Amygdala and Hippocampal Volumes in Relatives of Patients with Bipolar Disorder: A High—Risk Study
Bibliographic record
Abstract
OBJECTIVE: Bipolar disorders (BD) have a strong genetic underpinning, yet no biological vulnerability markers for BD have yet been identified. To test whether amygdala or hippocampal volumes represent an endophenotype for BD, we measured mesiotemporal volumes in young affected and unaffected relatives of patients with BD (high-risk design). METHOD: High-risk participants (aged 15 to 30 years) were recruited from families multiply affected with BD. They included 20 affected and 26 unaffected offspring of parents with primary mood disorders, matched by age and sex with 31 control subjects without a personal or family history of psychiatric disorders. Amygdala and hippocampal volumes were measured on 1.5 Tesla 3-dimensional anatomical magnetic resonance images using standard methods. RESULTS: We found comparable amygdala and hippocampal volumes among unaffected relatives, affected high-risk patients, and control subjects. The exclusion of 6 medicated patients did not change the results. There were no differences between participants with family history of BD I, compared with participants with family history of BD II, or between subjects with family history of BD with psychotic symptoms, compared with subjects with family history of BD without psychotic symptoms. CONCLUSIONS: Hippocampal and amygdala volume abnormalities were absent in unaffected and affected relatives of patients with BD and thus did not meet criteria for endophenotype.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".