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Kernohan KD, Boycott KM. The expanding diagnostic toolbox for rare genetic diseases. Nat Rev Genet 2024; 25:401-415. [PMID: 38238519 DOI: 10.1038/s41576-023-00683-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/22/2023] [Indexed: 05/23/2024]
Abstract
Genomic technologies, such as targeted, exome and short-read genome sequencing approaches, have revolutionized the care of patients with rare genetic diseases. However, more than half of patients remain without a diagnosis. Emerging approaches from research-based settings such as long-read genome sequencing and optical genome mapping hold promise for improving the identification of disease-causal genetic variants. In addition, new omic technologies that measure the transcriptome, epigenome, proteome or metabolome are showing great potential for variant interpretation. As genetic testing options rapidly expand, the clinical community needs to be mindful of their individual strengths and limitations, as well as remaining challenges, to select the appropriate diagnostic test, correctly interpret results and drive innovation to address insufficiencies. If used effectively - through truly integrative multi-omics approaches and data sharing - the resulting large quantities of data from these established and emerging technologies will greatly improve the interpretative power of genetic and genomic diagnostics for rare diseases.
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Affiliation(s)
- Kristin D Kernohan
- CHEO Research Institute, University of Ottawa, Ottawa, ON, Canada
- Newborn Screening Ontario, CHEO, Ottawa, ON, Canada
| | - Kym M Boycott
- CHEO Research Institute, University of Ottawa, Ottawa, ON, Canada.
- Department of Genetics, CHEO, Ottawa, ON, Canada.
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2
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Li JW, Mao SJ, Chao YQ, Hu CX, Qian YJ, Dai YL, Huang K, Shen Z, Zou CC. Application of tandem mass spectrometry in the screening and diagnosis of mucopolysaccharidoses. Orphanet J Rare Dis 2024; 19:179. [PMID: 38685110 PMCID: PMC11059687 DOI: 10.1186/s13023-024-03195-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 04/19/2024] [Indexed: 05/02/2024] Open
Abstract
Mucopolysaccharidoses (MPSs) are caused by a deficiency in the enzymes needed to degrade glycosaminoglycans (GAGs) in the lysosome. The storage of GAGs leads to the involvement of several systems and even to the death of the patient. In recent years, an increasing number of therapies have increased the treatment options available to patients. Early treatment is beneficial in improving the prognosis, but children with MPSs are often delayed in their diagnosis. Therefore, there is an urgent need to develop a method for early screening and diagnosis of the disease. Tandem mass spectrometry (MS/MS) is an analytical method that can detect multiple substrates or enzymes simultaneously. GAGs are reliable markers of MPSs. MS/MS can be used to screen children at an early stage of the disease, to improve prognosis by treating them before symptoms appear, to evaluate the effectiveness of treatment, and for metabolomic analysis or to find suitable biomarkers. In the future, MS/MS could be used to further identify suitable biomarkers for MPSs for early diagnosis and to detect efficacy.
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Affiliation(s)
- Jing-Wen Li
- Department of Endocrinology, the Children's Hospital of Zhejiang University School of Medicine, Hangzhou, 310052, China
| | - Shao-Jia Mao
- Department of Endocrinology, the Children's Hospital of Zhejiang University School of Medicine, Hangzhou, 310052, China
| | - Yun-Qi Chao
- Department of Endocrinology, the Children's Hospital of Zhejiang University School of Medicine, Hangzhou, 310052, China
| | - Chen-Xi Hu
- Department of Endocrinology, the Children's Hospital of Zhejiang University School of Medicine, Hangzhou, 310052, China
| | - Yan-Jie Qian
- Department of Endocrinology, the Children's Hospital of Zhejiang University School of Medicine, Hangzhou, 310052, China
| | - Yang-Li Dai
- Department of Endocrinology, the Children's Hospital of Zhejiang University School of Medicine, Hangzhou, 310052, China
| | - Ke Huang
- Department of Endocrinology, the Children's Hospital of Zhejiang University School of Medicine, Hangzhou, 310052, China
| | - Zheng Shen
- Lab Center, the Children's Hospital of Zhejiang University School of Medicine, Hangzhou, 310052, China
| | - Chao-Chun Zou
- Department of Endocrinology, the Children's Hospital of Zhejiang University School of Medicine, Hangzhou, 310052, China.
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3
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Wurth R, Turgeon C, Stander Z, Oglesbee D. An evaluation of untargeted metabolomics methods to characterize inborn errors of metabolism. Mol Genet Metab 2024; 141:108115. [PMID: 38181458 PMCID: PMC10843816 DOI: 10.1016/j.ymgme.2023.108115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 11/19/2023] [Accepted: 12/12/2023] [Indexed: 01/07/2024]
Abstract
Inborn errors of metabolism (IEMs) encompass a diverse group of disorders that can be difficult to classify due to heterogenous clinical, molecular, and biochemical manifestations. Untargeted metabolomics platforms have become a popular approach to analyze IEM patient samples because of their ability to detect many metabolites at once, accelerating discovery of novel biomarkers, and metabolic mechanisms of disease. However, there are concerns about the reproducibility of untargeted metabolomics research due to the absence of uniform reporting practices, data analyses, and experimental design guidelines. Therefore, we critically evaluated published untargeted metabolomic platforms used to characterize IEMs to summarize the strengths and areas for improvement of this technology as it progresses towards the clinical laboratory. A total of 96 distinct IEMs were collectively evaluated by the included studies. However, most of these IEMs were evaluated by a single untargeted metabolomic method, in a single study, with a limited cohort size (55/96, 57%). The goals of the included studies generally fell into two, often overlapping, categories: detecting known biomarkers from many biochemically distinct IEMs using a single platform, and detecting novel metabolites or metabolic pathways. There was notable diversity in the design of the untargeted metabolomic platforms. Importantly, the majority of studies reported adherence to quality metrics, including the use of quality control samples and internal standards in their experiments, as well as confirmation of at least some of their feature annotations with commercial reference standards. Future applications of untargeted metabolomics platforms to the study of IEMs should move beyond single-subject analyses, and evaluate reproducibility using a prospective, or validation cohort.
