To further evaluate causal genes and relevant tissues through which associated variants may be operating, we applied a trans-ancestry transcriptome-wide association study (TWAS) analysis to each phenotype across 49 tissues derived from the GTEx Consortium10. Using a P value threshold Bonferroni-corrected for the total number of genes and tissues within a phenotype, we found 1,167 genes significantly associated with SmkInit, 21 genes with AgeSmk, 203 genes with CigDay, 188 genes with SmkCes and 504 genes with DrnkWk (resulting in 1,705 unique genes across phenotypes; Supplementary Table 6). For each of our five phenotypes, matrix decomposition parallel analysis11 of the per-tissue P value correlation matrix suggested two components: one explaining 53.7–55.2% of the variance in P values, and another explaining 3.5–3.8% of the variance in P values. Similar loading patterns were observed for all phenotypes such that all tissues loaded strongly (all loadings > 0.12) on the first component, suggesting that it represents a general effect across tissues, whereas only brain tissues had strong loadings on the second component (all loadings > 0.12), indicating the importance of brain-specific gene expression effects
