Suggestive linkage of a chromosomal locus on 18p11 to cyclothymic temperament in bipolar disorder families
Bibliographic record
Abstract
Attempts to identify bipolar disorder (BP) genes have only enjoyed limited success. One potential cause for this problem is that the traditional categorical BP phenotypes currently used in genetic linkage studies are not the most informative, efficient, or biologically relevant. An alternative to these strict categorical BP phenotypes is quantitative BP phenotypes. By isolating one aspect of a complex trait such as BP into a simple, intermediate, quantitative trait, genes that contribute to the larger complex trait can be more readily identified. Along these lines, we utilized a temperament-based measure (cyclothymic temperament) as a quantitative, intermediate BP phenotype in linkage analyses and hypothesized that this measure might more efficiently detect loci for BP or temperamental traits that predispose to BP. A total of 158 individuals with temperament data from 28 BP families were used in the linkage analyses. All pedigrees had a proband diagnosed with BPI or BPII and at least two other family members with a mood disorder diagnosis. An 8 cM genome scan was performed and analyzed using MERLIN nonparametric multipoint regression linkage for a cyclothymic temperament trait. The highest overall LOD score was on chromosome 18 (LOD = 2.71, P = 0.0002). Other linkage peaks which may indicate potential regions of interest were found on chromosomes 3 and 7. The temperament-based cyclothymic trait yielded a higher peak LOD score and a lower P-value than analyses using traditional, categorical phenotypes in a separate analysis including these same families.
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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) | 0.004 | 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".