The Causal Relationships Between Extrinsic Exposures and Risk of Prostate Cancer: A Phenome-Wide Mendelian Randomization Study
Bibliographic record
Abstract
Background Prostate cancer is the second most common cancer in males worldwide, and multitudes of factors have been reported to be associated with prostate cancer risk. Objectives We aim to conduct the phenome-wide exposed-omics analysis of the risk factors for prostate cancer and verify the causal associations between them. Methods We comprehensively searched published systematic reviews and meta-analyses of cohort studies and conducted another systematic review and meta-analysis of the Mendelian randomization studies investigating the associations between extrinsic exposures and prostate cancer, thus to find all of the potential risk factors for prostate cancer. Then, we launched a phenome-wide two-sample Mendelian randomization analysis to validate the potentially causal relationships using the PRACTICAL consortium and UK Biobank. Results We found a total of 55 extrinsic exposures for prostate cancer risk. The causal effect of 30 potential extrinsic exposures on prostate cancer were assessed, and the results showed docosahexaenoic acid (DHA) [odds ratio (OR)=0.806, 95% confidence interval (CI): 0.661-0.984, p=0.034], insulin-like growth factor binding protein 3 (IGFBP-3) (OR=1.0002, 95%CI: 1.00004-1.0004, p=0.016), systemic lupus erythematosus (SLE) (OR=0.9993, 95%CI: 0.9986-0.99997, p=0.039), and body mass index (BMI) (OR=0.995, 95%CI: 0.990-0.9999, p=0.046) were associated with prostate cancer risk. However, no association was found between the other 26 factors and prostate cancer risk. Conclusions Our study discovered the phenome-wide exposed-omics risk factors profile of prostate cancer, and verified that the IGFBP-3, DHA, BMI, and SLE were causally related to prostate cancer risk. The results may provide new insight into the study of the pathogenesis of prostate cancer.
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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 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".