Methylome-wide association study of early life stressors and adult mental health reveals a relationship between birth date and cell type composition in blood
Bibliographic record
Abstract
Abstract The environment and events that we are exposed to in utero, during birth and in early childhood influence our future physical and mental health. The underlying mechanisms that lead to these outcomes in adulthood are unclear, but long-term changes in epigenetic marks, such as DNA methylation, could act as a mediating factor or biomarker. DNA methylation data was assayed at 713,522 CpG sites from 9,537 participants of the Generation Scotland: Scottish Family Health Study, a family-based cohort with extensive data on genetic, medical, family history and lifestyle information. Methylome-wide association studies of eight early life environment phenotypes and two adult mental health phenotypes were conducted using DNA methylation data collected from adult whole blood samples. Two genes involved with different developmental pathways (PRICKLE2 and ABI1) were annotated to CpG sites associated with preterm birth (P < 1.27 × 10 −9 ). A further two genes important to the development of sensory pathways (SOBP and RPGRIP1) were annotated to sites associated with low birth weight (P < 4.35 × 10 −8 ). Genes and gene-sets annotated from associated CpGs sites and methylation profile scores were then used to quantify any overlap between the early life environment and mental health traits. However, there was no evidence of any overlap after applying a correction for multiple testing. Time of year of birth was found to be associated with a significant difference in estimated lymphocyte and neutrophil counts. Early life environments influence the risk of developing mental health disorders later in life; however, this study provides no evidence that this is mediated by stable changes to the methylome detectable in peripheral blood.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".