high-field NMR metabolomics, as well as methods which have been described above to improve the resolution such as fast 2D NMR or pure-shift approaches. Recent results highlighted the potential of such advanced benchtop NMR methods for sample classification (Gouilleux et al., 2018), and one can expect that clinical metabolomics will benefit from such advances in the coming years.

## CONCLUSION

Thanks to intrinsic properties such as high reproducibility, the possibility to quantify, a high degree of structural information, its “universal” detection capacity for all organic molecules as well as its adaptability in the analysis of biological samples, NMR very early appeared as a platform of choice in clinical metabolomics. The numerous publications, works and results based on NMR attest this fact and keep contributing to the development of this approach. The recent progresses in mass spectrometry coupled with liquid or gas chromatography, a more sensitive and higher resolution technique, have progressively led NMR to play a “second” role in metabolomic studies, raising the question of its future in the field. However, the applications of metabolomics in clinical research and personalized medicine have brought new needs and challenges for metabolomics, such as the analysis of large cohorts, the stratification and the longitudinal follow-up of patients and the identification and quantification of biomarkers. To face such multiple requirements and needs, NMR has real assets and opportunities. Indeed, the many recent instrumental and methodological developments aiming at improving both

sensitivity and resolution, as well as the demonstration of its excellent complementarity with mass spectrometry, highlight the leading role of NMR spectroscopy in clinical metabolomics and in personalized medicine. The translation from laboratory studies to clinical practice is another challenge that metabolomics is facing and, in this respect, we are confident that NMR will be one of the key analytical platforms that can provide valuable and innovative solutions and opportunities with a view to a personalized approach to medicine. Considering the numerous promising perspectives mentioned in this review, there is no doubt that the recent and future developments will rekindle the flame of NMR spectroscopy in clinical metabolomics for the next decades.

## AUTHOR CONTRIBUTIONS

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

## ACKNOWLEDGMENTS

Authors from CEISAM acknowledge support of the European Research Council under the European Union's Horizon 2020 Research and Innovation Program (ERC Grant Agreement No. 814747/SUMMIT) the French National Infrastructure for Metabolomics and Fluxomics MetaboHUB-ANR-11-INBS-0010 (www.metabohub.fr) and the Corsaire metabolomics core facility (Biogenouest). PdT is Research Director of the FNRS.

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Boccard, J., and Rudaz, S. (2014). Harnessing the Complexity of Metabolomic Data with Chemometrics. *J. Chemom.* 28, 1–9. doi:10.1002/cem.2567

Bornet, A., Maucourt, M., Deborde, C., Jacob, D., Milani, J., Vuichoud, B., et al. (2016). Highly Repeatable Dissolution Dynamic Nuclear Polarization for Heteronuclear NMR Metabolomics. *Anal. Chem.* 88, 6179–6183. doi:10.1021/acs.analchem.6b01094

Bowen, S., and Hilty, C. (2010). Rapid Sample Injection for Hyperpolarized NMR Spectroscopy. *Phys. Chem. Chem. Phys.* 12, 5766–5770. doi:10.1039/c002316g

Bowler, R. P., Wendt, C. H., Fessler, M. B., Foster, M. W., Kelly, R. S., Lasky-Su, J., et al. (2017). New Strategies and Challenges in Lung Proteomics and Metabolomics: An Official American Thoracic Society Workshop Report. *Ann. ATS* 14, 1721–1743. doi:10.1513/AnnalsATS.201710-770WS

Bruno, C., Patin, F., Bocca, C., Nadal-Desbarats, L., Bonnier, F., Reynier, P., et al. (2018). The Combination of Four Analytical Methods to Explore Skeletal Muscle Metabolomics: Better Coverage of Metabolic Pathways or a Marketing Argument? *J. Pharm. Biomed. Anal.* 148, 273–279. doi:10.1016/j.jpba.2017.10.013

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Castañar, L. (2017). Pure Shift 1 H NMR: what Is Next? *Magn. Reson. Chem.* 55, 47–53. doi:10.1002/mrc.4545

Catapano, A. L., Graham, I., De Backer, G., Wiklund, O., Chapman, M. J., Drexel, H., et al. (2016). 2016 ESC/EAS Guidelines for the Management of Dyslipidaemias. *Atherosclerosis* 253, 281–344. doi:10.1016/j.atherosclerosis.2016.08.018

Chan, Q., Loo, R. L., Ebbels, T. M. D., Van Horn, L., Daviglus, M. L., Stamler, J., et al. (2017). Metabolic Phenotyping for Discovery of Urinary Biomarkers of Diet, Xenobiotics and Blood Pressure in the INTERMAP Study: An Overview. *Hypertens. Res.* 40, 336–345. doi:10.1038/hr.2016.164

