Early Life Adversity, but not suicide, is associated with less prefrontal cortex gray matter in adulthood
Bibliographic record
Abstract
Abstract Background Suicide and major depression (MDD) are more prevalent in individuals reporting early life adversity (ELA). Prefrontal cortex volume is reduced by stress acutely and progressively in vivo , and changes in neuron and glia density are reported in depressed suicide decedents. We previously found reduced levels of the neurotrophic factor BDNF in suicide decedents and with ELA, and in the present study we sought to determine whether cortex thickness, neuron density or glia density in the dorsolateral prefrontal (BA9) and anterior cingulate (BA24) cortex are associated with ELA or suicide. Methods A total of 52 brains, constituting 13 quadruplets of nonpsychiatric nonsuicide controls and MDD suicide decedents with and without ELA (n=13/group), all with psychological autopsy, were matched for age, sex and postmortem interval. Brains were collected at autopsy and frozen and blocks containing BA9 and BA24 were later dissected, post-fixed and sectioned. Sections were immunostained for NeuN to label neurons and counterstained with thionin to stain glial cell nuclei. Cortex thickness, neuron and glial density and neuron volume were measured by stereology. Results Cortical thickness was 6% less with an ELA history in BA9 and 12% less in BA24 ( p <0.05), but not in depressed suicide decedents in either BA9 or BA24. Neuron density was not different in ELA or in suicide decedents, but glial density was 17% greater with ELA history in BA9 and 15% greater in BA24, but not in suicides. Neuron volume was not different with ELA or suicide. Discussion Reported ELA, but not the stress associated with suicide, is associated with thinner prefrontal cortex and greater glia density in adulthood. ELA may alter normal neurodevelopment and contribute to suicide risk.
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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 | 0.000 |
| 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) | 0.002 | 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".