Longitudinal Trajectory of Cognition, Brain Morphometry, and Brain Predicted Age in Unaffected First‐Degree Relatives of Patients With Bipolar Disorder
Bibliographic record
Abstract
INTRODUCTION: Prior research suggests structural brain abnormalities and cognitive difficulties in patients with bipolar disorder. Although there is some evidence that similar structural and cognitive changes may also be present in unaffected relatives (UR) of patients with bipolar disorder, it is not known whether they remain static or aggravate over time. In this study, we investigate the longitudinal trajectories of cognition and brain structure in UR. METHODS: Longitudinal neurocognitive and MRI data were acquired at baseline from UR (n = 72) and healthy controls (HC; n = 65) and at 15 (±4) months follow-up (UR n = 32; HC n = 38). The differential trajectories between UR and HC in neurocognitive performance, white matter volume, regional cortical gray matter (GM) volume and thickness, hippocampal and amygdala volumes, and the difference between biological age and age estimated from brain MRI (brainPAD) were investigated using linear mixed models. RESULTS: UR showed subtle impairments in processing speed, which normalized at follow-up to levels comparable to HC. At both time points, UR showed stable enlargement of amygdalae compared to HC. There was a significant group-by-time interaction effect for the GM volume in the left superior temporal gyrus, driven by UR at baseline displaying larger GM volume compared to HC, which normalized over time. There was no significant difference between UR and HC in brainPAD. CONCLUSION: Bilaterally enlarged amygdala and larger temporal GM volume in UR compared to HC may reflect a vulnerability factor for bipolar disorder. Longer follow-up times are needed to elucidate structural predictors of risk of subsequent illness onset.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".