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Untargeted metabolomic analysis of urine samples for diagnosis of inherited metabolic disorders

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Abstract

Metabolomics has become an important tool for clinical research, especially for analyzing inherited metabolic disorders (IMDs). The purpose of this study was to explore the performance of metabolomics in diagnosing IMDs using an untargeted metabolomic approach. A total of 40 urine samples were collected: 20 samples from healthy children and 20 from pediatric patients, of whom 13 had confirmed IMDs and seven had suspected IMDs. Samples were analyzed by Orbitrap mass spectrometry in positive and negative mode alternately, coupled with ultra-high liquid chromatography. Raw data were processed using Compound Discovery 2.0 ™ and then exported for partial least squares discriminant analysis (PLS-DA) by SIMCA-P 14.1. After comparing with m/zCloud and chemSpider libraries, compounds with similarity above 80% were selected and normalized for subsequent relative quantification analysis. The uncommon compounds discovered were analyzed based on the Kyoto Encyclopedia of Genes and Genomes to explore their possible metabolic pathways. All IMDs patients were successfully distinguished from controls in the PLS-DA. Untargeted metabolomics revealed a broader metabolic spectrum in patients than what is observed using routine chromatographic methods for detecting IMDs. Higher levels of certain compounds were found in all 13 confirmed IMD patients and 5 of 7 suspected IMD patients. Several potential novel markers emerged after relative quantification. Untargeted metabolomics may be able to diagnose IMDs from urine and may deepen insights into the disease by revealing changes in various compounds such as amino acids, acylcarnitines, organic acids, and nucleosides. Such analyses may identify biomarkers to improve the study and treatment of IMDs.

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Abbreviations

IMD:

Inherited metabolic disorder

PLS-DA:

Partial least-squares discrimination analysis

LC–MS/MS:

Liquid chromatography with tandem mass spectrometry

GC/MS:

Gas chromatography/mass spectrometry

UHPLC:

Ultra-high performance liquid chromatography

HHH syndrome:

Hyperornithinemia-hyperammonemia-homocitrullinuria syndrome

PA:

Propionic aciduria

GA-II:

Glutaric acidemia type II

HMGCS2:

3-Hydroxy-3-methylglutaryl-CoA synthase 2

CPT I:

Carnitine palmitoyltransferase I

KEGG:

Kyoto Encyclopedia of Genes and Genomes

References

  • Albers E (2009) Metabolic characteristics and importance of the universal methionine salvage pathway recycling methionine from 5′-methylthioadenosine. IUBMB Life 61(12):1132–1142

    Article  CAS  Google Scholar 

  • Avila MA, García-Trevijano ER, Lu SC et al (2004) Methylthioadenosine. Int J Biochem Cell Biol 36(11):2125–30

    Article  CAS  Google Scholar 

  • Bigaud E, Corrales FJ (2016) Methylthioadenosine (MTA) regulates liver cells proteome and methylproteome: implications in liver biology and disease. Mol Cell Proteomics 15(5):1498–510

    Article  CAS  Google Scholar 

  • Coene KLM, Kluijtmans LAJ, van der Heeft E et al (2018) Next-generation metabolic screening: targeted and untargeted metabolomics for the diagnosis of inborn errors of metabolism in individual patients. J Inherit Metab Dis 41(3):337–353

    Article  CAS  Google Scholar 

  • Conlon TA, Fitzsimons PE, Borovickova I et al (2020) Hypoglycemia is not a defining feature of metabolic crisis in mitochondrial 3-hydroxy-3-methylglutaryl-CoA synthase deficiency: further evidence of specific biochemical markers which may aid diagnosis. JIMD Rep 55(1):26–31

    Article  Google Scholar 

  • Dixon RA, Ferreira D (2002) Genistein. Phytochemistry 60(3):205–11

    Article  CAS  Google Scholar 

  • Grebe SK, Singh RJ (2011) LC-MS/MS in the clinical laboratory - where to from here? Clin Biochem Rev 32(1):5–31

