Struggling Can Also Show on the Inside: Current Knowledge of the Impact of Childhood Maltreatment on Biomarkers in Mood Disorderss
Bibliographic record
Abstract
Maj Vinberg,1,2 Roger S McIntyre,3,4 Annamaria Giraldi,2,5,* Klara Coello6,* 1Mental Health Centre Northern Zealand, the Early Multimodular Prevention, and Intervention Research Institution (EMPIRI) – Mental Health Services CPH, Copenhagen, Denmark; 2Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; 3Mood Disorders Psychopharmacology Unit, Toronto Western Hospital, University Health Network, Toronto, ON, Canada; 4Institute of Medical Science, University of Toronto, Toronto, ON, Canada; 5Sexological Clinic, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark; 6Copenhagen Affective Disorder Research Centre (CADIC), Psychiatric Centre Copenhagen, Frederiksberg, Denmark*These authors contributed equally to this workCorrespondence: Maj Vinberg, Dyrehavevej 48, Hillerød, 3400, Denmark, Tel +453864 3227, Email maj.vinberg@regionh.dkAbstract: The link between childhood maltreatment and mood disorders is complex and involves multiple bio-psycho-social factors that affect multiple molecular pathways. The present narrative review aims to clarify the current understanding of the impact of childhood maltreatment on biomarkers in patients with mood disorders and their first-degree relatives. Neurotransmitters, such as serotonin, dopamine, norepinephrine, and hormones (eg the stress hormone cortisol), play a crucial role in regulating mood and emotion. Childhood maltreatment can alter and affect the levels and functioning of these neurotransmitters in the brain; further, childhood maltreatment can lead to structural and connectivity changes in the brain, hence contributing to the development of mood disorders and moderating illness presentation and modifying response to treatments. Childhood maltreatment information, therefore, appears mandatory in treatment planning and is a critical factor in therapeutic algorithms. Further research is needed to fully understand these pathways and develop new treatment modalities for individuals with mood disorders who have experienced childhood maltreatment and effective preventive interventions for individuals at risk of developing mood disorders.Keywords: biomarkers, childhood maltreatment, mood disorders, biosignatures, biotype
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".