Association of ADHD and the <i>Protogenin </i>gene in the chromosome 15q21.3 reading disabilities linkage region
Bibliographic record
Abstract
Twin studies indicate genetic overlap between symptoms of attention deficit hyperactivity disorder (ADHD) and reading disabilities (RD), and linkage studies identify several chromosomal regions possibly containing common susceptibility genes, including the 15q region. Based on a translocation finding and association to two specific alleles, the candidate gene, DYX1C1, has been proposed as the susceptibility gene for RD in 15q. Previously, we tested markers in DYX1C1 for association with ADHD. Although we identified association for haplotypes across the gene, we were unable to replicate the association to the specific alleles reported. Thus, the risk alleles for ADHD are yet to be identified. The susceptibility alleles may be in a remote regulatory element, or DYX1C1 may not be the risk gene. To continue study of 15q, we tested a coding region change in DYX1C1, followed by markers across the gene Protogenin (PRTG) in 253 ADHD nuclear families. PRTG was chosen based on its location and because it is closely related to DCC and Neogenin, two genes known to guide migratory cells and axons during development. The markers in DYX1C1 were not associated to ADHD when analyzed individually; however, six markers in PRTG showed significant association with ADHD as a categorical trait (P = 0.025-0.005). Haplotypes in both genes showed evidence for association. We identified association with ADHD symptoms measured as quantitative traits in PRTG, but no evidence for association with two key components of reading, word identification and decoding was observed. These findings, while preliminary, identify association of ADHD to a gene that potentially plays a role in cell migration and axon growth.
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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 | 0.000 |
| 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".