Chow, W.-H., Christman, M., Daniel, C. R., Ye, Y., Gomez, H., Dong, Q., et al. (2017). Cohort Profile: The Mexican American Mano a Mano Cohort. *Int. J. Epidemiol.* 46, e3. doi:10.1093/ije/dyv016

Ciaramelli, C., Fumagalli, M., Viglio, S., Bardoni, A. M., Piloni, D., Meloni, F., et al. (2017). 1H NMR to Evaluate the Metabolome of Bronchoalveolar Lavage Fluid (BALF) in Bronchiolitis Obliterans Syndrome (BOS): Toward the Development of a New Approach for Biomarker Identification. *J. Proteome Res.* 16, 1669–1682. doi:10.1021/acs.jproteome.6b01038

Clayton, E., Taylor, S., Wright, B., and Wilson, I. D. (1998). The Application of High Performance Liquid Chromatography, Coupled to Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry (HPLC-NMR-MS), to the Characterisation of Ibuprofen Metabolites from Human Urine. *Chromatographia* 47, 264–270. doi:10.1007/BF02466530

Clendinen, C. S., Lee-McMullen, B., Williams, C. M., Stupp, G. S., Vandenborne, K., Hahn, D. A., et al. (2014). 13C NMR Metabolomics: Applications at Natural Abundance. *Anal. Chem.* 86, 9242–9250. doi:10.1021/ac502346h

Coman, C., Solari, F. A., Hentschel, A., Sickmann, A., Zahedi, R. P., and Ahrends, R. (2016). Simultaneous Metabolite, Protein, Lipid Extraction (SIMPLEX): A Combinatorial Multimolecular Omics Approach for Systems Biology. *Mol. Cell Proteom.* 15, 1435–1466. doi:10.1074/mcp.M115.053702

Crockford, D. J., Holmes, E., Lindon, J. C., Plumb, R. S., Zirah, S., Bruce, S. J., et al. (2006). Statistical Heterospectroscopy, an Approach to the Integrated Analysis of NMR and UPLC-MS Data Sets: Application in Metabonomic Toxicology Studies. *Anal. Chem.* 78, 363–371. doi:10.1021/ac051444m

Crockford, D. J., Maher, A. D., Ahmadi, K. R., Barrett, A., Plumb, R. S., Wilson, I. D., et al. (2008). 1H NMR and UPLC-MSE Statistical Heterospectroscopy: Characterization of Drug Metabolites (Xenometabolome) in Epidemiological Studies. *Anal. Chem.* 80, 6835–6844. doi:10.1021/ac801075m

Crown, S. B., and Antoniewicz, M. R. (2013). Publishing 13C Metabolic Flux Analysis Studies: A Review and Future Perspectives. *Metab. Eng.* 20, 42–48. doi:10.1016/j.ymben.2013.08.005

Cui, L., Lu, H., and Lee, Y. H. (2018). Challenges and Emergent Solutions for LC-MS/MS Based Untargeted Metabolomics in Diseases. *Mass. Spec. Rev.* 37, 772–792. doi:10.1002/mas.21562

Cuperlovic-Culf, M., and Culf, A. S. (2016). Applied Metabolomics in Drug Discovery. *Expert Opin. Drug Discov.* 11, 759–770. doi:10.1080/17460441.2016.1195365

Curtarello, M., Tognon, M., Venturoli, C., Silic-Benussi, M., Grassi, A., Verza, M., et al. (2019). Rewiring of Lipid Metabolism and Storage in Ovarian Cancer Cells after Anti-VEGF Therapy. *Cells* 8, 1601. doi:10.3390/cells8121601

Dear, G. J., Ayrton, J., Plumb, R., Sweatman, B. C., Ismail, I. M., Fraser, I. J., et al. (1998). A Rapid and Efficient Approach to Metabolite Identification Using Nuclear Magnetic Resonance Spectroscopy, Liquid Chromatography/mass Spectrometry and Liquid Chromatography/nuclear Magnetic Resonance Spectroscopy/sequential Mass Spectrometry. *Rapid Commun. Mass Spectrom.* 12, 2023–2030.

