THE METABOLOMICS SIGNATURE ASSOCIATED WITH RESPONSIVENESS TO STEROID THERAPY IN FOCAL SEGMENTAL GLOMERULOSCLEROSIS: A PILOT STUDY.

BACKGROUND: Focal segmental glomerulosclerosis (FSGS) is considered one of the most severe glomerular diseases and around 80% of cases are resistant to steroid treatment. Since a large proportion of steroid-resistant (SR) FSGS patients progress to end-stage renal disease, other therapeutic strategies may benefit this population. However, identification of non-invasive biomarkers to predict this high-risk population is needed. OBJECTIVE: We aimed to identify the biomarker candidates to distinguish SR from steroid-sensitive (SS) patients using metabolomics approach and to identify the possible molecular mechanism of resistance. METHODS: Urine was collected from biopsy-proven FSGS patients eligible for monotherapy with prednisolone. Patients were followed for 6-8 weeks and categorized as SS or SR. Metabolite profile of urine samples was analyzed by one-dimensional 1H-nuclear magnetic resonance (1H-NMR). Predictive biomarker candidates and their diagnostic importance impaired molecular pathways in SR patients, and the common target molecules between biomarker candidates and drug were predicted. RESULTS: Homovanillic acid, 4-methylcatechol, and tyrosine were suggested as the significant predictive biomarker candidates, while L-3,4-dihydroxyphenylalanine, norepinephrine, and gentisic acid had high accuracy as well. Tyrosine metabolism was the most important pathway that is perturbed in SR patients. Common targets of the action of biomarker candidates and prednisolone were molecules that contributed in apoptosis. CONCLUSION: Urine metabolites including homovanillic acid, 4-methylcatechol, and tyrosine may serve as potential non-invasive predictive biomarkers for evaluating the responsiveness of FSGS patients.

The metabolomics signature associated with responsiveness to steroid therapy in focal segmental glomerulosclerosis: a pilot study

Abstract Background Focal segmental glomerulosclerosis (FSGS) is considered one of the most severe glomerular diseases and around 80% of cases are resistant to steroid treatment. Since a large proportion of steroid-resistant (SR) FSGS patients progress to end-stage renal disease, other therapeutic strategies may benefit this population. However, identification of non-invasive biomarkers to predict this high-risk population is needed. Objective We aimed to identify the biomarker candidates to distinguish SR from steroid-sensitive (SS) patients using metabolomics approach and to identify the possible molecular mechanism of resistance. Methods Urine was collected from biopsy-proven FSGS patients eligible for monotherapy with prednisolone. Patients were followed for 6-8 weeks and categorized as SS or SR. Metabolite profile of urine samples was analyzed by one-dimensional 1H-nuclear magnetic resonance (1H-NMR). Predictive biomarker candidates and their diagnostic importance impaired molecular pathways in SR patients, and the common target molecules between biomarker candidates and drug were predicted. Results Homovanillic acid, 4-methylcatechol, and tyrosine were suggested as the significant predictive biomarker candidates, while L-3,4-dihydroxyphenylalanine, norepinephrine, and gentisic acid had high accuracy as well. Tyrosine metabolism was the most important pathway that is perturbed in SR patients. Common targets of the action of biomarker candidates and prednisolone were molecules that contributed in apoptosis. Conclusion Urine metabolites including homovanillic acid, 4-methylcatechol, and tyrosine may serve as potential non-invasive predictive biomarkers for evaluating the responsiveness of FSGS patients.