A sex-specific genome-wide association study of depression phenotypes in UK Biobank
Bibliographic record
Abstract
Abstract There are marked sex differences in the prevalence, phenotypic presentation and treatment response for major depression. While genome-wide association studies (GWAS) adjust for sex differences, to date, no studies seek to identify sex-specific markers and pathways. In this study, we performed a sex-stratified genome-wide association analysis for broad depression with the UK Biobank total participants ( N = 274,141), including only non-related participants, as well as with males ( N = 127,867) and females ( N = 146,274) separately. Bioinformatics analyses were performed to characterize common and sex-specific markers and associated processes/pathways. We identified 11 loci passing genome-level significance ( P < 5 × 10 −8 ) in females and one in males. In both males and females, genetic correlations were significant between the broad depression GWA and other psychopathologies; however, correlations with educational attainment and metabolic features including body fat, waist circumference, waist-to-hip ratio and triglycerides were significant only in females. Gene-based analysis showed 147 genes significantly associated with broad depression in the total sample, 64 in the females and 53 in the males. Gene-based analysis revealed “Regulation of Gene Expression” as a common biological process, but suggested sex-specific molecular mechanisms. Finally, sex-specific polygenic risk scores (PRSs) for broad depression outperformed total and the opposite sex PRSs in the prediction of broad major depressive disorder. These findings provide evidence for sex-dependent genetic pathways for clinical depression as well as for health conditions comorbid with depression.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".