Debik, J., Euceda, L. R., Lundgren, S., Gythfeldt, H. v. d. L., Garred, O., Borgen, E., et al. (2019). Assessing Treatment Response and Prognosis by Serum and Tissue Metabolomics in Breast Cancer Patients. *J. Proteome Res.* 18, 3649–3660. doi:10.1021/acs.jproteome.9b00316

Deelen, J., Kettunen, J., Fischer, K., van der Spek, A., Trompét, S., Kastenmüller, G., et al. (2019). A Metabolic Profile of All-Cause Mortality Risk Identified in an Observational Study of 44,168 Individuals. *Nat. Commun.* 10, 3346. doi:10.1038/s41467-019-11311-9

Deng, L., Gu, H., Zhu, J., Nagana Gowda, G. A., Djukovic, D., Chiorean, E. G., et al. (2016). Combining NMR and LC/MS Using Backward Variable Elimination: Metabolomics Analysis of Colorectal Cancer, Polyps, and Healthy Controls. *Anal. Chem.* 88, 7975–7983. doi:10.1021/acs.analchem.6b00885

Dennis, E. A. (2009). Lipidomics Joins the Omics Evolution. *Proc. Natl. Acad. Sci.* 106, 2089–2090. doi:10.1073/pnas.0812636106

Dey, A., Charrier, B., Martineau, E., Deborde, C., Gandriau, E., Moing, A., et al. (2020). Hyperpolarized NMR Metabolomics at Natural 13C Abundance. *Anal. Chem.* 92, 14867–14871. doi:10.1021/acs.analchem.0c03510

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Emwas, A.-H., Roy, R., McKay, R. T., Tenori, L., Saccenti, E., Gowda, G. A. N., et al. (2019). NMR Spectroscopy for Metabolomics Research. *Metabolites* 9, 123. doi:10.3390/metabo9070123

Everett, J. R. (2017). NMR-based Pharmacometabonomics: A New Paradigm for Personalised or Precision Medicine. *Prog. Nucl. Magn. Reson. Spectrosc.* 102-103, 1–14. doi:10.1016/j.pnmrs.2017.04.003

Fan, T. W., Lane, A. N., Higashi, R. M., Farag, M. A., Gao, H., Bousamra, M., et al. (2009). Altered Regulation of Metabolic Pathways in Human Lung Cancer Discerned by 13C Stable Isotope-Resolved Metabolomics (SIRM). *Mol. Cancer* 8, 41. doi:10.1186/1476-4598-8-41

Fan, T. W.-M., Lorkiewicz, P. K., Sellers, K., Moseley, H. N. B., Higashi, R. M., and Lane, A. N. (2012). Stable Isotope-Resolved Metabolomics and Applications for Drug Development. *Pharmacol. Ther.* 133, 366–391. doi:10.1016/j.pharmthera.2011.12.007

Féraud, B., Govaerts, B., Verleysen, M., and de Tullio, P. (2015). Statistical Treatment of 2D NMR COSY Spectra in Metabolomics: Data Preparation, Clustering-Based Evaluation of the Metabolomic Informative Content and Comparison with 1H-NMR. *Metabolomics* 11, 1756–1768. doi:10.1007/s11306-015-0830-7

Féraud, B., Leenders, J., Martineau, E., Giraudeau, P., Govaerts, B., and de Tullio, P. (2019). Two Data Pre-processing Workflows to Facilitate the Discovery of Biomarkers by 2D NMR Metabolomics. *Metabolomics* 15, 63. doi:10.1007/s11306-019-1524-3

Féraud, B., Martineau, E., Leenders, J., Govaerts, B., de Tullio, P., and Giraudeau, P. (2020). Combining Rapid 2D NMR Experiments with Novel Pre-processing Workflows and MIC Quality Measures for Metabolomics. *Metabolomics* 16, 42. doi:10.1007/s11306-020-01662-6

Fei, Q., Wang, D., Jasbi, P., Zhang, P., Nagana Gowda, G. A., Raftery, D., et al. (2019). Combining NMR and MS with Chemical Derivatization for Absolute Quantification with Reduced Matrix Effects. *Anal. Chem.* 91, 4055–4062. doi:10.1021/acs.analchem.8b05611

Finch, G., Yilmaz, A., and Utz, M. (2016). An Optimised Detector for *In-Situ* High-Resolution NMR in Microfluidic Devices. *J. Magn. Reson.* 262, 73–80. doi:10.1016/j.jmr.2015.11.011

Frédéric, M., Pirotte, B., Fillet, M., and de Tullio, P. (2016). Metabolomics as a Challenging Approach for Medicinal Chemistry and Personalized Medicine. *J. Med. Chem.* 59, 8649–8666. doi:10.1021/acs.jmedchem.5b01335

Gebretsadik, T., Linert, W., Thomas, M., Berhanu, T., and Frew, R. (2019). LC-NMR for Natural Products Analysis: A Journey from an Academic Curiosity to a Robust Analytical Tool. *Sci* 1, 31. doi:10.3390/sci1010031

Gil, M., Samino, S., Barrilero, R., and Correig, X. (2019). "Lipid Profiling Using 1H NMR Spectroscopy," in *NMR-Based Metabolomics: Methods and Protocols Methods in Molecular Biology*. Editors G. A. N. Gowda and D. Raftery (New York, NY: Springer), 35–47. doi:10.1007/978-1-4939-9690-2_3

