Sex-specific pathways among tri-allelic serotonin transporter polymorphism, trait neuroticism and generalized anxiety disorder
Bibliographic record
Abstract
Background: Neuroticism personality trait is recognized as an important endophenotypic predictor of generalized anxiety disorder (GAD). Furthermore, endophenotype-based pathway approaches have recently been shown to have greater advantages for gene-finding strategies than traditional case-control studies. In the present study, in addition to conventional case-control methods, we used pathway analyses to test whether the tri-allelic serotonin transporter promoter polymorphism (combining 5-HTTLPR and rs25531) is associated with risk of GAD through its effects on trait neuroticism. Methods: We included 2236 Han Chinese adults in this study, including 736 patients with GAD and 1500 healthy participants. We genotyped the 5-HTTLPR and rs25531 polymorphisms using the polymerase chain reaction restriction fragment length polymorphism method. We used the Neuroticism scale of the Maudsley Personality Inventory (MPI) short version (MPI-Neuroticism) to measure participants' tendency toward neuroticism. Results: Using endophenotype-based path analyses, we found significant indirect effects of the tri-allelic genotype on risk of GAD, mediated by MPI-Neuroticism in both men and women. Compared to women carrying the S'S' genotype, women carrying the L' allele had higher levels of MPI-Neuroticism, which in turn were associated with higher risk of GAD. Men, however, showed the opposite pattern. Using traditional case-control comparisons, we observed that the effect of tri-allelic genotype on GAD was significant, but only in women. Limitations: Participants were restricted to Han Chinese, and we used only 1 questionnaire to assess neuroticism. Conclusion: These findings are the first to show that the triallelic 5-HTTLPR polymorphism is associated with elevated risk of GAD, and that this effect is mediated via increased trait neuroticism, a sex-dependent risk pathway.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".