Nontargeted urine metabolomic analysis of acute intermittent porphyria reveals novel interactions between bile acids and heme metabolism: New promising biomarkers for the long-term management of patients

• Published in: Journal of inherited metabolic disease
• Main Authors: Lefebvre, Thibaud, Eguether, Thibaut, Thévenot, Etienne, Poli, Antoine, Chu-Van, Emeline, Krasniqi, Pranvera, Schmitt, Caroline, Talbi, Neila, Nicolas, Gaël, Puy, Hervé, Junot, Christophe, Lamazière, Antonin, Castelli, Florence, Gouya, Laurent, Fenaille, François
• Format: Journal Article
• Language: English
• Published: United States 25.10.2024
• Subjects: acute hepatic porphyria; cholic acid; high resolution mass spectrometry; chenodeoxy; bile acid; heme
• ISSN: 0141-8955; 1573-2665; 1573-2665
• DOI: 10.1002/jimd.12809

Acute intermittent porphyria is an inherited error of heme synthesis. The underlying pathophysiology, involving mainly hepatic heme synthesis, is poorly understood despite its occurrence, and the severity of acute porphyria attack is still difficult to control. A better understanding of the interactions between heme synthesis and global metabolism would improve the management of AIP patients. An untargeted metabolomic analysis was performed on the urine of 114 patients with overt AIP and asymptomatic carriers using liquid chromatography coupled to high-resolution mass spectrometry. The collected data were analyzed by combining univariate and multivariate analyses. A total of 239 metabolites were annotated in urine samples by matching chromatographic and mass spectral characteristics with those from our chemical library. Twenty-six metabolites, including porphyrin precursors, intermediates of tryptophan or glycine metabolism and, unexpectedly, bile acids, showed significant concentration differences between the phenotypic groups. Dysregulation of bile acid metabolism was confirmed by targeted quantitative analysis, which revealed an imbalance in favor of hydrophobic bile acids associated with changes in conjugation, which was more pronounced in the severe phenotype. Using a random forest model, the cholic acid/chenodeoxycholic acid ratio enables the differential classification of severe patients from other patients with a diagnostic accuracy of 84%. The analysis of urine samples revealed significant modifications in the metabolome of AIP patients. Alteration in bile acids provides new insights into the pathophysiology of chronic complications, such as primary liver cancer, while also providing new biomarker candidates for predicting the most severe phenotypes.