Contributions of intrinsic and environmental factors to early life DNA methylation
Bibliographic record
Abstract
Many early experiences and exposures are known to cause health disparities later in life, suggesting that they are somehow ‘biologically embedded’. The mechanisms underlying ‘biological embedding’ are currently not well understood. However, emerging evidence has implicated a potential contribution from epigenetic modifications, such as DNA methylation (DNAm), which has been shown to associate with early life experiences of low socioeconomic status. Additional related experiences have also been connected with DNAm, including parental stress, childhood maltreatment or deprivation, and maternal mental health problems during the perinatal period. The relationship between early life experience and epigenetics is complicated by internal psychological and physiological factors, as well as genetic variation, which can account for 20% to 80% of inter-individual epigenetic differences. As well, stress reactivity and temperament are predictive of how a child may interact with his or her environment and can affect how such exposures are internalized. Thus, the main objectives of my dissertation were to elucidate the relationships between childhood environment, DNAm, genetic variation, and behaviour, to understand how these systems influence one another. Using matched DNAm profiles from blood and buccal tissue from a cross-sectional cohort of Canadian children, I uncovered tissue-specific and -shared DNAm signatures in order to glean the utility of accessible tissues in epigenetic association studies. In a longitudinal cohort, I tested the hypothesis that indicators of children’s early internal, biological and behavioural responses to stressful challenges are linked to stable patterns of DNAm later in life; I found relationships between biobehavioural response propensities in early life and patterns of DNAm in DLX5 and IGF2 genes at ages 15 and 18. Finally, I examined the epigenetic correlates of familial socioeconomic status in matched childhood peripheral blood and dried neonatal blood spot samples, allowing me to assess the DNAm pattern over time. Together these findings build upon our current understanding of the role of DNAm in biological embedding and more broadly, the field of social epigenetics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".