COMT and MAO-A Polymorphisms and Obsessive-Compulsive Disorder: A Family-Based Association Study
Bibliographic record
Abstract
OBJECTIVE: Obsessive-compulsive disorder (OCD) is a common and debilitating psychiatric illness. Although a genetic component contributes to its etiology, no single gene or mechanism has been identified to the OCD susceptibility. The catechol-O-methyltransferase (COMT) and monoamine oxidase A (MAO-A) genes have been investigated in previous OCD studies, but the results are still unclear. More recently, Taylor (2013) in a comprehensive meta-analysis of genetic association studies has identified COMT and MAO-A polymorphisms involved with OCD. In an effort to clarify the role of these two genes in OCD vulnerability, a family-based association investigation was performed as an alternative strategy to the classical case-control design. METHODS: Transmission disequilibrium analyses were performed after genotyping 13 single-nucleotide polymorphisms (eight in COMT and five in MAO-A) in 783 OCD trios (probands and their parents). Four different OCD phenotypes (from narrow to broad OCD definitions) and a SNP x SNP epistasis were also analyzed. RESULTS: OCD, broad and narrow phenotypes,were not associated with any of the investigated COMT and MAO-A polymorphisms. In addition, the analyses of gene-gene interaction did not show significant epistatic influences on phenotype between COMT and MAO-A. CONCLUSIONS: The findings do not support an association between DSM-IV OCD and the variants of COMT or MAO-A. However, results from this study cannot exclude the contribution of these genes in the manifestation of OCD. The evaluation of broader spectrum phenotypes could help to understand the role of these and other genes in the pathophysiology of OCD and its spectrum disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".