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Record W3092710597 · doi:10.1017/s0954579420000899

DNA methylation profiles in adults born at extremely low birth weight

2020· article· en· W3092710597 on OpenAlexafffund
Karen J. Mathewson, Patrick O. McGowan, Wilfred C. de Vega, Ryan J. Van Lieshout, Katherine M. Morrison, Saroj Saigal, Louis A. Schmidt

Bibliographic record

VenueDevelopment and Psychopathology · 2020
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsUniversity of TorontoMcMaster University
FundersCanadian Institutes of Health Research
KeywordsdNaMBirth weightEpigeneticsDNA methylationGeneLow birth weightCohortMethylationPhysiologyGeneticsBiologyPregnancyMedicineInternal medicineGene expression

Abstract

fetched live from OpenAlex

Effects of stresses associated with extremely preterm birth may be biologically "recorded" in the genomes of individuals born preterm via changes in DNA methylation (DNAm) patterns. Genome-wide DNAm profiles were examined in buccal epithelial cells from 45 adults born at extremely low birth weight (ELBW; ≤1000 g) in the oldest known cohort of prospectively followed ELBW survivors (Mage = 32.35 years, 17 male), and 47 normal birth weight (NBW; ≥2500 g) control adults (Mage = 32.43 years, 20 male). Sex differences in DNAm profiles were found in both birth weight groups, but they were greatly enhanced in the ELBW group (77,895 loci) versus the NBW group (3,424 loci), suggesting synergistic effects of extreme prenatal adversity and sex on adult DNAm profiles. In men, DNAm profiles differed by birth weight group at 1,354 loci on 694 unique genes. Only two loci on two genes distinguished between ELBW and NBW women. Gene ontology (GO) and network analyses indicated that loci differentiating between ELBW and NBW men were abundant in genes within biological pathways related to neuronal development, synaptic transportation, metabolic regulation, and cellular regulation. Findings suggest increased sensitivity of males to long-term epigenetic effects of extremely preterm birth. Group differences are discussed in relation to particular gene functions.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.505

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 head0.046
GPT teacher head0.331
Teacher spread0.285 · 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 designObservational
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

Citations5
Published2020
Admission routes2
Has abstractyes

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