Systematic review of genome-wide association studies of anxiety disorders and neuroticism
Bibliographic record
Abstract
To summarise SNP associations identified by genome-wide association studies (GWASs) of anxiety disorders and neuroticism; to appraise the quality of individual studies, and to assess the ancestral diversity of study participants. We searched PubMed, Scopus, PsychInfo and PubPsych for GWASs of anxiety disorders, non-diagnostic traits (such as anxiety sensitivity), and neuroticism, and extracted all SNPs that surpassed genome-wide significance. We graded study quality using Q-genie scores and reviewed the ancestral diversity of included participants. 32 studies met our inclusion criteria. A total of 563 independent significant variants were identified, of which 29 were replicated nominally in independent samples, and 3 were replicated significantly. The studies had good global quality, but many smaller studies were underpowered. Phenotypic heterogeneity for anxiety (and less so for neuroticism) seemed to reflect the complexity of capturing this trait. Ancestral diversity was poor, with 70% of studies including only populations of European ancestry. The functionality of genes identified by GWASs of anxiety and neuroticism deserves further investigation. Future GWASs should have larger sample sizes, more rigorous phenotyping and include more ancestrally diverse population groups.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".