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Affiliation(s)
- Rachel Wurth
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, 200 1(st) St SW, Rochester, MN 55905, USA
| | - Coleman Turgeon
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905, USA
| | - Zinandré Stander
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905, USA
| | - Devin Oglesbee
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905, USA.
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Torres CL, Scalco FB, de Oliveira MLC, Peake RWA, Garrett R. Untargeted LC-HRMS metabolomics reveals candidate biomarkers for mucopolysaccharidoses. Clin Chim Acta 2023; 541:117250. [PMID: 36764508 DOI: 10.1016/j.cca.2023.117250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 12/19/2022] [Accepted: 02/06/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND Mucopolysaccharidoses (MPSs) are inherited genetic diseases caused by an absence or deficiency of lysosomal enzymes responsible for catabolizing glycosaminoglycans (GAGs). Undiagnosed patients, or those without adequate treatment in early life, can be severely and irreversibly affected by the disease. In this study, we applied liquid chromatography-high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics to identify potential biomarkers for MPS disorders to better understand how MPS may affect the metabolome of patients. METHODS Urine samples from 37 MPS patients (types I, II, III, IV, and VI; untreated and treated with enzyme replacement therapy (ERT)) and 38 controls were analyzed by LC-HRMS. Data were processed by an untargeted metabolomics workflow and submitted to multivariate statistical analyses to reveal significant differences between the MPS and control groups. RESULTS A total of 12 increased metabolites common to all MPS types were identified. Dipeptides, amino acids and derivatives were increased in the MPS group compared to controls. N-acetylgalactosamines 4- or 6-sulfate, important constituents of GAGs, were also elevated in MPS patients, most prominently in those with MPS VI. Notably, treated patients exhibited lower levels of the aforementioned acylaminosugars than untreated patients in all MPS types. CONCLUSIONS Untargeted metabolomics has enabled the detection of metabolites that could improve our understanding of MPS physiopathology. These potential biomarkers can be utilized in screening methods to support diagnosis and ERT monitoring.
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Affiliation(s)
- Clarisse L Torres
- Metabolomics Laboratory, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Fernanda B Scalco
- Inborn Error of Metabolism Laboratory, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Maria Lúcia C de Oliveira
- Inborn Error of Metabolism Laboratory, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Roy W A Peake
- Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Rafael Garrett
- Metabolomics Laboratory, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil; Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
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Hertzog A, Selvanathan A, Devanapalli B, Ho G, Bhattacharya K, Tolun AA. A narrative review of metabolomics in the era of "-omics": integration into clinical practice for inborn errors of metabolism. Transl Pediatr 2022; 11:1704-1716. [PMID: 36345452 PMCID: PMC9636448 DOI: 10.21037/tp-22-105] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 08/23/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND AND OBJECTIVE Traditional targeted metabolomic investigations identify a pre-defined list of analytes in samples and have been widely used for decades in the diagnosis and monitoring of inborn errors of metabolism (IEMs). Recent technological advances have resulted in the development and maturation of untargeted metabolomics: a holistic, unbiased, analytical approach to detecting metabolic disturbances in human disease. We aim to provide a summary of untargeted metabolomics [focusing on tandem mass spectrometry (MS-MS)] and its application in the field of IEMs. METHODS Data for this review was identified through a literature search using PubMed, Google Scholar, and personal repositories of articles collected by the authors. Findings are presented within several sections describing the metabolome, the current use of targeted metabolomics in the diagnostic pathway of patients with IEMs, the more recent integration of untargeted metabolomics into clinical care, and the limitations of this newly employed analytical technique. KEY CONTENT AND FINDINGS Untargeted metabolomic investigations are increasingly utilized in screening for rare disorders, improving understanding of cellular and subcellular physiology, discovering novel biomarkers, monitoring therapy, and functionally validating genomic variants. Although the untargeted metabolomic approach has some limitations, this "next generation metabolic screening" platform is becoming increasingly affordable and accessible. CONCLUSIONS When used in conjunction with genomics and the other promising "-omic" technologies, untargeted metabolomics has the potential to revolutionize the diagnostics of IEMs (and other rare disorders), improving both clinical and health economic outcomes.
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Affiliation(s)
- Ashley Hertzog
- NSW Biochemical Genetics Service, The Children's Hospital at Westmead, Westmead, NSW, Australia
| | - Arthavan Selvanathan
- Genetic Metabolic Disorders Service, The Children's Hospital at Westmead, Westmead, NSW, Australia
| | - Beena Devanapalli
- NSW Biochemical Genetics Service, The Children's Hospital at Westmead, Westmead, NSW, Australia
| | - Gladys Ho
- Sydney Genome Diagnostics, The Children's Hospital at Westmead, Westmead, NSW, Australia.,Specialty of Genomic Medicine, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Kaustuv Bhattacharya
- Genetic Metabolic Disorders Service, The Children's Hospital at Westmead, Westmead, NSW, Australia.,Specialty of Genomic Medicine, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Adviye Ayper Tolun
- NSW Biochemical Genetics Service, The Children's Hospital at Westmead, Westmead, NSW, Australia.,Specialty of Genomic Medicine, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
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Paglia G, Smith AJ, Astarita G. Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics. MASS SPECTROMETRY REVIEWS 2022; 41:722-765. [PMID: 33522625 DOI: 10.1002/mas.21686] [Citation(s) in RCA: 84] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 01/17/2021] [Accepted: 01/17/2021] [Indexed: 06/12/2023]
Abstract
Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.
