Family history of depression is associated with younger age of onset in patients with recurrent depression
Bibliographic record
Abstract
BACKGROUND: Genetic epidemiology data suggest that younger age of onset is associated with family history (FH) of depression. The present study tested whether the presence of FH for depression or anxiety in first-degree relatives determines younger age of onset for depression. METHOD: A sample of 1022 cases with recurrent major depressive disorder (MDD) was recruited at the Max Planck Institute and at two affiliated hospitals. Patients were assessed using the Schedules for Clinical Assessment in Neuropsychiatry and questionnaires including demographics, medical history, questions on the use of alcohol and tobacco, personality traits and life events. Survival analysis and the Cox proportional hazard model were used to determine whether FH of depression signals earlier age of onset of depression. RESULTS: Patients who reported positive FH had a significantly earlier age of onset than patients who did not report FH of depression (log-rank=48, df=1, p<0.0001). The magnitude of association of FH varies by age of onset, with the largest estimate for MDD onset before age 20 years (hazard ratio=2.2, p=0.0009), whereas FH is not associated with MDD for onset after age 50 years (hazard ratio=0.89, p=0.5). The presence of feelings of guilt, anxiety symptoms and functional impairment due to depressive symptoms appear to characterize individuals with positive FH of depression. CONCLUSIONS: FH of depression contributes to the onset of depression at a younger age and may affect the clinical features of the illness.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".