Understanding Brain Transcriptome Signatures Associated with Disparate Psychiatric Outcomes in Black American Populations
Bibliographic record
Abstract
The molecular basis underlying disparate schizophrenia (SCZ) outcomes remains unclear, but stress and immune pathways associated with social inequalities are thought to contribute. To address questions about race-specific effects on the brain and in SCZ, I analyzed post-mortem DLPFC RNA-seq data from two racially diverse cohorts in the CommonMind Consortium (235 Black and 546 White; 322 SCZ and 459 controls). Mega-analyses yielded 1514 genes with differential expression (DE) between Black and White-reported individuals and enrichments implicated upregulation in stress and immune pathways in Black individuals. Interaction models showed 109 gene sets DE in a race-specific manner across SCZ, and semantic clustering revealed these sets implicated metabolic and immune pathways. Our results support a molecular mechanism underpinning racial differences in SCZ outcomes involving immune and stress pathways and underscore the importance of diverse cohort ascertainment to capture the diversity of SCZ pathogenesis.
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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 | 0.000 |
| 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) | 0.002 | 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".