Multitissue analysis of absorption, distribution, metabolism, and excretion gene expression: Sex and age effects across human organ systems

Interindividual differences in drug efficacy and safety are driven by variability in the expression of absorption, distribution, metabolism, and excretion (ADME) genes. A comprehensive analysis of 400 ADME-related genes across all available tissues from the Genotype-Tissue Expression v10 RNA-seq data set was conducted to characterize sex- and age-related expression variations. Principal component analysis revealed distinct tissue-specific ADME expression signatures, with the liver showing the highest ADME functional capacity, followed by the small intestine and kidney cortex. Sex-stratified analysis identified 117 ADME genes with significant expression differences (adjusted P < .05), with the digestive system showing numerous differentially expressed genes, predominantly female-biased. Notable sex differences included CYP3A4, CES1, CYP2C19, GSTM1, and various UDP-glucuronosyltransferases (UGTs), which showed a substantial female-biased expression. Age-related analysis across 6 age brackets (20-29 through 70+ years) revealed divergent pathway remodeling: cytochrome P450 enzymes showed consistent age-related declines across tissues, whereas UGT enzymes exhibited substantial increases in the digestive, immune, and urinary systems. Combined sex and age analysis demonstrated that elderly females showed the most pronounced changes, with UGT and transporter expression changing in most tissues relative to young males. This atlas reveals the complex demographic influences on drug metabolism, with female-biased and age-dependent expression changes in clinically important ADME genes, supporting the need for sex- and age-specific dosing strategies in precision medicine. SIGNIFICANT STATEMENT: This study provides a systematic analysis of the sex and age transcriptional differences in drug-metabolizing enzyme and transporter expression across human tissues. These data identify clinically significant demographic variations that may directly inform precision dosing strategies.