Psychopathological precursors of the onset of mood disorders in offspring of parents with and without mood disorders: results of a 13‐year prospective cohort high‐risk study
Bibliographic record
Abstract
BACKGROUND: There is still limited evidence from prospective high-risk research on the evolution of specific disorders that may emerge early in the development of mood disorders. Moreover, few studies have examined the specificity of mood disorder subtypes among offspring of parents with both major subtypes of mood disorders and controls based on prospective tracking across the transition from childhood to adulthood. Our specific objectives were to (a) identify differences in patterns of psychopathological precursors among youth with (hypo)mania compared to MDD and (b) examine whether these patterns differ by subtypes of parental mood disorders. METHODS: Our data stem from a prospective cohort study of 449 directly interviewed offspring (51% female, mean age 10.1 years at study intake) of 88 patients with BPD, 71 with MDD, 30 with substance use disorders and 60 medical controls. The mean duration of follow-up was 13.2 years with evaluations conducted every three years. RESULTS: Within the whole cohort of offspring, MDE (Hazard Ratio = 4.44; 95%CI: 2.19-9.02), CD (HR = 3.31;1.55-7.07) and DUD (HR = 2.54; 1.15-5.59) predicted the onset of (hypo)manic episodes, whereas MDD in offspring was predicted by SAD (HR = 1.53; 1.09-2.15), generalized anxiety (HR = 2.56; 1.05-6.24), and panic disorder (HR = 3.13; 1.06-9.23). The early predictors of (hypo)mania in the whole cohort were also significantly associated with the onset of (hypo)mania among the offspring of parents with BPD. CONCLUSIONS: The onset of mood disorders is frequently preceded by identifiable depressive episodes and nonmood disorders. These precursors differed by mood subtype in offspring. High-risk offspring with these precursors should be closely monitored to prevent the further development of MDD or conversion to BPD.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".