We used Mendelian Randomization (MR) to investigate the bidirectional causal relationships between PAU liability and traits that were significantly genetically correlated (p < 6.99 × 10−5). However, all or most of the published traits in recent large GWAS include UKB data. To avoid biases caused by overlapping samples in MR analysis, we only tested the relationship between published traits and AUD (MVP+PGC). For robust causal effect inference, we limited the traits studied to those with more than 10 available instruments (association p < 5 × 10−8). For causality on AUD, 15 exposures were analyzed (Table 2), and for causality from AUD on others, 23 traits were tested. We applied Bonferroni correction for the 38 hypotheses, interpreting p-values < 1.32×10−3 (0.05/38) as significant.
