CAG repeat polymorphisms in KCNN3 (HSKCa3) and PPP2R2B show no association or linkage to schizophrenia
Bibliographic record
Abstract
The purpose of this study was to determine whether genetic linkage or association could be observed between schizophrenia (SZ) and the CAG repeat polymorphisms within the genes KCNN3 (known previously as hSKCa3) and PPP2R2B (linked to Spino-Cerebellar Atrophy 12) in the Xhosa population in South Africa. Neither locus has been studied previously in African populations. The polymorphisms were genotyped in 589 individuals to form samples for Transmission Disequilibrium Test (TDT) analysis (176 unrelated probands, 145 with both parents and 30 with one parent genotyped), linkage analysis (49 families with 54 independent affected sib pairs [ASPs]), and case-control analyses (67 familial cases with a first-degree SZ relative, 101 sporadic cases with no affected first- or second-degree relative, and 90 control cases). No significant differences were found among familial cases, sporadic cases and controls in allele sizes (Kruskal-Wallis tests) or the numbers of alleles with sizes above and below the mean size for each polymorphism. Allele size was not correlated with age of onset (Spearman correlation). No significant evidence for association was observed using TDT analyses for all triads and separately for the familial triads. No significant evidence for linkage was observed for either locus with affected sib pair analysis using the possible triangle method or with Non-Parametric Linkage (NPL) analysis of the multiplex families. In conclusion, no significant evidence for linkage or association with SZ was observed for either polymorphism in this population.
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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 | 0.000 | 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".