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Cannet C, Bayat A, Frauendienst-Egger G, Freisinger P, Spraul M, Himmelreich N, Kockaya M, Ahring K, Godejohann M, MacDonald A, Trefz F. Phenylketonuria (PKU) Urinary Metabolomic Phenotype Is Defined by Genotype and Metabolite Imbalance: Results in 51 Early Treated Patients Using Ex Vivo 1H-NMR Analysis. Molecules 2023; 28:4916. [PMID: 37446577 DOI: 10.3390/molecules28134916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/13/2023] [Accepted: 06/14/2023] [Indexed: 07/15/2023] Open
Abstract
Phenylketonuria (PKU) is a rare metabolic disorder caused by mutations in the phenylalanine hydroxylase gene. Depending on the severity of the genetic mutation, medical treatment, and patient dietary management, elevated phenylalanine (Phe) may occur in blood and brain tissues. Research has recently shown that high Phe not only impacts the central nervous system, but also other organ systems (e.g., heart and microbiome). This study used ex vivo proton nuclear magnetic resonance (1H-NMR) analysis of urine samples from PKU patients (mean 14.9 ± 9.2 years, n = 51) to identify the impact of elevated blood Phe and PKU treatment on metabolic profiles. Our results found that 24 out of 98 urinary metabolites showed a significant difference (p < 0.05) for PKU patients compared to age-matched healthy controls (n = 51) based on an analysis of urinary metabolome. These altered urinary metabolites were related to Phe metabolism, dysbiosis, creatine synthesis or intake, the tricarboxylic acid (TCA) cycle, end products of nicotinamide-adenine dinucleotide degradation, and metabolites associated with a low Phe diet. There was an excellent correlation between the metabolome and genotype of PKU patients and healthy controls of 96.7% in a confusion matrix model. Metabolomic investigations may contribute to a better understanding of PKU pathophysiology.
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Affiliation(s)
| | - Allan Bayat
- Kennedy Centre, Center for PKU, 2600 Glostrup, Denmark
| | | | - Peter Freisinger
- Department of Pediatrics, School of Medicine, University of Tübingen, 72074 Tübingen, Germany
| | | | | | - Musa Kockaya
- Private Pediatric Practice, 68307 Mannheim, Germany
| | | | | | - Anita MacDonald
- Dietetic Department, Birmingham Children's Hospital, Birmingham B4 6NH, UK
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Saffari A, Cannet C, Blaschek A, Hahn A, Hoffmann GF, Johannsen J, Kirsten R, Kockaya M, Kölker S, Müller-Felber W, Roos A, Schäfer H, Schara U, Spraul M, Trefz FK, Vill K, Wick W, Weiler M, Okun JG, Ziegler A. 1H-NMR-based metabolic profiling identifies non-invasive diagnostic and predictive urinary fingerprints in 5q spinal muscular atrophy. Orphanet J Rare Dis 2021; 16:441. [PMID: 34670613 PMCID: PMC8527822 DOI: 10.1186/s13023-021-02075-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 10/10/2021] [Indexed: 11/13/2022] Open
Abstract
Background 5q spinal muscular atrophy (SMA) is a disabling and life-limiting neuromuscular disease. In recent years, novel therapies have shown to improve clinical outcomes. Yet, the absence of reliable biomarkers renders clinical assessment and prognosis of possibly already affected newborns with a positive newborn screening result for SMA imprecise and difficult. Therapeutic decisions and stratification of individualized therapies remain challenging, especially in symptomatic children. The aim of this proof-of-concept and feasibility study was to explore the value of 1H-nuclear magnetic resonance (NMR)-based metabolic profiling in identifying non-invasive diagnostic and prognostic urinary fingerprints in children and adolescents with SMA. Results Urine samples were collected from 29 treatment-naïve SMA patients (5 pre-symptomatic, 9 SMA 1, 8 SMA 2, 7 SMA 3), 18 patients with Duchenne muscular dystrophy (DMD) and 444 healthy controls. Using machine-learning algorithms, we propose a set of prediction models built on urinary fingerprints that showed potential diagnostic value in discriminating SMA patients from controls and DMD, as well as predictive properties in separating between SMA types, allowing predictions about phenotypic severity. Interestingly, preliminary results of the prediction models suggest additional value in determining biochemical onset of disease in pre-symptomatic infants with SMA identified by genetic newborn screening and furthermore as potential therapeutic monitoring tool. Conclusions This study provides preliminary evidence for the use of 1H-NMR-based urinary metabolic profiling as diagnostic and prognostic biomarker in spinal muscular atrophy. Supplementary Information The online version contains supplementary material available at 10.1186/s13023-021-02075-x.
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Affiliation(s)
- Afshin Saffari
- Division of Child Neurology and Metabolic Medicine, Center for Child and Adolescent Medicine, Heidelberg University Hospital, Im Neuenheimer Feld 430, 69120, Heidelberg, Germany
| | | | - Astrid Blaschek
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, LMU Hospital, Dr. von Hauner Children's Hospital, Munich, Germany
| | - Andreas Hahn
- Department of Child Neurology, University Hospital Gießen, Gießen, Germany
| | - Georg F Hoffmann
- Division of Child Neurology and Metabolic Medicine, Center for Child and Adolescent Medicine, Heidelberg University Hospital, Im Neuenheimer Feld 430, 69120, Heidelberg, Germany
| | - Jessika Johannsen
- Department of Pediatrics, Neuropediatrics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Romy Kirsten
- NCT Liquidbank, National Center for Tumor Diseases, Heidelberg, Germany
| | | | - Stefan Kölker
- Division of Child Neurology and Metabolic Medicine, Center for Child and Adolescent Medicine, Heidelberg University Hospital, Im Neuenheimer Feld 430, 69120, Heidelberg, Germany
| | - Wolfgang Müller-Felber
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, LMU Hospital, Dr. von Hauner Children's Hospital, Munich, Germany
| | - Andreas Roos
- Department of Neuropediatrics, Developmental Neurology and Social Pediatrics, Centre for Neuromuscular Disorders in Children, Children's University Clinic Essen, University of Duisburg-Essen, Essen, Germany
| | | | - Ulrike Schara
- Department of Neuropediatrics, Developmental Neurology and Social Pediatrics, Centre for Neuromuscular Disorders in Children, Children's University Clinic Essen, University of Duisburg-Essen, Essen, Germany
| | | | - Friedrich K Trefz
- Division of Child Neurology and Metabolic Medicine, Center for Child and Adolescent Medicine, Heidelberg University Hospital, Im Neuenheimer Feld 430, 69120, Heidelberg, Germany
| | - Katharina Vill
- Division of Pediatric Neurology and Developmental Medicine and LMU Center for Children With Medical Complexity, LMU Hospital, Dr. von Hauner Children's Hospital, Munich, Germany
| | - Wolfgang Wick
- Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany
| | - Markus Weiler
- Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jürgen G Okun
- Division of Child Neurology and Metabolic Medicine, Center for Child and Adolescent Medicine, Heidelberg University Hospital, Im Neuenheimer Feld 430, 69120, Heidelberg, Germany
| | - Andreas Ziegler
- Division of Child Neurology and Metabolic Medicine, Center for Child and Adolescent Medicine, Heidelberg University Hospital, Im Neuenheimer Feld 430, 69120, Heidelberg, Germany.
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