Evolutionary genomics of human intellectual disability
Bibliographic record
Abstract
Previous studies have postulated that X-linked and autosomal genes underlying human intellectual disability may have also mediated the evolution of human cognition. We have conducted the first comprehensive assessment of the extent and patterns of positive Darwinian selection on intellectual disability genes in humans. We report three main findings. First, as noted in some previous reports, intellectual disability genes with primary functions in the central nervous system exhibit a significant concentration to the X chromosome. Second, there was no evidence for a higher incidence of recent positive selection on X-linked than autosomal intellectual disability genes, nor was there a higher incidence of selection on such genes overall, compared to sets of control genes. However, the X-linked intellectual disability genes inferred to be subject to recent positive selection were concentrated in the Rho GTP-ase pathway, a key signaling pathway in neural development and function. Third, among all intellectual disability genes, there was evidence for a higher incidence of recent positive selection on genes involved in DNA repair, but not for genes involved in other functions. These results provide evidence that alterations to genes in the Rho GTP-ase and DNA-repair pathways may play especially-important roles in the evolution of human cognition and vulnerability to genetically-based intellectual disability.
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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 | 0.001 | 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".