Pharmacometabolomics of ACE Inhibitors in Chronic Kidney Disease: Serum Bile Acids and Gut-Derived Metabolites Predict Antiproteinuric Response

Background: Angiotensin-converting enzyme inhibitors (ACEIs) are first-line therapy for reducing proteinuria and slowing chronic kidney disease (CKD) progression. However, substantial interindividual variability in antiproteinuric response exists, and the underlying metabolic mechanisms remain unclear. This study aimed to identify serum metabolic signatures, particularly bile acids and gut-derived metabolites, that predict ACEI antiproteinuric response using pharmacometabolomics. Methods: A total of 55 non-diabetic CKD patients with overt proteinuria were prospectively enrolled and treated with ramipril for 12 weeks. According to the reduction in urinary protein excretion, patients were classified as responders (≥50% reduction from baseline, n=28) and non-responders (<50% reduction, n=27). Baseline serum samples were analyzed by UHPLC-MS/MS-based untargeted metabolomics. Multivariate analysis (OPLS-DA) and pathway enrichment were performed. Results: A total of 126 differential metabolites were identified (VIP>1.5, p<0.05). Bile acid metabolism and tryptophan-related gut-derived metabolites were the most significantly enriched pathways. Compared with responders, non-responders exhibited significantly elevated serum levels of primary bile acids (cholic acid, chenodeoxycholic acid) and conjugated species (glycocholic acid, taurocholic acid) (all p<0.01). Additionally, gut-derived metabolites including indoxyl sulfate and p-cresyl sulfate, as well as kynurenine/tryptophan ratio, were markedly higher in non-responders (p<0.01). A combined panel of three metabolites (taurocholic acid, indoxyl sulfate, and kynurenine) predicted poor antiproteinuric response with an area under the curve (AUC) of 0.90 (95% CI: 0.82–0.96). Conclusions: Pharmacometabolomics reveals that elevated serum bile acids and gut-derived uremic toxins are associated with reduced ACEI antiproteinuric efficacy in CKD. These metabolic signatures may serve as predictive biomarkers to guide personalized ACEI therapy and highlight the gut-liver-kidney axis in drug response.