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Affiliation(s)
- Giuseppe Paglia
- School of Medicine and Surgery, University of Milano-Bicocca, Vedano al Lambro (MB), Italy
| | - Andrew J Smith
- School of Medicine and Surgery, University of Milano-Bicocca, Vedano al Lambro (MB), Italy
| | - Giuseppe Astarita
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington, District of Columbia, USA
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Rocchetti MT, Spadaccino F, Catalano V, Zaza G, Stallone G, Fiocco D, Netti GS, Ranieri E. Metabolic Fingerprinting of Fabry Disease: Diagnostic and Prognostic Aspects. Metabolites 2022; 12:metabo12080703. [PMID: 36005574 PMCID: PMC9415061 DOI: 10.3390/metabo12080703] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/21/2022] [Accepted: 07/22/2022] [Indexed: 11/16/2022] Open
Abstract
Fabry disease (FD) is an X-linked lysosomal disease due to a deficiency in the activity of the lysosomal-galactosidase A (GalA), a key enzyme in the glycosphingolipid degradation pathway. FD is a complex disease with a poor genotype–phenotype correlation. In the early stages, FD could involve the peripheral nervous system (acroparesthesias and dysautonomia) and the ski (angiokeratoma), but later kidney, heart or central nervous system impairment may significantly decrease life expectancy. The advent of omics technologies offers the possibility of a global, integrated and systemic approach well-suited for the exploration of this complex disease. In this narrative review, we will focus on the main metabolomic studies, which have underscored the importance of detecting biomarkers for a diagnostic and prognostic purpose in FD. These investigations are potentially useful to explain the wide clinical, biochemical and molecular heterogeneity found in FD patients. Moreover, the quantitative mass spectrometry methods developed to evaluate concentrations of these biomarkers in urine and plasma will be described. Finally, the complex metabolic biomarker profile depicted in FD patients will be reported, which varies according to gender, types of mutations, and therapeutic treatment.
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Affiliation(s)
- Maria Teresa Rocchetti
- Department of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy; (M.T.R.); (D.F.)
| | - Federica Spadaccino
- Unit of Clinical Pathology, Center for Molecular Medicine, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy; (F.S.); (V.C.); (E.R.)
| | - Valeria Catalano
- Unit of Clinical Pathology, Center for Molecular Medicine, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy; (F.S.); (V.C.); (E.R.)
| | - Gianluigi Zaza
- Unit of Nephology, Dialysis and Transplantation, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy; (G.Z.); (G.S.)
| | - Giovanni Stallone
- Unit of Nephology, Dialysis and Transplantation, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy; (G.Z.); (G.S.)
| | - Daniela Fiocco
- Department of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy; (M.T.R.); (D.F.)
| | - Giuseppe Stefano Netti
- Unit of Clinical Pathology, Center for Molecular Medicine, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy; (F.S.); (V.C.); (E.R.)
- Correspondence: ; Tel.: +39-0881-732619
| | - Elena Ranieri
- Unit of Clinical Pathology, Center for Molecular Medicine, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy; (F.S.); (V.C.); (E.R.)
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Understanding Inborn Errors of Metabolism through Metabolomics. Metabolites 2022; 12:metabo12050398. [PMID: 35629902 PMCID: PMC9143820 DOI: 10.3390/metabo12050398] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 04/14/2022] [Accepted: 04/25/2022] [Indexed: 12/10/2022] Open
Abstract
Inborn errors of metabolism (IEMs) are rare diseases caused by a defect in a single enzyme, co-factor, or transport protein. For most IEMs, no effective treatment is available and the exact disease mechanism is unknown. The application of metabolomics and, more specifically, tracer metabolomics in IEM research can help to elucidate these disease mechanisms and hence direct novel therapeutic interventions. In this review, we will describe the different approaches to metabolomics in IEM research. We will discuss the strengths and weaknesses of the different sample types that can be used (biofluids, tissues or cells from model organisms; modified cell lines; and patient fibroblasts) and when each of them is appropriate to use.
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10
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Ducatez F, Mauhin W, Boullier A, Pilon C, Pereira T, Aubert R, Benveniste O, Marret S, Lidove O, Bekri S, Tebani A. Parsing Fabry Disease Metabolic Plasticity Using Metabolomics. J Pers Med 2021; 11:jpm11090898. [PMID: 34575675 PMCID: PMC8468728 DOI: 10.3390/jpm11090898] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Revised: 09/03/2021] [Accepted: 09/05/2021] [Indexed: 12/12/2022] Open
Abstract
Background: Fabry disease (FD) is an X-linked lysosomal disease due to a deficiency in the activity of the lysosomal α-galactosidase A (GalA), a key enzyme in the glycosphingolipid degradation pathway. FD is a complex disease with a poor genotype–phenotype correlation. FD could involve kidney, heart or central nervous system impairment that significantly decreases life expectancy. The advent of omics technologies offers the possibility of a global, integrated and systemic approach well-suited for the exploration of this complex disease. Materials and Methods: Sixty-six plasmas of FD patients from the French Fabry cohort (FFABRY) and 60 control plasmas were analyzed using liquid chromatography and mass spectrometry-based targeted metabolomics (188 metabolites) along with the determination of LysoGb3 concentration and GalA enzymatic activity. Conventional univariate analyses as well as systems biology and machine learning methods were used. Results: The analysis allowed for the identification of discriminating metabolic profiles that unambiguously separate FD patients from control subjects. The analysis identified 86 metabolites that are differentially expressed, including 62 Glycerophospholipids, 8 Acylcarnitines, 6 Sphingomyelins, 5 Aminoacids and 5 Biogenic Amines. Thirteen consensus metabolites were identified through network-based analysis, including 1 biogenic amine, 2 lysophosphatidylcholines and 10 glycerophospholipids. A predictive model using these metabolites showed an AUC-ROC of 0.992 (CI: 0.965–1.000). Conclusion: These results highlight deep metabolic remodeling in FD and confirm the potential of omics-based approaches in lysosomal diseases to reveal clinical and biological associations to generate pathophysiological hypotheses.
