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Simultaneously, the metabolomic fingerprint of chronic kidney disease (CKD) is often associated with underlying mitochondrial dysfunction. This study aimed to characterize urinary metabolic signatures in genetically confirmed paediatric PMD without chronic kidney disease, comparing them to healthy controls, suspected (unconfirmed) mitochondrial disease (SMD), and non-mitochondrial CKD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We performed untargeted\n                      <jats:sup>1<\/jats:sup>\n                      H NMR metabolomic profiling of 76 urine samples from 51 paediatric patients and 10 healthy controls. PMD patients in acute decompensation or known CKD and statistical outlier samples were excluded. Final comparisons included genetically confirmed PMD without CKD (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200913), SMD (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200910), non-mitochondrial CKD (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200928; 17 at stages 1\u20132 and 9 at stages 3\u20135), and healthy controls (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200910). Spectral data were analyzed using multivariate statistical approaches\u2014including principal component analysis (PCA) and partial least squares\u2013discriminant analysis (PLS-DA)\u2014as well as univariate methods with Mann-Whitney U for pairwise group metabolite comparison.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Urinary metabolic profiles of PMD patients differed from healthy controls and CKD patients. Multivariate analysis revealed a strong discriminative ability between PMD and controls (Q\u00b2 = 0.53) and advanced CKD (Q\n                      <jats:sup>2<\/jats:sup>\n                      \u2009=\u20090.78). Compared to controls, PMD patients had increased levels of Krebs cycle intermediates (\n                      <jats:italic>cis<\/jats:italic>\n                      -aconitate, fumarate and succinate), creatine, tryptophan, homovanillate (HVA) and hypoxanthine, as well as decreased histidine. All, except fumarate and histidine, remained discriminative when comparing PMD to CKD. CKD patients showed a diverging metabolomic fingerprint with 1-methylnicotinamide (MNA) and 2-hydroxyisobutyrate emerging as potential CKD-specific biomarkers, effectively discriminating between CKD stage 3\u20135 from earlier stages and controls. A five-metabolite panel comprising\n                      <jats:italic>cis<\/jats:italic>\n                      -aconitate, fumarate, HVA, tryptophan and histidine achieved high diagnostic performance for identifying PMD, with an area under the curve (AUC) of 0.836 (PMD vs. controls) and AUC\u2009=\u20090.783 across all groups. This biosignature integrates metabolites involved in distinct functional domains including energy metabolism, neurotransmitter turnover and amino acid metabolism and renal handling.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Urinary metabolomic profiling by NMR revealed a distinct biosignature in pediatric PMD patients without renal involvement, characterized by elevated levels of tryptophan, HVA, and Krebs cycle intermediates, and diminished histidine. The divergent changes in tryptophan, histidine and HVA, suggest a mitochondria-specific metabolic phenotype in PMD. These findings support the use of urinary NMR metabolomics as a non-invasive tool for biomarker discovery in PMD and highlight the potential of integrated, multiparametric metabolic fingerprints for diagnostic refinement and patient stratification.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s11306-025-02363-8","type":"journal-article","created":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T00:13:38Z","timestamp":1768781618000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["NMR-based urinary biomarkers in pediatric primary mitochondrial disorders and chronic kidney disease: shared mitochondrial dysfunction, diverging biosignatures"],"prefix":"10.1007","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6471-4067","authenticated-orcid":false,"given":"Margarida","family":"Paiva Coelho","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8621-5410","authenticated-orcid":false,"given":"Jo\u00e3o E.","family":"Rodrigues","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6478-4241","authenticated-orcid":false,"given":"Teresa","family":"Costa","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1629-3755","authenticated-orcid":false,"given":"Aureliano","family":"Dias","sequence":"additional","affiliation":[]},{"given":"In\u00eas C. 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