    PubMed  PubMed Central  Google Scholar 

  • Ismail IT, Showalter MR, Fiehn O (2019) Inborn errors of metabolism in the era of untargeted metabolomics and lipidomics. Metabolites 9(10):242

    Article  CAS  Google Scholar 

  • Ismail IT, Showalter MR, Fiehn O (2019) Inborn errors of metabolism in the era of untargeted metabolomics and lipidomics. Metabolites 9(10):242

    Article  CAS  Google Scholar 

  • Janeckova H, Kalivodova A, Najdekr L et al (2015) Untargeted metabolomic analysis of urine samples in the diagnosis of some inherited metabolic disorders. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub 159(4):582–585

    Article  Google Scholar 

  • Kennedy AD, Miller MJ, Beebe K et al (2016) Metabolomic profiling of human urine as a screen for multiple inborn errors of metabolism. Genet Test Mol Biomarkers 20(9):485–95

    Article  CAS  Google Scholar 

  • Kim DH, Kim B-G, Jung NR et al (2009) Production of genistein from naringenin using Escherichia coli containing isoflavone synthase-cytochrome P450 reductase fusion protein. J Microbiol Biotechnol 19(12):1612–6

    Article  CAS  Google Scholar 

  • Komiyama K, Tronquet C, Hirokawa Y et al (1986) The suppressive effect of pyrrole-2-carboxylic acid on platelet aggregation. Jpn J Antibio 39(3):746–750

    CAS  Google Scholar 

  • Kompare M, Rizzo WB (2008) Mitochondrial fatty-acid oxidation disorders. Semin Pediatr Neurol 15(3):140–9

    Article  Google Scholar 

  • Lee T, Takami Y, Yamada K et al (2019) A Japanese case of mitochondrial 3-hydroxy-3-methylglutaryl-CoA synthase deficiency who presented with severe metabolic acidosis and fatty liver without hypoglycemia. JIMD Rep 48(1):19–25

    Article  Google Scholar 

  • Leuzzi V, Mastrangelo M, Battini R (2013) Inborn errors of creatine metabolism and epilepsy. Epilepsia 54(2):217–27

    Article  CAS  Google Scholar 

  • Miller MJ, Kennedy AD, Eckhart AD et al (2015) Untargeted metabolomic analysis for the clinical screening of inborn errors of metabolism. J Inherit Metab Dis 38:1029–1039

    Article  CAS  Google Scholar 

  • Mordaunt D, Cox D, Fuller M (2020) Metabolomics to improve the diagnostic efficiency of inborn errors of metabolism. Int J Mol Sci 21(4):1195

    Article  CAS  Google Scholar 

  • Mussap M, Zaffanello M, Fanos V et al (2018) Metabolomics: a challenge for detecting and monitoring inborn errors of metabolism. Ann Transl Med 6(17):338

    Article  Google Scholar 

  • Oleg A Shchelochkov, Nuria Carrillo, Charles Venditti (2012) GeneReviews® [Internet]. Seattle (WA): University of Washington, Seattle; 1993–2021

  • Parveen N, Cornell KA (2011) Methylthioadenosine/S-adenosylhomocysteine nucleosidase, a critical enzyme for bacterial metabolism. Mol Microbiol 79(1):7–20

    Article  CAS  Google Scholar 

  • Pitt JJ, Peters H, Boneh A et al (2015) Mitochondrial 3-hydroxy-3-methylglutaryl-CoA synthase deficiency: urinary organic acid profiles and expanded spectrum of mutations. J Inherit Metab Dis 38(3):459–66

    Article  CAS  Google Scholar 

  • Radhakrishnan AN, Meister A (1957) Conversion of hydroxyproline to pyrrole-2-carboxylic acid. J Biol Chem 226(1):559–571

    Article  CAS  Google Scholar 

  • Robinson BH (2006) Lactic acidemia and mitochondrial disease. Mol Genet Metab 89(1–2):3–13

    Article  CAS  Google Scholar 

  • Sandlers Y (2017) The future perspective: metabolomics in laboratory medicine for inborn errors of metabolism. Transl Res 189:65–75