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Affiliation(s)
- Franklin Ducatez
- Department of Metabolic Biochemistry, Normandie University, UNIROUEN, INSERM U1245, CHU Rouen, 76000 Rouen, France; (F.D.); (C.P.); (R.A.); (S.B.)
- Department of Neonatal Pediatrics, Intensive Care, and Neuropediatrics, Normandie University, UNIROUEN, INSERM U1245, CHU Rouen, 76000 Rouen, France;
| | - Wladimir Mauhin
- Department of Internal Medicine, Groupe Hospitalier Diaconesses Croix Saint Simon, Site Avron & UMRS 974, 75013 Paris, France; (W.M.); (O.L.)
| | - Agnès Boullier
- MP3CV-UR7517, CURS-Université de Picardie Jules Verne, Avenue de la Croix Jourdain, 80054 Amiens, France;
- Laboratoire de Biochimie CHU Amiens-Picardie, Avenue de la Croix Jourdain, 80054 Amiens, France
| | - Carine Pilon
- Department of Metabolic Biochemistry, Normandie University, UNIROUEN, INSERM U1245, CHU Rouen, 76000 Rouen, France; (F.D.); (C.P.); (R.A.); (S.B.)
| | - Tony Pereira
- CHU Rouen, Institut de Biologie Clinique, 76000 Rouen, France;
| | - Raphaël Aubert
- Department of Metabolic Biochemistry, Normandie University, UNIROUEN, INSERM U1245, CHU Rouen, 76000 Rouen, France; (F.D.); (C.P.); (R.A.); (S.B.)
| | - Olivier Benveniste
- Department of Internal Medicine, Hôpital Pitié-Salpêtrière & INSERM U 974, 75013 Paris, France;
| | - Stéphane Marret
- Department of Neonatal Pediatrics, Intensive Care, and Neuropediatrics, Normandie University, UNIROUEN, INSERM U1245, CHU Rouen, 76000 Rouen, France;
| | - Olivier Lidove
- Department of Internal Medicine, Groupe Hospitalier Diaconesses Croix Saint Simon, Site Avron & UMRS 974, 75013 Paris, France; (W.M.); (O.L.)
| | - Soumeya Bekri
- Department of Metabolic Biochemistry, Normandie University, UNIROUEN, INSERM U1245, CHU Rouen, 76000 Rouen, France; (F.D.); (C.P.); (R.A.); (S.B.)
| | - Abdellah Tebani
- Department of Metabolic Biochemistry, Normandie University, UNIROUEN, INSERM U1245, CHU Rouen, 76000 Rouen, France; (F.D.); (C.P.); (R.A.); (S.B.)
- Correspondence:
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Mak J, Cowan TM. Detecting lysosomal storage disorders by glycomic profiling using liquid chromatography mass spectrometry. Mol Genet Metab 2021; 134:43-52. [PMID: 34474962 PMCID: PMC9069563 DOI: 10.1016/j.ymgme.2021.08.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 08/14/2021] [Accepted: 08/15/2021] [Indexed: 01/15/2023]
Abstract
BACKGROUND Urine and plasma biomarker testing for lysosomal storage disorders by liquid chromatography mass spectrometry (LC-MS) currently requires multiple analytical methods to detect the abnormal accumulation of oligosaccharides, mucopolysaccharides, and glycolipids. To improve clinical testing efficiency, we developed a single LC-MS method to simultaneously identify disorders of oligosaccharide, mucopolysaccharide, and glycolipid metabolism with minimal sample preparation. METHODS We created a single chromatographic method for separating free glycans and glycolipids in their native form, using an amide column and high pH conditions. We used this glycomic profiling method both in untargeted analyses of patient and control urines using LC ion-mobility high-resolution MS (biomarker discovery), and targeted analyses of urine, serum, and dried blood spot samples by LC-MS/MS (clinical validation). RESULTS Untargeted glycomic profiling revealed twenty biomarkers that could identify and subtype mucopolysaccharidoses. We incorporated these with known oligosaccharide and glycolipid biomarkers into a rapid test that identifies at least 27 lysosomal storage disorders, including oligosaccharidoses, mucopolysaccharidoses, sphingolipidoses, glycogen storage disorders, and congenital disorders of glycosylation and de-glycosylation. In a validation set containing 115 urine samples from patients with lysosomal storage disorders, all were unambiguously distinguished from normal controls, with correct disease subtyping for 88% (101/115) of cases. Glucosylsphingosine was reliably elevated in dried blood spots from Gaucher disease patients with baseline resolution from galactosylsphingosine. CONCLUSION Glycomic profiling by liquid chromatography mass spectrometry identifies a range of lysosomal storage disorders. This test can be used in clinical evaluations to rapidly focus a diagnosis, as well as to clarify or support additional gene sequencing and enzyme studies.
