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Record W4320065861 · doi:10.1289/isee.2022.o-pk-07

DNA methylation as a potential mediator of the association between indoor air pollution and neurodevelopmental delay in a South African birth cohort

2022· article· en· W4320065861 on OpenAlexaff
Dakotah Feil, Grace M. Christensen, Sarina Abrishamcar, Aneesa Vanker, Nastassja Koen, Anna Kilanowski, Nadia Hoffman, Kirsten A. Donald, Michael S. Kobor, Heather J. Zar, Dan J. Stein, Anke Hüls

Bibliographic record

VenueISEE Conference Abstracts · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsVancouver Hospital and Health Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsdNaMDNA methylationMediationBayley Scales of Infant DevelopmentCpG siteMethylationMedicineToxicantOffspringCognitionPregnancyEnvironmental healthBiologyGeneticsInternal medicineGenePsychiatryPsychomotor learning

Abstract

fetched live from OpenAlex

Background and Aim Prenatal exposure to indoor air pollution (IAP) has been linked to neurodevelopmental delay in toddlers. Changes in DNA methylation (DNAm) have been independently associated with both prenatal air pollution exposure and delayed neurodevelopment. Investigating DNAm as a mediator may help to elucidate the biological pathways driving the association between IAP and neurodevelopmental delay. In this study, we aim to identify differentially methylated CpG sites and gene regions that mediate this association. Methods We analyzed data from 142 mother-child pairs enrolled in the South African Drakenstein Child Health Study. DNAm from cord blood was measured using the Infinium MethylationEPIC and HumanMethylation450 arrays. Particulate matter with an aerodynamic diameter of 10m or less (PM10) was measured inside participants’ homes during the second trimester of pregnancy. Neurodevelopment was assessed at age 2 years using the Bayley Scales of Infant and Toddler Development III in four domains (cognitive function, general adaptive behavior, language, and motor function). We used three high-dimensional mediation analysis techniques (HIMA, DACT and gHMA) to identify potential mediators, complemented with causal mediation analysis to assess the robustness of our results. Results Differential methylation at 29 CpG sites and 4 gene regions (GOPC, RP11-74K11.1, DYRK1A, RNMT) was found to significantly mediate the association between prenatal PM10 exposure and cognitive neurodevelopment. Estimated proportion mediated (95%-confidence interval) ranged from 0.29 (0.01,0.86) for cg00694520 to 0.54 (0.11,1.56) for cg05023582. Conclusions DYRK1A and several of the genes our CpG sites mapped to, including CNKSR1, IPO13, IFNGR1, LONP2, and CDH1 are associated with biological pathways implicated in neurodevelopment and three of our identified CpG sites (cg23560546, cg22572779, cg15000966) have been previously associated with fetal brain development. These findings suggest that DNAm may mediate the association between prenatal PM10 exposure and cognitive neurodevelopment. Keywords: particulate matter, neurodevelopment, cord blood, epigenetics, newborn DNA methylation

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.223
Teacher spread0.211 · 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 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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