    Article  CAS  Google Scholar 

  • Schuster K, Bailey LB, Cerda JJ et al (1984) Urinary 4-pyridoxic acid excretion in 24-hour versus random urine samples as a measurement of vitamin B6 status in humans. Am J Clin Nutr 39(3):466–470

    Article  CAS  Google Scholar 

  • Sklirou E, Lichter-Konecki U (2018) Inborn errors of metabolism with cognitive impairment: metabolism defects of phenylalanine, homocysteine and methionine, purine and pyrimidine, and creatine. Pediatr Clin North Am 65(2):267–277

    Article  Google Scholar 

  • Soloms G, Alt EJ, Jensen RL, Dorsey DC (1965) The Guthrie test in monitoring the diet in PKU: an appraisal of its applicability. Clin Pediatr (phila) 4:147–149

    Article  CAS  Google Scholar 

  • Ueland PM, Ulvik A, Rios-Avila L et al (2015) Direct and functional biomarkers of vitamin B6 status. Annu Rev Nutr 35:33–70

    Article  CAS  Google Scholar 

  • Villani GR, Gallo G, Scolamiero E (2017) “Classical organic acidurias”: diagnosis and pathogenesis. Clin Exp Med 17(3):305–323

    Article  CAS  Google Scholar 

  • Wortmann SB, Mayr JA (2019) Choline-related-inherited metabolic diseases-a mini review. J Inherit Metab Dis 42(2):237–242

    Article  CAS  Google Scholar 

  • Yamanishi Y, Iguchi M, Oyama H et al (1972) Collagen metabolism. I. Significance of urinary pyrrole-2-carboxylic acid. J Clin Endocrinol Metab 35(1):55–8

    Article  CAS  Google Scholar 

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Acknowledgements

We would like to thank Prof. Tingyu Li (Children’s Hospital of Chongqing Medical University, Chongqing, China) for providing the urine samples of healthy children as normal controls.

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Authors and Affiliations

  1. Newborn Screening Center, Chongqing Health Center for Women and Children, Longshan Road 120th, Yubei District, Chongqing, 401147, People’s Republic of China

    Hao Liu & Jingkun Miao

  2. Center for Clinical Molecular Medicine, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Children’s Hospital of Chongqing Medical University, Zhongshan Road 2nd, Yuzhong District, Chongqing, 400014, People’s Republic of China

    Hao Liu, Dongjuan Wang, Kexing Wan, Zhaojian Yuan, Juan Zhang, Lin Zou & Xiaoyan He

  3. Chongqing Key Laboratory of Child Nutrition and Health, Children’s Hospital of Chongqing Medical University, Chongqing, 400014, People’s Republic of China

    Jiang Zhu & Qiu Li

Authors
  1. Hao Liu
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  2. Jiang Zhu
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  3. Qiu Li
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  4. Dongjuan Wang
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  5. Kexing Wan
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  7. Juan Zhang
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  8. Lin Zou
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  9. Xiaoyan He
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  10. Jingkun Miao
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Contributions

HL: raw data processing, manuscript writing, study design, and execution

JZ and QL: sample collection and healthy control information writing

DJ W: statistical analysis

ZJ Y: table preparation

KX W: figure preparation

LZ: data interpretation

JZ: sample collection and patient data collection

JK M: manuscript revision, study design

XY He: manuscript revision, study design

Corresponding authors

Correspondence to Xiaoyan He or Jingkun Miao.

Ethics declarations

Ethics approval

All procedures were performed in accordance with the ethical standards of Chongqing Health Center for Women and Children and Children’s Hospital of Chongqing Medical University with informed consent.

Patient consent

This work was performed with the informed consent of the patient’s family.

Competing interests

The authors declare no competing interests.

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Hao Liu is the first author

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Liu, H., Zhu, J., Li, Q. et al. Untargeted metabolomic analysis of urine samples for diagnosis of inherited metabolic disorders. Funct Integr Genomics 21, 645–653 (2021). https://doi.org/10.1007/s10142-021-00804-w

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  • DOI: https://doi.org/10.1007/s10142-021-00804-w

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