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Affiliation(s)
- Justin Mak
- Clinical Biochemical Genetics Laboratory, Stanford Health Care, United States of America.
| | - Tina M Cowan
- Clinical Biochemical Genetics Laboratory, Stanford Health Care, United States of America; Department of Pathology, Stanford University Medical Center, United States of America
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Abstract
This paper aims to cover the main strategies based on ion mobility spectrometry (IMS) for the analysis of biological samples. The determination of endogenous and exogenous compounds in such samples is important for the understanding of the health status of individuals. For this reason, the development of new approaches that can be complementary to the ones already established (mainly based on liquid chromatography coupled to mass spectrometry) is welcomed. In this regard, ion mobility spectrometry has appeared in the analytical scenario as a powerful technique for the separation and characterization of compounds based on their mobility. IMS has been used in several areas taking advantage of its orthogonality with other analytical separation techniques, such as liquid chromatography, gas chromatography, capillary electrophoresis, or supercritical fluid chromatography. Bioanalysis is not one of the areas where IMS has been more extensively applied. However, over the last years, the interest in using this approach for the analysis of biological samples has clearly increased. This paper introduces the reader to the principles controlling the separation in IMS and reviews recent applications using this technique in the field of bioanalysis.
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De Pasquale V, Caterino M, Costanzo M, Fedele R, Ruoppolo M, Pavone LM. Targeted Metabolomic Analysis of a Mucopolysaccharidosis IIIB Mouse Model Reveals an Imbalance of Branched-Chain Amino Acid and Fatty Acid Metabolism. Int J Mol Sci 2020; 21:ijms21124211. [PMID: 32545699 PMCID: PMC7352355 DOI: 10.3390/ijms21124211] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 06/09/2020] [Accepted: 06/10/2020] [Indexed: 12/11/2022] Open
Abstract
Mucopolysaccharidoses (MPSs) are inherited disorders of the glycosaminoglycan (GAG) metabolism. The defective digestion of GAGs within the intralysosomal compartment of affected patients leads to a broad spectrum of clinical manifestations ranging from cardiovascular disease to neurological impairment. The molecular mechanisms underlying the progression of the disease downstream of the genetic mutation of genes encoding for lysosomal enzymes still remain unclear. Here, we applied a targeted metabolomic approach to a mouse model of PS IIIB, using a platform dedicated to the diagnosis of inherited metabolic disorders, in order to identify amino acid and fatty acid metabolic pathway alterations or the manifestations of other metabolic phenotypes. Our analysis highlighted an increase in the levels of branched-chain amino acids (BCAAs: Val, Ile, and Leu), aromatic amino acids (Tyr and Phe), free carnitine, and acylcarnitines in the liver and heart tissues of MPS IIIB mice as compared to the wild type (WT). Moreover, Ala, Met, Glu, Gly, Arg, Orn, and Cit amino acids were also found upregulated in the liver of MPS IIIB mice. These findings show a specific impairment of the BCAA and fatty acid catabolism in the heart of MPS IIIB mice. In the liver of affected mice, the glucose-alanine cycle and urea cycle resulted in being altered alongside a deregulation of the BCAA metabolism. Thus, our data demonstrate that an accumulation of BCAAs occurs secondary to lysosomal GAG storage, in both the liver and the heart of MPS IIIB mice. Since BCAAs regulate the biogenesis of lysosomes and autophagy mechanisms through mTOR signaling, impacting on lipid metabolism, this condition might contribute to the progression of the MPS IIIB disease.
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Affiliation(s)
- Valeria De Pasquale
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy; (V.D.P.); (M.C.); (M.C.); (L.M.P.)
| | - Marianna Caterino
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy; (V.D.P.); (M.C.); (M.C.); (L.M.P.)
- CEINGE—Biotecnologie Avanzate s.c.ar.l., 80145 Naples, Italy;
| | - Michele Costanzo
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy; (V.D.P.); (M.C.); (M.C.); (L.M.P.)
- CEINGE—Biotecnologie Avanzate s.c.ar.l., 80145 Naples, Italy;
| | - Roberta Fedele
- CEINGE—Biotecnologie Avanzate s.c.ar.l., 80145 Naples, Italy;
| | - Margherita Ruoppolo
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy; (V.D.P.); (M.C.); (M.C.); (L.M.P.)
- CEINGE—Biotecnologie Avanzate s.c.ar.l., 80145 Naples, Italy;
- Correspondence: ; Tel.: +39-081-3737850
| | - Luigi Michele Pavone
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131 Naples, Italy; (V.D.P.); (M.C.); (M.C.); (L.M.P.)
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A Proteomics-Based Analysis Reveals Predictive Biological Patterns in Fabry Disease. J Clin Med 2020; 9:jcm9051325. [PMID: 32370284 PMCID: PMC7290805 DOI: 10.3390/jcm9051325] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 04/27/2020] [Accepted: 04/28/2020] [Indexed: 02/06/2023] Open
Abstract
Background: Fabry disease (FD) is an X-linked progressive lysosomal disease (LD) due to glycosphingolipid metabolism impairment. Currently, plasmatic globotriaosylsphingosine (LysoGb3) is used for disease diagnosis and monitoring. However, this biomarker is inconstantly increased in mild forms and in some female patients. Materials and Methods: We applied a targeted proteomic approach to explore disease-related biological patterns that might explain the disease pathophysiology. Forty proteins, involved mainly in inflammatory and angiogenesis processes, were assessed in 69 plasma samples retrieved from the French Fabry cohort (FFABRY) and from 83 healthy subjects. For predictive performance assessment, we also included other LD samples (Gaucher, Pompe and Niemann Pick C). Results: The study yielded four discriminant proteins that include three angiogenesis proteins (fibroblast growth factor 2 (FGF2), vascular endothelial growth factor A (VEGFA), vascular endothelial growth factor C (VEGFC)) and one cytokine interleukin 7 (IL-7). A clear elevation of FGF2 and IL-7 concentrations was observed in FD compared to other LD samples. No correlation was observed between these proteins and globotriaosylsphingosine (LysoGb3). A significant correlation exists between IL-7 and residual enzyme activity in a non-classical phenotype. This highlights the orthogonal biological information yielded by these proteins that might help in stratifying Fabry patients. Conclusion: This work highlights the potential of using proteomics approaches in exploring FD and enhancing FD diagnosis and therapeutic monitoring performances.
