Neuropsychological effects of the <i><scp>CSMD1</scp></i> genome‐wide associated schizophrenia risk variant rs10503253
Bibliographic record
Abstract
The single-nucleotide polymorphism (SNP) rs10503253, located within the CUB and Sushi multiple domains-1 (CSMD1) gene on 8p23.2, was recently identified as genome-wide significant for schizophrenia (SZ), but is of unknown function. We investigated the neurocognitive effects of this CSMD1 variant in vivo in patients and healthy participants using behavioral and imaging measures of brain structure and function. We compared carriers and non-carriers of the risk 'A' allele on measures of neuropsychological performance typically impaired in SZ (general cognitive ability, episodic and working memory and attentional control) in independent samples of Irish patients (n = 387) and controls (n = 171) and German patients (205) and controls (n = 533). Across these groups, the risk 'A' allele at CSMD1 was associated with deleterious effects across a number of neurocognitive phenotypes. Specifically, the risk allele was associated with poorer performance on neuropsychological measures of general cognitive ability and memory function but not attentional control. These effects, while significant, were subtle, and varied between samples. Consistent with previous evidence suggesting that CSMD1 may be involved in brain mechanisms related to memory and learning, these data appear to reflect the deleterious effects of the identified 'A' risk allele on neurocognitive function, possibly as part of the mechanism by which CSMD1 is associated with SZ risk.
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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) | 0.001 | 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) | 0.001 | 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".