Antioxidative Defense Genes and Brain Structure in Youth Bipolar Disorder
Bibliographic record
Abstract
BACKGROUND: Oxidative stress is implicated in the neuropathology of bipolar disorder (BD). We investigated the association of single-nucleotide polymorphisms (SNPs) in the antioxidative genes superoxide dismutase 2 (SOD2) and glutathione peroxidase 3 (GPX3) with structural neuroimaging phenotypes in youth BD. METHODS: SOD2 rs4880 and GPX3 rs3792797 SNP genotypes, along with structural magnetic resonance imaging, were obtained from 147 youth (BD = 75; healthy controls = 72). Images were processed using FreeSurfer, yielding surface area, volume, and thickness values for regions of interest (prefrontal cortex [PFC], caudal anterior cingulate cortex, hippocampus) and for vertex-wise whole-brain analysis. Analyses controlled for age, sex, race, and intracranial volume for volume, area, and thickness analyses. RESULT: Regions of interest analyses revealed diagnosis-by-SOD2 rs4880 interaction effects for caudal anterior cingulate cortex volume and surface area as well as PFC volume; in each case, there was lower volume/area in the BD GG genotype group vs the healthy controls GG genotype group. There was a significant BD diagnosis × GPX3 rs3793797 interaction effect for PFC surface area, where area was lower in the BD A-allele carrier group vs the other genotype groups. Vertex-wise analyses revealed significant interaction effects in frontal, temporal, and parietal regions related to smaller brain structure in the BD SOD2 rs4880 GG group and BD GPX3 rs3793797 A-allele carrier group. CONCLUSION: We found preliminary evidence that SOD2 rs4880 and GPX3 rs3792797 are differentially associated with brain structures in youth with BD in regions that are relevant to BD. Further studies incorporating additional neuroimaging phenotypes and blood levels of oxidative stress markers are warranted.
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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 | 0.000 |
| 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".