Genetic and phenotypic overlap of specific obsessive-compulsive and attention-deficit/hyperactive subtypes with Tourette syndrome
Bibliographic record
Abstract
BACKGROUND: The unique phenotypic and genetic aspects of obsessive-compulsive (OCD) and attention-deficit/hyperactivity disorder (ADHD) among individuals with Tourette syndrome (TS) are not well characterized. Here, we examine symptom patterns and heritability of OCD and ADHD in TS families. METHOD: OCD and ADHD symptom patterns were examined in TS patients and their family members (N = 3494) using exploratory factor analyses (EFA) for OCD and ADHD symptoms separately, followed by latent class analyses (LCA) of the resulting OCD and ADHD factor sum scores jointly; heritability and clinical relevance of the resulting factors and classes were assessed. RESULTS: EFA yielded a 2-factor model for ADHD and an 8-factor model for OCD. Both ADHD factors (inattentive and hyperactive/impulsive symptoms) were genetically related to TS, ADHD, and OCD. The doubts, contamination, need for sameness, and superstitions factors were genetically related to OCD, but not ADHD or TS; symmetry/exactness and fear-of-harm were associated with TS and OCD while hoarding was associated with ADHD and OCD. In contrast, aggressive urges were genetically associated with TS, OCD, and ADHD. LCA revealed a three-class solution: few OCD/ADHD symptoms (LC1), OCD & ADHD symptoms (LC2), and symmetry/exactness, hoarding, and ADHD symptoms (LC3). LC2 had the highest psychiatric comorbidity rates (⩾50% for all disorders). CONCLUSIONS: Symmetry/exactness, aggressive urges, fear-of-harm, and hoarding show complex genetic relationships with TS, OCD, and ADHD, and, rather than being specific subtypes of OCD, transcend traditional diagnostic boundaries, perhaps representing an underlying vulnerability (e.g. failure of top-down cognitive control) common to all three disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".