Risk of Mental Illness in Offspring of Parents With Schizophrenia, Bipolar Disorder, and Major Depressive Disorder: A Meta-Analysis of Family High-Risk Studies
Bibliographic record
Abstract
OBJECTIVE: Offspring of parents with severe mental illness (SMI; schizophrenia, bipolar disorder, major depressive disorder) are at an increased risk of developing mental illness. We aimed to quantify the risk of mental disorders in offspring and determine whether increased risk extends beyond the disorder present in the parent. METHOD: Meta-analyses of absolute and relative rates of mental disorders in offspring of parents with schizophrenia, bipolar disorder, or depression in family high-risk studies published by December 2012. RESULTS: We included 33 studies with 3863 offspring of parents with SMI and 3158 control offspring. Offspring of parents with SMI had a 32% probability of developing SMI (95% CI: 24%-42%) by adulthood (age >20). This risk was more than twice that of control offspring (risk ratio [RR] 2.52; 95% CI 2.08-3.06, P < .001). High-risk offspring had a significantly increased rate of the disorder present in the parent (RR = 3.59; 95% CI: 2.57-5.02, P < .001) and of other types of SMI (RR = 1.92; 95% CI: 1.48-2.49, P < .001). The risk of mood disorders was significantly increased among offspring of parents with schizophrenia (RR = 1.62; 95% CI: 1.02-2.58; P = .042). The risk of schizophrenia was significantly increased in offspring of parents with bipolar disorder (RR = 6.42; 95% CI: 2.20-18.78, P < .001) but not among offspring of parents with depression (RR = 1.71; 95% CI: 0.19-15.16, P = .631). CONCLUSIONS: Offspring of parents with SMI are at increased risk for a range of psychiatric disorders and one third of them may develop a SMI by early adulthood.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.041 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".