The association of genetic variation in CACNA1C with resting-state functional connectivity in youth bipolar disorder
Bibliographic record
Abstract
BACKGROUND: CACNA1C rs1006737 A allele, identified as a genetic risk variant for bipolar disorder (BD), is associated with anomalous functional connectivity in adults with and without BD. Studies have yet to investigate the association of CACNA1C rs1006737 with resting-state functional connectivity (rsFC) in youth BD. METHODS: Participants included 139 youth with BD-I, -II, or -not otherwise specified, ages 13-20 years, including 27 BD A-carriers, 41 BD non-carriers, 32 healthy controls (HC) A-carriers, and 39 HC non-carriers. Anterior cingulate cortex (ACC), amygdala, and orbitofrontal cortex (OFC) were examined as regions-of-interest in seed-to-voxel analyses. General linear models included main effects of diagnosis and rs1006737, and an interaction term, controlling for age, sex, and race. RESULTS: We observed a main effect of BD diagnosis on rsFC between the right amygdala and the right occipital pole (p = 0.02), and a main effect of rs1006737 genotypes on rsFC between the right OFC and bilateral occipital cortex (p < 0.001). Two significant BD diagnosis-by-CACNA1C rs1006737 interactions were also identified. The A allele was associated with positive rsFC between the right ACC and right amygdala in BD but negative rsFC in HC (p = 0.01), and negative rsFC between the left OFC and left putamen in BD but positive rsFC in HC (p = 0.01). CONCLUSION: This study found that the rs1006737 A allele, identified as a genetic risk variant for BD in adults, was differentially associated with rsFC in youth with BD in regions relevant to emotion, executive function, and reward. Future task-based approaches are warranted to better understand brain connectivity in relation to CACNA1C in BD.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".