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15
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Tebani A, Abily-Donval L, Schmitz-Afonso I, Piraud M, Ausseil J, Zerimech F, Pilon C, Pereira T, Marret S, Afonso C, Bekri S. Analysis of Mucopolysaccharidosis Type VI through Integrative Functional Metabolomics. Int J Mol Sci 2019; 20:ijms20020446. [PMID: 30669586 PMCID: PMC6359186 DOI: 10.3390/ijms20020446] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 01/17/2019] [Accepted: 01/18/2019] [Indexed: 12/12/2022] Open
Abstract
Metabolic phenotyping is poised as a powerful and promising tool for biomarker discovery in inherited metabolic diseases. However, few studies applied this approach to mcopolysaccharidoses (MPS). Thus, this innovative functional approach may unveil comprehensive impairments in MPS biology. This study explores mcopolysaccharidosis VI (MPS VI) or Maroteaux–Lamy syndrome (OMIM #253200) which is an autosomal recessive lysosomal storage disease caused by the deficiency of arylsulfatase B enzyme. Urine samples were collected from 16 MPS VI patients and 66 healthy control individuals. Untargeted metabolomics analysis was applied using ultra-high-performance liquid chromatography combined with ion mobility and high-resolution mass spectrometry. Furthermore, dermatan sulfate, amino acids, carnitine, and acylcarnitine profiles were quantified using liquid chromatography coupled to tandem mass spectrometry. Univariate analysis and multivariate data modeling were used for integrative analysis and discriminant metabolites selection. Pathway analysis was done to unveil impaired metabolism. The study revealed significant differential biochemical patterns using multivariate data modeling. Pathway analysis revealed that several major amino acid pathways were dysregulated in MPS VI. Integrative analysis of targeted and untargeted metabolomics data with in silico results yielded arginine-proline, histidine, and glutathione metabolism being the most affected. This study is one of the first metabolic phenotyping studies of MPS VI. The findings might shed light on molecular understanding of MPS pathophysiology to develop further MPS studies to enhance diagnosis and treatments of this rare condition.
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Affiliation(s)
- Abdellah Tebani
- Department of Metabolic Biochemistry, Rouen University Hospital, 76000 Rouen, France.
- Normandie University, UNIROUEN, CHU Rouen, INSERM U1245, 76000 Rouen, France.
- Normandie Univ, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000 Rouen, France.
| | - Lenaig Abily-Donval
- Normandie University, UNIROUEN, CHU Rouen, INSERM U1245, 76000 Rouen, France.
- Department of Neonatal Pediatrics, Intensive Care and Neuropediatrics, Rouen University Hospital, 76031 Rouen, France.
| | | | - Monique Piraud
- Service de Biochimie et Biologie Moléculaire Grand Est, Unité des Maladies Héréditaires du Métabolisme et Dépistage Néonatal, Centre de Biologie et de Pathologie Est, Hospices Civils de Lyon, 69002 Lyon, France.
| | - Jérôme Ausseil
- INSERM U1088, Laboratoire de Biochimie Métabolique, Centre de Biologie Humaine, CHU Sud, 80054 Amiens CEDEX, France.
| | - Farid Zerimech
- Laboratoire de Biochimie et Biologie Moléculaire, Université de Lille et Pôle de Biologie Pathologie Génétique du CHRU de Lille, 59000 Lille, France.
| | - Carine Pilon
- Department of Metabolic Biochemistry, Rouen University Hospital, 76000 Rouen, France.
| | - Tony Pereira
- Department of Pharmacology, Rouen University Hospital, 76000 Rouen, France.
| | - Stéphane Marret
- Normandie University, UNIROUEN, CHU Rouen, INSERM U1245, 76000 Rouen, France.
- Department of Neonatal Pediatrics, Intensive Care and Neuropediatrics, Rouen University Hospital, 76031 Rouen, France.
| | - Carlos Afonso
- Normandie Univ, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000 Rouen, France.
| | - Soumeya Bekri
- Department of Metabolic Biochemistry, Rouen University Hospital, 76000 Rouen, France.
- Normandie University, UNIROUEN, CHU Rouen, INSERM U1245, 76000 Rouen, France.
