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Record W4412647599 · doi:10.1186/s13072-025-00612-7

Identification of genetic and non-genetic modifiers of genomic imprinting through screening of imprinted DMR methylation in humans

2025· article· en· W4412647599 on OpenAlex
Francesco Cecere, Raissa Relator, Michael A. Levy, Ankit Verma, Haley McConkey, Bruno Hay Mele, Laura Pignata, Carlo Giaccari, Emilia D’Angelo, Subham Saha, Abu Saadat, Angela Sparago, Claudia Angelini, Flavia Cerrato, Bekim Sadiković, Andrea Riccio

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEpigenetics & Chromatin · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsLondon Health Sciences CentreWestern University
FundersAssociazione Italiana per la Ricerca sul CancroFondazione TelethonGovernment of CanadaMinistero dell’Istruzione, dell’Università e della RicercaGenome CanadaOntario GenomicsOntario Genomics Institute
KeywordsGenomic imprintingBiologyImprinting (psychology)GeneticsIdentification (biology)Human geneticsMethylationDNA methylationComputational biologyEvolutionary biologyGeneGene expressionEcology

Abstract

fetched live from OpenAlex

BACKGROUND: Genomic imprinting is required for normal development, and abnormal methylation of differentially methylated regions (iDMRs) controlling the parent of origin-dependent expression of the imprinted genes has been found in congenital disorders affecting growth, metabolism, neurobehavior, and in cancer. In most of these cases the cause of the imprinting abnormalities is unknown. Also, these studies have generally been performed on a limited number of CpGs, and a systematic investigation of iDMR methylation in the general population is lacking. RESULTS: By analysing a vast number of either in-house generated or online available whole-genome methylation array datasets of unaffected individuals, and patients with complex and rare disorders, we determined the most common iDMR methylation profiles in a large population and identified many genetic and non-genetic factors contributing to their variability in blood DNA. We found that methylation variability was not homogeneous within the iDMRs and that the CpGs closer to the ZFP57 binding sites are less susceptible to methylation changes. We demonstrated the methylation polymorphism of three iDMRs and the atypical behaviour of several others, and reported the association of 25 disease- and 47 non-disease-complex traits as well as 15 Mendelian and chromosomal disorders with iDMR methylation changes. The most significantly associated complex traits included ageing, intracytoplasmic sperm injection, African versus European ancestry, female sex, pre- and postnatal exposure to pollutants and blood cell type compositions, while the associated genetic diseases included Down syndrome and the developmental disorders with molecular defects in the DNA methyltransferases DNMT1 and DNMT3B, H3K36 methyltransferase SETD2, chromatin remodelers SRCAP and SMARCA4 and transcription factor ADNP. CONCLUSIONS: These findings identify several genetic and non-genetic factors including new genes associated with genomic imprinting maintenance in humans, which may have a role in the aetiology of the diseases with imprinting abnormalities and have clear implications in molecular diagnostics.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.978

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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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