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Record W4316464831 · doi:10.3390/genes14010216

Distinct Roles of Histone Lysine Demethylases and Methyltransferases in Developmental Eye Disease

2023· article· en· W4316464831 on OpenAlexaff
Linda M. Reis, Hüban Atilla, Pekka Kannus, Adele Schneider, Samuel Thompson, Tanya Bardakjian, Elena V. Semina

Bibliographic record

VenueGenes · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversity of Alberta
FundersNational Eye Institute
KeywordsBiologyGeneticsHistone methyltransferaseMethyltransferaseEpigeneticsDemethylaseHistonePhenotypeHistone methylationGeneMethylationDNA methylationGene expression

Abstract

fetched live from OpenAlex

Histone lysine methyltransferase and demethylase enzymes play a central role in chromatin organization and gene expression through the dynamic regulation of histone lysine methylation. Consistent with this, genes encoding for histone lysine methyltransferases (KMTs) and demethylases (KDMs) are involved in complex human syndromes, termed congenital regulopathies. In this report, we present several lines of evidence for the involvement of these genes in developmental ocular phenotypes, suggesting that individuals with structural eye defects, especially when accompanied by craniofacial, neurodevelopmental and growth abnormalities, should be examined for possible variants in these genes. We identified nine heterozygous damaging genetic variants in KMT2D (5) and four other histone lysine methyltransferases/demethylases (KMT2C, SETD1A/KMT2F, KDM6A and KDM5C) in unrelated families affected with developmental eye disease, such as Peters anomaly, sclerocornea, Axenfeld-Rieger spectrum, microphthalmia and coloboma. Two families were clinically diagnosed with Axenfeld-Rieger syndrome and two were diagnosed with Peters plus-like syndrome; others received no specific diagnosis prior to genetic testing. All nine alleles were novel and five of them occurred de novo; five variants resulted in premature truncation, three were missense changes and one was an in-frame deletion/insertion; and seven variants were categorized as pathogenic or likely pathogenic and two were variants of uncertain significance. This study expands the phenotypic spectra associated with KMT and KDM factors and highlights the importance of genetic testing for correct clinical diagnosis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.299
Teacher spread0.280 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations12
Published2023
Admission routes1
Has abstractyes

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