Developmental origins of depression‐related white matter properties: Findings from a prenatal birth cohort
Bibliographic record
Abstract
Depression is the leading cause of years lost due to disability worldwide. Still, the mechanisms underlying its development are not well understood. This study aimed to evaluate white-matter properties associated with depressive symptomatology in young adulthood and their developmental origins. Diffusion tensor imaging and assessment of depressive symptomatology were conducted in 128 young adults (47% male, age 23-24) from a prenatal birth cohort (European Longitudinal Study of Pregnancy and Childhood). For a subset of these individuals, the database included information on prenatal stress (n = 93) and depressive symptoms during adolescence (assessed repeatedly at age 15 and 19). Depressive symptoms in young adulthood were associated with lower fractional anisotropy in the left and right cingulum and higher fractional anisotropy in the right corticospinal tract and superior longitudinal fasciculus. Further analyses revealed that prenatal stress and depressive symptomatology during adolescence were independent predictors of altered white-matter properties in the cingulum in young adulthood. We conclude that typically developing young adults with more depressive symptoms already exhibit tract-specific alterations in white-matter properties and that prenatal stress and depressive symptomatology during adolescence might contribute to their development.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".