Analytical and bioanalytical chemistry · 2026
Decoding the urinary metabolome of aromatic amino acid pathways in Alport syndrome.
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Gallou Domniki, Morillas-Armenta Jaime, Fernández-García Miguel, Requena Belen, Angulo Santiago, Begou Olga, Gika Helen, Theodoridis Georgios, Fernández-Juárez Gema, Shabaka Amir, Gradillas Ana, Barbas Coral, González-Ruiz Víctor, Villaseñor Alma
Аннотация
Chronic kidney disease (CKD) has been associated with alterations in plasma-free aromatic amino acids (AAA)-tryptophan (Trp), phenylalanine (Phe), and tyrosine (Tyr)-and some downstream metabolites. However, AAA metabolism comprises a wider set of compounds, including microbiome-derived and sulfate-conjugated metabolites excreted in urine with potential biological implications. Alport syndrome (AS), a genetic condition defined by progressive renal impairment, frequently advances to CKD, suggesting that disturbances in AAA-related metabolism may also be relevant in this disorder. Nevertheless, a comprehensive quantitative method covering AAA-derived metabolites enabling an assessment of their implications in AS has not been established. Here, we introduce a novel method for the quantification of up to 43 AAA-derived metabolites in urine, including sulfated metabolites. The method is based on liquid chromatography coupled to tandem mass spectrometry and includes six deuterated internal standards to achieve reliable quantitation. A pooled healthy urine sample was characterized, and the method was validated in terms of linearity, matrix effect, accuracy, precision and sensitivity. The method was applied to urine samples from AS patients-with CKD and non-CKD-and controls. Significant alterations across groups in the concentrations of metabolites from Trp, Phe, and Tyr pathways were observed, including 4-OH-phenylacetic acid-O-sulfate. Notably, the urinary kynurenic acid (KYNA)/Trp ratio emerged as a potential indicator of renal function, showing a marked increase in AS patients with CKD, consistent with enhanced kynurenine pathway activation. Overall, this analytical platform represents a valuable tool for clinical research and for advancing the understanding of AAA-related metabolic dysregulation in renal diseases.