Ahn Seol, Rinu Mathew, Yigal Dror

Bibliographic record

VenuePediatric Blood & Cancer · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsUniversity of TorontoHospital for Sick ChildrenNova Scotia Health AuthorityIzaak Walton Killam Health Centre
Fundersnot available
KeywordsBone marrowHaematopoiesisFeature (linguistics)Bone marrow failureChromatinHistoneHistone acetyltransferase

Abstract

fetched live from OpenAlex

KAT6A syndrome (Arboleda-Tham syndrome) is a rare disorder caused by heterozygous pathogenic variants in KAT6A, a histone acetyltransferase essential for chromatin remodeling and hematopoietic stem cell function. While neurodevelopmental features are well established, hematologic manifestations are underrecognized. We describe two pediatric patients from Canada and Korea who developed severe bone marrow failure and were successfully treated with hematopoietic stem cell transplantation. One carried an upstream truncating variant, the other a downstream frameshift; both disrupted domains critical for transcriptional regulation. The literature review revealed additional cases with cytopenias. Our findings highlight bone marrow failure as an overlooked feature of KAT6A syndrome.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.004
GPT teacher head0.243
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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