Adaptive evolution of genes underlying schizophrenia
Bibliographic record
Abstract
Schizophrenia poses an evolutionary-genetic paradox because it exhibits strongly negative fitness effects and high heritability, yet it persists at a prevalence of approximately 1% across all human cultures. Recent theory has proposed a resolution: that genetic liability to schizophrenia has evolved as a secondary consequence of selection for human cognitive traits. This hypothesis predicts that genes increasing the risk of this disorder have been subject to positive selection in the evolutionary history of humans and other primates. We evaluated this prediction using tests for recent selective sweeps in human populations and maximum-likelihood tests for selection during primate evolution. Significant evidence for positive selection was evident using one or both methods for 28 of 76 genes demonstrated to mediate liability to schizophrenia, including DISC1, DTNBP1 and NRG1, which exhibit especially strong and well-replicated functional and genetic links to this disorder. Strong evidence of non-neutral, accelerated evolution was found for DISC1, particularly for exon 2, the only coding region within the schizophrenia-associated haplotype. Additionally, genes associated with schizophrenia exhibited a statistically significant enrichment in their signals of positive selection in HapMap and PAML analyses of evolution along the human lineage, when compared with a control set of genes involved in neuronal activities. The selective forces underlying adaptive evolution of these genes remain largely unknown, but these findings provide convergent evidence consistent with the hypothesis that schizophrenia represents, in part, a maladaptive by-product of adaptive changes during human evolution.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".