A linkage disequilibrium study of bipolar disorder and microsatellite markers on 22q13
Bibliographic record
Abstract
Bipolar disorder is a major psychiatric disorder characterized by extreme mood states that alternate between mania and depression. Family, twin, and adoption studies indicate a genetic component to the disease, but the etiology is suspected to be complex, with multiple genes contributing to an increased susceptibility to the disorder. We have previously reported a genome scan in which a genome-wide maximum LOD score indicated evidence of linkage at the marker D22S278 at 22q13. This area is of particular interest since it is also implicated in schizophrenia, and thus may harbor a susceptibility gene common to both disorders. In our further efforts to fine map this region, we examined 10 microsatellite markers spanning an interval of 2.3 MB in a set of 142 parent-proband triads. Linkage disequilibrium to illness was tested using the Transmission Disequilibrium Test. Haplotypes were determined and marker-to-marker linkage disequilibrium across the region was examined. D22S281 and D22S685 yielded suggestive evidence of linkage disequilibrium to bipolar disorder (empirical values of 0.023 and 0.036, respectively), but a marker-to-marker analysis indicates that a higher density screen is needed to adequately analyze this region.
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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 | 0.002 |
| 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) | 0.001 | 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".