Genome-Wide Association Study Meta-Analysis of 9619 Cases With Tic Disorders
Bibliographic record
Abstract
BACKGROUND: Despite the significant personal and societal burden of tic disorders (TDs), treatment outcomes remain modest, necessitating a deeper understanding of their etiology. Family history is the biggest known risk factor, and identifying risk genes could accelerate progress in the field. METHODS: Expanding upon previous sample size limitations, we added 4800 new TD cases and 971,560 controls and conducted a genome-wide association study (GWAS) meta-analysis with 9619 cases and 981,048 controls of European ancestry. We attempted to replicate the results in an independent deCODE genetics GWAS (885 TD cases and 310,367 controls). To characterize GWAS findings, we conducted several post-GWAS gene-based and enrichment analyses. RESULTS: ) within MCHR2-AS1 was identified, although it was not replicated. Post-GWAS analyses revealed a 13.8% single nucleotide polymorphism heritability and 3 significant genes: BCL11B, NDFIP2, and RBM26. Common variant risk for TD was enriched within genes preferentially expressed in the cortico-striato-thalamo-cortical circuit (including the putamen, caudate, nucleus accumbens, and Brodmann area 9) and 5 brain cell types (excitatory and inhibitory telencephalon neurons, inhibitory diencephalon and mesencephalon neurons, and hindbrain and medium spiny neurons). TD polygenic risk was enriched within loss-of-function intolerant genes (p = .0017) and high-confidence neurodevelopmental disorder genes (p = .0108). Of 112 genetic correlations, 43 were statistically significant, showing high positive correlations with most psychiatric disorders. Of the 2 single nucleotide polymorphisms previously associated with TDs, one (rs2453763) replicated in an independent subsample of our GWAS (p = .00018). CONCLUSIONS: This GWAS was still underpowered to identify high-confidence, replicable loci, but the results suggest imminent discovery of common genetic variants for TDs.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.020 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".