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16
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Direct Infusion Based Metabolomics Identifies Metabolic Disease in Patients' Dried Blood Spots and Plasma. Metabolites 2019; 9:metabo9010012. [PMID: 30641898 PMCID: PMC6359237 DOI: 10.3390/metabo9010012] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 01/04/2019] [Accepted: 01/08/2019] [Indexed: 01/17/2023] Open
Abstract
In metabolic diagnostics, there is an emerging need for a comprehensive test to acquire a complete view of metabolite status. Here, we describe a non-quantitative direct-infusion high-resolution mass spectrometry (DI-HRMS) based metabolomics method and evaluate the method for both dried blood spots (DBS) and plasma. 110 DBS of 42 patients harboring 23 different inborn errors of metabolism (IEM) and 86 plasma samples of 38 patients harboring 21 different IEM were analyzed using DI-HRMS. A peak calling pipeline developed in R programming language provided Z-scores for ~1875 mass peaks corresponding to ~3835 metabolite annotations (including isomers) per sample. Based on metabolite Z-scores, patients were assigned a ‘most probable diagnosis’ by an investigator blinded for the known diagnoses of the patients. Based on DBS sample analysis, 37/42 of the patients, corresponding to 22/23 IEM, could be correctly assigned a ‘most probable diagnosis’. Plasma sample analysis, resulted in a correct ‘most probable diagnosis’ in 32/38 of the patients, corresponding to 19/21 IEM. The added clinical value of the method was illustrated by a case wherein DI-HRMS metabolomics aided interpretation of a variant of unknown significance (VUS) identified by whole-exome sequencing. In summary, non-quantitative DI-HRMS metabolomics in DBS and plasma is a very consistent, high-throughput and nonselective method for investigating the metabolome in genetic disease.
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17
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Liang D, Moutinho JL, Golan R, Yu T, Ladva CN, Niedzwiecki M, Walker DI, Sarnat SE, Chang HH, Greenwald R, Jones DP, Russell AG, Sarnat JA. Use of high-resolution metabolomics for the identification of metabolic signals associated with traffic-related air pollution. ENVIRONMENT INTERNATIONAL 2018; 120:145-154. [PMID: 30092452 PMCID: PMC6414207 DOI: 10.1016/j.envint.2018.07.044] [Citation(s) in RCA: 108] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 07/27/2018] [Accepted: 07/27/2018] [Indexed: 05/03/2023]
Abstract
BACKGROUND High-resolution metabolomics (HRM) is emerging as a sensitive tool for measuring environmental exposures and biological responses. The aim of this analysis is to assess the ability of high-resolution metabolomics (HRM) to reflect internal exposures to complex traffic-related air pollution mixtures. METHODS We used untargeted HRM profiling to characterize plasma and saliva collected from participants in the Dorm Room Inhalation to Vehicle Emission (DRIVE) study to identify metabolic pathways associated with traffic emission exposures. We measured a suite of traffic-related pollutants at multiple ambient and indoor sites at varying distances from a major highway artery for 12 weeks in 2014. In parallel, 54 students living in dormitories near (20 m) or far (1.4 km) from the highway contributed plasma and saliva samples. Untargeted HRM profiling was completed for both plasma and saliva samples; metabolite and metabolic pathway alternations were evaluated using a metabolome-wide association study (MWAS) framework with pathway analyses. RESULTS Weekly levels of traffic pollutants were significantly higher at the near dorm when compared to the far dorm (p < 0.05 for all pollutants). In total, 20,766 metabolic features were extracted from plasma samples and 29,013 from saliva samples. 45% of features were detected and shared in both plasma and saliva samples. 1291 unique metabolic features were significantly associated with at least one or more traffic indicator, including black carbon, carbon monoxide, nitrogen oxides and fine particulate matter (p < 0.05 for all significant features), after controlling for confounding and false discovery rate. Pathway analysis of metabolic features associated with traffic exposure indicated elicitation of inflammatory and oxidative stress related pathways, including leukotriene and vitamin E metabolism. We confirmed the chemical identities of 10 metabolites associated with traffic pollutants, including arginine, histidine, γ‑linolenic acid, and hypoxanthine. CONCLUSIONS Using HRM, we identified and verified biological perturbations associated with primary traffic pollutant in panel-based setting with repeated measurement. Observed response was consistent with endogenous metabolic signaling related to oxidative stress, inflammation, and nucleic acid damage and repair. Collectively, the current findings provide support for the use of untargeted HRM in the development of metabolic biomarkers of traffic pollution exposure and response.
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Affiliation(s)
- Donghai Liang
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, USA.
| | - Jennifer L Moutinho
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, USA
| | - Rachel Golan
- Department of Public Health, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Tianwei Yu
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, USA
| | - Chandresh N Ladva
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA
| | - Megan Niedzwiecki
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Douglas I Walker
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, USA
| | - Stefanie Ebelt Sarnat
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, USA
| | - Howard H Chang
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, USA
| | - Roby Greenwald
- Division of Environmental Health, Georgia State University School of Public Health, Atlanta, USA
| | - Dean P Jones
- Clinical Biomarkers Laboratory, Division of Pulmonary, Allergy, and Critical Care Medicine, School of Medicine, Emory University, Atlanta, USA
| | - Armistead G Russell
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, USA
| | - Jeremy A Sarnat
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, USA
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18
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Tebani A, Abily-Donval L, Schmitz-Afonso I, Héron B, Piraud M, Ausseil J, Zerimech F, Gonzalez B, Marret S, Afonso C, Bekri S. Unveiling metabolic remodeling in mucopolysaccharidosis type III through integrative metabolomics and pathway analysis. J Transl Med 2018; 16:248. [PMID: 30180851 PMCID: PMC6122730 DOI: 10.1186/s12967-018-1625-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 08/30/2018] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Metabolomics represent a valuable tool to recover biological information using body fluids and may help to characterize pathophysiological mechanisms of the studied disease. This approach has not been widely used to explore inherited metabolic diseases. This study investigates mucopolysaccharidosis type III (MPS III). A thorough and holistic understanding of metabolic remodeling in MPS III may allow the development, improvement and personalization of patient care. METHODS We applied both targeted and untargeted metabolomics to urine samples obtained from a French cohort of 49 patients, consisting of 13 MPS IIIA, 16 MPS IIIB, 13 MPS IIIC, and 7 MPS IIID, along with 66 controls. The analytical strategy is based on ultra-high-performance liquid chromatography combined with ion mobility and high-resolution mass spectrometry. Twenty-four amino acids have been assessed using tandem mass spectrometry combined with liquid chromatography. Multivariate data modeling has been used for discriminant metabolite selection. Pathway analysis has been performed to retrieve metabolic pathways impairments. RESULTS Data analysis revealed distinct biochemical profiles. These metabolic patterns, particularly those related to the amino acid metabolisms, allowed the different studied groups to be distinguished. Pathway analysis unveiled major amino acid pathways impairments in MPS III mainly arginine-proline metabolism and urea cycle metabolism. CONCLUSION This represents one of the first metabolomics-based investigations of MPS III. These results may shed light on MPS III pathophysiology and could help to set more targeted studies to infer the biomarkers of the affected pathways, which is crucial for rare conditions such as MPS III.
