Bipolar disorder risk gene <i>FOXO6</i> modulates negative symptoms in schizophrenia: a neuroimaging genetics study
Bibliographic record
Abstract
Background: Despite being diagnostically associated uniquely with schizophrenia, negative symptoms are also observed in bipolar disorder (BD). Genome-wide association studies (GWAS) have uncovered a number of shared risk genes between schizophrenia and BD. The objectives of this study were to examine whether previously identified risk genes for BD are associated with negative symptom severity within a first-episode schizophrenia (FES) cohort and to examine whether such genes influence brain morphology. Methods: Patients experiencing FES were genotyped for 21 previously identified BD risk genes; a series of univariate analyses of covariance examined the association between negative symptom severity, as measured using the Scale for the Assessment of Negative Symptoms (SANS), and genotype. A subset of participants underwent a structural 1.5 T MRI T 1 scan, analyzed for surface area and cortical thickness changes via the CIVET pipeline and LPBA40 atlas. Results: We included 133 patients with FES in our analysis; 61 of them underwent structural MRI. We observed a significant association between negative symptom severity and the BD risk gene FOXO6 (rs4660531). Individuals with the CC genotype presented significantly higher negative symptoms (Cohen d = 0.46, F = 5.854, p = 0.017) and significantly smaller surface area within the right middle orbitofrontal gyrus (Cohen d = 0.69, F = 7.289, p = 0.009) than carriers of allele A. Limitations: Limitations of this study include its modest sample size and lack of a control sample. Conclusion: Lacking the FOXO6 risk allele was associated with an increase in negative symptoms and surface area reduction in the right orbitofrontal gyrus — an area previously associated with negative symptoms —– suggesting that presence of the FOXO6 risk allele confers resistance against negative symptoms and associated neuroanatomical changes in individuals with FES.
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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".