Heritability of obsessive–compulsive trait dimensions in youth from the general population
Bibliographic record
Abstract
Obsessive-compulsive disorder (OCD) is a heritable childhood-onset psychiatric disorder that may represent the extreme of obsessive-compulsive (OC) traits that are widespread in the general population. We report the heritability of the Toronto Obsessive-Compulsive Scale (TOCS), a new measure designed to assess the complete range of OC traits in youth. We also examined the dimensional nature of the TOCS and the degree to which genetic effects are unique or shared between dimensions. OC traits were measured using the TOCS in 16,718 youth (6-18 years) at a science museum. We conducted a factor analysis to identify OC trait dimensions. We used univariate and multivariate twin models to estimate the heritability of OC trait dimensions in a subset of twins (220 pairs). Six OC dimensions were identified: Cleaning/Contamination, Symmetry/Ordering, Rumination, Superstition, Counting/Checking, and Hoarding. The TOCS total score (74%) and each OC dimension was heritable (30-77%). Hoarding was not highly correlated with other OC dimensions, but did share genetic effects. Shared genetics accounted for most of the shared variance among dimensions, whereas unique environment accounted for the majority of dimension-specific variance. One exception was Hoarding, which had considerable unique genetic factors. A latent trait did not account for the shared variance between dimensions. In conclusion, OC traits and individual OC dimensions were heritable, although the degree of shared and dimension-specific etiological factors varied by dimension. The TOCS may be informative for genetic research of OC traits in youth. Genetic research of OC traits should consider both OC dimension and total trait scores.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".