Polygenic Scores and Mood Disorder Onsets in the Context of Family History and Early Psychopathology
Bibliographic record
Abstract
Importance: Bipolar disorder (BD) and major depressive disorder (MDD) aggregate within families, with risk often first manifesting as early psychopathology, including attention-deficit/hyperactivity disorder (ADHD) and anxiety disorders. Objective: To determine whether polygenic scores (PGS) are associated with mood disorder onset independent of familial high risk for BD (FHR-BD) and early psychopathology. Design, Setting, and Participants: This cohort study used data from 7 prospective cohorts enriched in FHR-BD from Australia, Canada, the Netherlands, Spain, and the US. Participants with FHR-BD, defined as having at least 1 first-degree relative with BD, were compared with participants without FHR for any mood disorder. Participants were repeatedly assessed with variable follow-up intervals from July 1992 to July 2023. Data were analyzed from August 2023 to August 2024. Exposures: PGS indexed genetic liability for MDD, BD, anxiety, neuroticism, subjective well-being, ADHD, self-regulation, and addiction risk factor. Semistructured diagnostic interviews with relatives established FHR-BD. ADHD or anxiety disorder diagnoses before mood disorder onset constituted early psychopathology. Main Outcomes and Measures: The outcome of interest, mood disorder onset, was defined as a consensus-confirmed new diagnosis of MDD or BD. Cox regression examined associations of PGS, FHR-BD, ADHD, and anxiety with mood disorder onset. Kaplan-Meier curves and log-rank tests evaluated the probability of onset by PGS quartile and familial risk status. Results: A total of 1064 participants (546 [51.3%] female; mean [SD] age at last assessment, 21.7 [5.1] years), including 660 with FHR-BD and 404 without FHR for any mood disorder, were repeatedly assessed for mental disorders. A total of 399 mood disorder onsets occurred over a variable mean (SD) follow-up interval of 6.3 (5.7) years. Multiple PGS were associated with onset after correcting for FHR-BD and early psychopathology, including PGS for ADHD (hazard ratio [HR], 1.19; 95% CI, 1.06-1.34), self-regulation (HR, 1.19; 95% CI, 1.06-1.34), neuroticism (HR, 1.18; 95% CI, 1.06-1.32), MDD (HR, 1.17; 95% CI, 1.04-1.31), addiction risk factor (HR, 1.16; 95% CI, 1.04-1.30), anxiety (HR, 1.15; 95% CI, 1.02-1.28), BD (HR, 1.14; 95% CI, 1.02-1.28), and subjective well-being (HR, 0.89; 95% CI, 0.79-0.99). High PGS for addiction risk factor, anxiety, BD, and MDD were associated with increased probability of onset in the control group. High PGS for ADHD and self-regulation increased rates of onset among participants with FHR-BD. PGS for self-regulation, ADHD, and addiction risk factors showed stronger associations with onsets of BD than MDD. Conclusions and Relevance: In this cohort study, multiple PGS were associated with mood disorder onset independent of family history of BD and premorbid diagnoses of ADHD or anxiety. The association between PGS and mood disorder risk varied depending on family history status.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".