Association of the <i><scp>ROBO1</scp></i> gene with reading disabilities in a family‐based analysis
Bibliographic record
Abstract
Linkage studies have identified a locus on chromosome 3 as reading disabilities (RD) and speech and sound disorder (SSD) susceptibility region, with both RD and SSD sharing similar phonological processing and phonological memory difficulties. One gene in this region, roundabout homolog 1 (ROBO1), has been indicated as a RD candidate and has shown significant association with measures of phonological memory in a population-based sample. In this study, we conducted a family-based association analysis using two independent samples collected in Toronto and Calgary, Canada. Using the two samples, we tested for association between ROBO1 single nucleotide polymorphisms (SNPs) and RD, along with quantitative measures for reading, spelling and phonological memory. One SNP, rs331142, which was selected based on its correlation with ROBO1 expression in brain tissue, was found to be significantly associated with RD in the Toronto sample with over transmission of the minor C allele (P = 0.001), correlated with low expression. This SNP is located ~200 bp from a putative enhancer and results for a marker within the enhancer, rs12495133, showed evidence for association with the same allele in both the Toronto and Calgary samples (P = 0.005 and P = 0.007). These results support previous associations between ROBO1 and RD, as well as correlation with low gene expression, suggesting a possible mechanism of risk conferred by this gene.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".