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Record W4221110947 · doi:10.1186/s12864-022-08451-6

DNA methylation changes in cord blood and the developmental origins of health and disease – a systematic review and replication study

2022· review· en· W4221110947 on OpenAlexafffundabout
Loubna Akhabir, Randa Stringer, Dipika Desai, Piush J. Mandhane, Meghan B. Azad, Padmaja Subbarao, Stuart E. Turvey, Guillaume Paré, Sonia S. Anand, Stephanie A. Atkinson, Allan B. Becker, Jeffrey R. Brook, Judah A. Denburg, Russell J. de Souza, Milan Gupta, Michael S. Kobor, Diana L. Lefebvre, Wendy Lou, Sarah D. McDonald, Andrew Mente, David Meyre, Theo J. Moraes, Katherine M. Morrison, Malcolm R. Sears, Koon Teo, Julie Wilson, Salim Yusuf, Gita Wahi, Michael A. Zulyniak

Bibliographic record

VenueBMC Genomics · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsImpactThrombosis and Atherosclerosis Research InstituteBC Children's HospitalUniversity of British ColumbiaHospital for Sick ChildrenUniversity of ManitobaChildren's Hospital Research Institute of ManitobaPopulation Health Research InstituteUniversity of AlbertaMcMaster University
FundersIndian Council of Medical ResearchMcMaster UniversityHamilton Health SciencesCanadian Institutes of Health ResearchAllerGenCanada Excellence Research Chairs, Government of CanadaHeart and Stroke Foundation of Canada
KeywordsCord bloodDNA methylationPregnancyOffspringBiologyEpigenomeGestational diabetesGestational agePhysiologyMedicineGestationImmunologyGeneticsGene

Abstract

fetched live from OpenAlex

BACKGROUND: Environmental exposures in utero which modify DNA methylation may have a long-lasting impact on health and disease in offspring. We aimed to identify and replicate previously published genomic loci where DNA methylation changes are attributable to in utero exposures in the NutriGen birth cohort studies Alliance. METHODS: We reviewed the literature to identify differentially methylated sites of newborn DNA which are associated with the following five traits of interest maternal diabetes, pre-pregnancy body mass index (BMI), diet during pregnancy, smoking, and gestational age. We then attempted to replicate these published associations in the Canadian Healthy Infant Longitudinal Development (CHILD) and the South Asian birth cohort (START) cord blood epigenome-wide data. RESULTS: We screened 68 full-text articles and identified a total of 17 cord blood epigenome-wide association studies (EWAS) of the traits of interest. Out of the 290 CpG sites reported, 19 were identified in more than one study; all of them associated with maternal smoking. In CHILD and START EWAS, thousands of sites associated with gestational age were identified and maintained significance after correction for multiple testing. In CHILD, there was differential methylation observed for 8 of the published maternal smoking sites. No other traits tested (i.e., folate levels, gestational diabetes, birthweight) replicated in the CHILD or START cohorts. CONCLUSIONS: Maternal smoking during pregnancy and gestational age are strongly associated with differential methylation in offspring cord blood, as assessed in the EWAS literature and our birth cohorts. There are a limited number of reported methylation sites associated in more than two independent studies related to pregnancy. Additional large studies of diverse populations with fine phenotyping are needed to produce robust epigenome-wide data in order to further elucidate the effect of intrauterine exposures on the infants' methylome.

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)0.012
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0050.009
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.337
Teacher spread0.277 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations27
Published2022
Admission routes3
Has abstractyes

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