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