Exploring Causal Relationships of Depression and Psoriatic Disease (Psoriatic Arthritis and Psoriasis) Through Mendelian Randomization
Bibliographic record
Abstract
Objectives Previous observational studies have demonstrated an association between PsA and depression (comorbidity). However, whether these associations are causative and reverse causality was not assessed. Mendelian randomization (MR) can assess causality between exposure and an outcome by using genetic instrumental variables. In this study, we perform a bidirectional two-sample MR to explore the complex causal relationship between depression and PsA or psoriasis. Methods The study cohorts (depression, PsA, psoriasis and controls) were identified from the UK or FinnGen biobank. The summary statistics from Genome-wide association studies (GWAS) were extracted from IEU GWAS database. The selection of SNPs was performed by considering the GWAS significance(5e-07), clumping, linkage disequilibrium, and minor allele frequency. The effects alleles were harmonized for exposures and outcomes. Heterogeneity and horizontal pleiotropy analysis were also performed. An inverse variance weighted (IVW) model was used to estimate causality for each IV in this two-sample MR study. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for causal estimations. The MR also was performed in both directions to explore the possibility of reverse causality. Results Patients with depression (170,756), PsA (1553), psoriasis (4510) and controls (147211 to 329433) were analyzed. The number of instrumental variables (SNPs) is presented in Table 1. Although there appeared to be a positive association between depression and PsA and psoriasis, it did not reach statistical significance (OR 1.19, 95% CI 0.87-1.64, p = 0.27) for PsA but a significant causal effect (OR 1.3 (1.08-1.58), p=0.006) for psoriasis. There was no evidence for reverse causation of psoriasis leading to depression (OR 1.0 (0.98-1.02), p=0.82) and significance for reverse causation of PsA leading to depression was significant (OR 1.02 (1.0-1.03), p=0.002). Table 1 Conclusion This study underscores the importance of MR as a powerful tool for establishing causal relationships in rheumatology, which has significant implications for clinical practice. The lack of a significant consistent causal link between depression and PsA suggests that the relationship observed in observational studies may be due to confounding factors and potential bias, however, there appears to be a causal association of depression leading to psoriasis.
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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 | 0.030 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".