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Individualized metabolomics: opportunities and challenges

  • Biswapriya Misra ORCID logo EMAIL logo
Published/Copyright: April 5, 2019
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Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 58 Issue 6

Abstract

The goal of advancing science in health care is to provide high quality treatment and therapeutic opportunities to patients in need. This is especially true in precision medicine, wherein the ultimate goal is to link disease phenotypes to targeted treatments and novel therapeutics at the scale of an individual. With the advent of -omics technologies, such as genomics, proteomics, microbiome, among others, the metabolome is of wider and immediate interest for its important role in metabolic regulation. The metabolome, of course, comes with its own questions regarding technological challenges. In this opinion article, I attempt to interrogate some of the main challenges associated with individualized metabolomics, and available opportunities in the context of its clinical application. Some questions this article addresses and attempts to find answers for are: Can a personal metabolome (n = 1) be inexpensive, affordable and informative enough (i.e. provide predictive yet validated biomarkers) to represent the entirety of a population? How can a personal metabolome complement advances in other -omics areas and the use of monitoring devices, which occupy our personal space?

Keywords: big data; clinical; healthcare; individualized; mass spectrometry; metabolomics; personalized; precision
Corresponding author: Biswapriya Misra, PhD, Center for Precision Medicine, Department of Internal Medicine, Section on Molecular Medicine, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, 27157 NC, USA, Twitter: @BiswapriyaMisra

Acknowledgments

The author would like to acknowledge the mass-spectrometry, metabolomics and healthcare research community with their relentless efforts to help serve patients as a primary objective of their research. The author also thanks the three anonymous and kind reviewers for helping improve this article leaps and bounds.

  1. Author contribution: The sole author (BBM) has accepted responsibility for the entire content of this submitted manuscript and submission.

  2. Research funding: None declared.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Conflicts of Interest: The author declares that the review was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author does not endorse or promote any commercial brands mentioned in this review and are cited only for academic reasons.

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Received: 2019-02-03
Accepted: 2019-03-04
Published Online: 2019-04-05
Published in Print: 2020-06-25

©2019 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/cclm-2019-0130
Keywords for this article
big data; clinical; healthcare; individualized; mass spectrometry; metabolomics; personalized; precision

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Advancements in mass spectrometry as a tool for clinical analysis: part II
  4. Quantitative protein assessment
  5. Complexity, cost, and content – three important factors for translation of clinical protein mass spectrometry tests, and the case for apolipoprotein C-III proteoform testing
  6. Vedolizumab quantitation using high-resolution accurate mass-mass spectrometry middle-up protein subunit: method validation
  7. Development and evaluation of an element-tagged immunoassay coupled with inductively coupled plasma mass spectrometry detection: can we apply the new assay in the clinical laboratory?
  8. MALDI-MS for the clinic
  9. Matrix-assisted laser desorption ionisation (MALDI) mass spectrometry (MS): basics and clinical applications
  10. Clinical use of mass spectrometry (imaging) for hard tissue analysis in abnormal fracture healing
  11. Cellular resolution in clinical MALDI mass spectrometry imaging: the latest advancements and current challenges
  12. Bacterial identification by lipid profiling using liquid atmospheric pressure matrix-assisted laser desorption/ionization mass spectrometry
  13. Clinical application of ’omics technologies
  14. Individualized metabolomics: opportunities and challenges
  15. Diagnostic amyloid proteomics: experience of the UK National Amyloidosis Centre
  16. The “olfactory fingerprint”: can diagnostics be improved by combining canine and digital noses?
  17. Peptidomic and proteomic analysis of stool for diagnosing IBD and deciphering disease pathogenesis
  18. The influence of hypoxia on the prostate cancer proteome
  19. Laboratory automation and kit-based approaches
  20. Mass spectrometry and total laboratory automation: opportunities and drawbacks
  21. The pathway through LC-MS method development: in-house or ready-to-use kit-based methods?
  22. Evaluation of the 25-hydroxy vitamin D assay on a fully automated liquid chromatography mass spectrometry system, the Thermo Scientific Cascadion SM Clinical Analyzer with the Cascadion 25-hydroxy vitamin D assay in a routine clinical laboratory
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