DNA methylation at birth and fine motor ability in childhood: an epigenome-wide association study with replication
Bibliographic record
Abstract
Lower fine motor performance in childhood has been associated with poorer cognitive development and neurodevelopmental conditions such as autism spectrum disorder, yet, biological underpinnings remain unclear. DNA methylation (DNAm), an essential process for healthy neurodevelopment, is a key molecular system of interest. In this study, we conducted the first epigenome-wide association study of neonatal DNAm with childhood fine motor ability and further examined the replicability of epigenetic markers in an independent cohort. The discovery study was embedded in Generation R, a large population-based prospective cohort, including a subsample of 924 ~ 1026 European-ancestry singletons with available data on DNAm in cord blood and fine motor ability at a mean (SD) age of 9.8 (0.4) years. Fine motor ability was measured using a finger-tapping test (3 subtests including left-, right-hand and bimanual), one of the most frequently used neuropsychological instruments of fine motor function. The replication study comprised 326 children with a mean (SD) age of 6.8 (0.4) years from an independent cohort, the INfancia Medio Ambiente (INMA) study. Four CpG sites at birth were prospectively associated with childhood fine motor ability after genome-wide correction. Of these, one CpG (cg07783800 in GNG4) was replicated in INMA, showing that lower levels of methylation at this site were associated with lower fine motor performance in both cohorts. GNG4 is highly expressed in the brain and has been implicated in cognitive decline. Our findings support a prospective, reproducible association between DNAm at birth and fine motor ability in childhood, pointing to GNG4 methylation at birth as a potential biomarker of fine motor ability.
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 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".