Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Abstract

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

Imaging Evaluation of Intervertebral Disc Degeneration and Painful Discs—Advances and Challenges in Quantitative MRI

“…Gornet et al [96] found that MRS scores, using structural integrity markers (carbohydrate/collagen and PG) expected to decrease with disc degeneration and acidic pain markers (alanine, lactate, and propionate) expected to increase with hypoxia and inflammation, could be obtained by quantifying spectral features from optimized clinical MRS data identified painful discs in patients with chronic LBP with a sensitivity of 82% and a specificity of 88% when compared to provocative discography. As MRS targets the measurement of trace metabolites with signal intensity much lower than that of MRI, the spatiotemporal resolution is low at current clinical MRI field strengths [97]. The widespread use of high-field MRI in the future may expand the clinical application of MRS, which can provide biochemical information.…”

Differential metabolism between biofilm and suspended Pseudomonas aeruginosa cultures in bovine synovial fluid by 2D NMR-based metabolomics

“…On the other hand, 1D NMR spectra can be rapidly collected within minutes. While use of NMR is still relatively limited in clinical diagnostics, there are increasing numbers of hospitals with NMR machines for metabolomics analysis of patient samples, for example for cardiovascular disease, diabetes, and cancer (31). These newly identified metabolites may also be translated to other more targeted methods that are faster and less costly than NMR, such as biosensors or immunoassays (32, 33).…”

1H-NMR-based metabolic profiling identifies non-invasive diagnostic and predictive urinary fingerprints in 5q spinal muscular atrophy

“…NMR-based metabolomics offers many advantages in biomarker development. NMR is a high-throughput method requiring minimal sample preparation, allowing quantitative analysis with excellent reproducibility and unlike commonly used techniques, such as mass spectrometry, simultaneously measures all of the more abundant compounds within a biological sample [ 34 , 35 ]. Urine has been proposed as the preferred medium for biomarker development in neurological diseases including SMA, since it is readily available and easily obtained in a non-invasive manner and more importantly, unlike blood and cerebrospinal fluid, lacks homeostatic mechanisms that might attenuate systemic fluctuations, thus more adequately reflecting disease-specific changes [ 18 , 24 ].…”