P6345Effect of free testosterone levels on cardiovascular outcomes: a Mendelian randomization analysis
Bibliographic record
Abstract
Background: In 2013, over 2.3 million people in the US alone were prescribed a testosterone product, despite controversy surrounding potential adverse cardiovascular effects. Randomized clinical trials (RCT) have been inconclusive in addressing this question, and are likely underpowered to detect effects for less frequent events such as stroke. Purpose: To address this issue, we conducted a Mendelian randomization (MR) analysis of free testosterone to test the causal effect of lifelong elevated testosterone concentration on major adverse cardiovascular events. Methods: A two-sample MR analysis was performed by first identifying genetic variants associated with calculated free testosterone (CFT) in 4,147 participants from the ORIGIN trial. CFT genetic associations were combined with genetic effect on cardiovascular outcomes using publicly available summary association statistics. A CFT genetic risk score (GRS) was further tested for association with cardiovascular outcomes in UK Biobank participants (N=343,725). Results: We first validated our instrument by testing for associations with known effects of testosterone. As expected, the GRS for CFT was associated with decreased body fat mass (β = -0.12 kg per ng/dL increase in CFT; p=0.027) in the UK Biobank. Genetically increased CFT increased risk of cardioembolic stroke (OR = 1.29 per ng/dL; 95% CI = 1.10 to 1.51; p=0.002), but had no effect on coronary artery disease (CAD) or other stroke subtypes. Follow-up analyses using a GRS in UK Biobank participants demonstrated a consistent null effect on CAD, overall stroke, and atrial fibrillation. Cardioembolic stroke was not reported in UK Biobank, but arterial embolism showed a consistent increased risk (OR = 1.47 per ng/dL; 95% CI = 1.08 to 2.00; p=0.013). To further explore the association with embolism, we investigated the effect of CFT on risk factors for thrombosis. Genetically elevated CFT significantly increased platelet counts (β = 1.5E9 cells per L per ng/dL; 95% CI = 0.8 to 2.2; p=9.8E-6).
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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 | 0.058 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".