Association between<i>COMT Val158Met</i>and psychiatric disorders: A comprehensive meta‐analysis
Bibliographic record
Abstract
Catechol-O-methyltransferase (COMT) Val158Met is widely regarded as potentially important for understanding the genetic etiology of many different psychiatric disorders. The present study appears to be the first comprehensive meta-analysis of COMT genetic association studies to cover all psychiatric disorders for which there were available data, published in any language, and with an emphasis on investigating disorder subtypes (defined clinically or by demographic or other variables). Studies were included if they reported one or more datasets (i.e., some studies examined more than one clinical group) in which there were sufficient information to compute effect sizes. A total of 363 datasets were included, consisting of 56,998 cases and 74,668 healthy controls from case control studies, and 2,547 trios from family based studies. Fifteen disorders were included. Attention-deficit hyperactivity disorder and panic disorder were associated with the Val allele for Caucasian samples. Substance-use disorder, defined by DSM-IV criteria, was associated with the Val allele for Asian samples. Bipolar disorder was associated with the Met allele in Asian samples. Obsessive-compulsive disorder tended to be associated with the Met allele only for males. There was suggestive evidence that the Met allele is associated with an earlier age of onset of schizophrenia. Results suggest pleiotropy and underscore the importance of examining subgroups-defined by variables such as age of onset, sex, ethnicity, and diagnostic system-rather than examining disorders as monolithic constructs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".