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Affiliation(s)
- Abdellah Tebani
- Department of Metabolic Biochemistry, Rouen University Hospital, 76000, Rouen Cedex, France.,Normandie Univ, UNIROUEN, CHU Rouen, INSERM U1245, 76000, Rouen, France.,Normandie Univ, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000, Rouen, France
| | - Lenaig Abily-Donval
- Normandie Univ, UNIROUEN, CHU Rouen, INSERM U1245, 76000, Rouen, France.,Department of Neonatal Pediatrics, Intensive Care and Neuropediatrics, Rouen University Hospital, 76031, Rouen, France
| | | | - Bénédicte Héron
- Department of Pediatric Neurology, Reference Center of Lysosomal Diseases, Trousseau Hospital, APHP and Sorbonne Université, GRC No 19, Pathologies Congénitales du Cervelet-LeucoDystrophies, AP-HP, Hôpital Armand Trousseau, 75012, Paris, France
| | - Monique Piraud
- Service de Biochimie et Biologie Moléculaire Grand Est, Unité des Maladies Héréditaires du Métabolisme et Dépistage Néonatal, Centre de Biologie et de Pathologie Est, CHU de Lyon, Lyon, France
| | - Jérôme Ausseil
- INSERM U1088, Laboratoire de Biochimie Métabolique, Centre de Biologie Humaine, CHU Sud, 80054, Amiens Cedex, France
| | - Farid Zerimech
- Laboratoire de Biochimie et Biologie Moléculaire, Université de Lille et Pôle de Biologie Pathologie Génétique du CHRU de Lille, 59000, Lille, France
| | - Bruno Gonzalez
- Normandie Univ, UNIROUEN, CHU Rouen, INSERM U1245, 76000, Rouen, France
| | - Stéphane Marret
- Normandie Univ, UNIROUEN, CHU Rouen, INSERM U1245, 76000, Rouen, France.,Department of Neonatal Pediatrics, Intensive Care and Neuropediatrics, Rouen University Hospital, 76031, Rouen, France
| | - Carlos Afonso
- Normandie Univ, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000, Rouen, France
| | - Soumeya Bekri
- Department of Metabolic Biochemistry, Rouen University Hospital, 76000, Rouen Cedex, France. .,Normandie Univ, UNIROUEN, CHU Rouen, INSERM U1245, 76000, Rouen, France.
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Mussap M, Zaffanello M, Fanos V. Metabolomics: a challenge for detecting and monitoring inborn errors of metabolism. ANNALS OF TRANSLATIONAL MEDICINE 2018; 6:338. [PMID: 30306077 DOI: 10.21037/atm.2018.09.18] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Timely newborn screening and genetic profiling are crucial in early recognition and treatment of inborn errors of metabolism (IEMs). A proposed nosology of IEMs has inserted 1,015 well-characterized IEMs causing alterations in specific metabolic pathways. With the increasing expansion of metabolomics in clinical biochemistry and laboratory medicine communities, several research groups have focused their interest on the analysis of metabolites and their interconnections in IEMs. Metabolomics has the potential to extend metabolic information, thus allowing to achieve an accurate diagnosis for the individual patient and to discover novel IEMs. Structural and functional information on 247 metabolites associated with 147 IEMs and 202 metabolic pathways involved in various IEMs have been reported in the human metabolome data base (HMDB). For each metabolic gene, a new computational approach can be developed for predicting a set of metabolites, whose concentration is predicted to change after gene knockout in urine, blood and other biological fluids. Both targeted and untargeted mass spectrometry (MS)-based metabolomic approaches have been used to expand the range of disease-associate metabolites. The quantitative targeted approach, in conjunction with chemometrics, can be considered a basic tool for validating known diagnostic biomarkers in various metabolic disorders. The untargeted approach broadens the identification of new biomarkers in known IEMs and allows pathways analysis. Urine is an ideal biological fluid for metabolomics in neonatology; however, the lack of standardization of preanalytical phase may generate potential interferences in metabolomic studies. The integration of genomic and metabolomic data represents the current challenge for improving diagnosis and prognostication of IEMs. The goals consist in identifying both metabolically active loci and genes relevant to a disease phenotype, which means deriving disease-specific biological insights.
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Affiliation(s)
- Michele Mussap
- Laboratory Medicine, Department of Surgical Sciences, University of Cagliari, Cagliari, Italy
| | - Marco Zaffanello
- Department of Surgical Sciences, Dentistry, Gynecology and Pediatrics, University of Verona, Verona, Italy
| | - Vassilios Fanos
- Department of Surgical Sciences, Neonatal Intensive Care Unit, Puericulture Institute and Neonatal Section, University of Cagliari, Cagliari, Italy
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