Giraudeau, P., and Frydman, L. (2014). Ultrafast 2D NMR: An Emerging Tool in Analytical Spectroscopy. *Annu. Rev. Anal. Chem.* 7, 129–161. doi:10.1146/annurev-anchem-071213-020208

Giraudeau, P. (2020). NMR-based Metabolomics and Fluxomics: Developments and Future Prospects. *Analyst* 145, 2457–2472. doi:10.1039/D0AN00142B

Giskeødegård, G. F., Andreassen, T., Bertilsson, H., Tessem, M.-B., and Bathen, T. F. (2019). The Effect of Sampling Procedures and Day-To-Day Variations in Metabolomics Studies of Biofluids. *Analytica Chim. Acta* 1081, 93–102. doi:10.1016/j.aca.2019.07.026

Gogiahvili, M., Nowacki, J., Hergenröder, R., Hengstler, J. G., Lambert, J., and Edlund, K. (2019). HR-MAS NMR Based Quantitative Metabolomics in Breast Cancer. *Metabolites* 9, 19. doi:10.3390/metabo9020019

González-Ruiz, V., Schvartz, D., Sandström, J., Pezzatti, J., Jeanneret, F., Tonoli, D., et al. (2019). An Integrative Multi-Omics Workflow to Address Multifactorial Toxicology Experiments. *Metabolites* 9, 79. doi:10.3390/metabo9040079

Gouilleux, B., Marchand, J., Charrier, B., Remaud, G. S., and Giraudeau, P. (2018). High-throughput Authentication of Edible Oils with Benchtop Ultrafast 2D NMR. *Food Chem.* 244, 153–158. doi:10.1016/j.foodchem.2017.10.016

Gouilleux, B., Farjon, J., and Giraudeau, P. (2020). Gradient-based Pulse Sequences for Benchtop NMR Spectroscopy. *J. Magn. Reson.* 319, 106810. doi:10.1016/j.jmr.2020.106810

Goulitquer, S., Croyal, M., Lalande, J., Royer, A.-L., Guitton, Y., Arzur, D., et al. (2018). Consequences of Blunting the Mevalonate Pathway in Cancer Identified by a Pluri-Omics Approach. *Cell Death Dis.* 9, 1–12. doi:10.1038/s41419-018-0761-0

Gowda, G. A. N., and Djukovic, D. (2014). Overview of Mass Spectrometry-Based Metabolomics: Opportunities and Challenges. *Methods Mol. Biol.* 1198, 3–12. doi:10.1007/978-1-4939-1258-2_1

Gross, R. W., and Han, X. (2011). Lipidomics at the Interface of Structure and Function in Systems Biology. *Chem. Biol.* 18, 284–291. doi:10.1016/j.chembiol.2011.01.014

Gu, H., Pan, Z., Xi, B., Asiago, V., Musselman, B., and Raftery, D. (2011). Principal Component Directed Partial Least Squares Analysis for Combining Nuclear Magnetic Resonance and Mass Spectrometry Data in Metabolomics: Application to the Detection of Breast Cancer. *Analytica Chim. Acta* 686, 57–63. doi:10.1016/j.aca.2010.11.040

Guo, R., Chen, Y., Borgard, H., Jijiwa, M., Nasu, M., He, M., et al. (2020). The Function and Mechanism of Lipid Molecules and Their Roles in the Diagnosis and Prognosis of Breast Cancer. *Molecules* 25, 4864. doi:10.3390/molecules2504864

Hao, J., Astle, W., De Iorio, M., and Ebbels, T. M. D. (2012). BATMAN--an R Package for the Automated Quantification of Metabolites from Nuclear Magnetic Resonance Spectra Using a Bayesian Model. *Bioinformatics* 28, 2088–2090. doi:10.1093/bioinformatics/bts308

Hermkens, N. K. J., Eshuis, N., van Weerdenburg, B. J. A., Feiters, M. C., Rutjes, F. P. J. T., Wijmenga, S. S., et al. (2016). NMR-Based Chemosensing via P-H2 Hyperpolarization: Application to Natural Extracts. *Anal. Chem.* 88, 3406–3412. doi:10.1021/acs.analchem.6b00184

Holzgrabe, U., Deubner, R., Schollmayer, C., and Waibel, B. (2005). Quantitative NMR Spectroscopy-Applications in Drug Analysis. *J. Pharm. Biomed. Anal.* 38, 806–812. doi:10.1016/j.jpba.2005.01.050

Hu, R., Li, T., Yang, Y., Tian, Y., and Zhang, L. (2021). "NMR-Based Metabolomics in Cancer Research," in *Cancer Metabolomics: Methods And Applications Advances in Experimental Medicine and Biology*. Editor S. Hu (Cham: Springer International Publishing), 201–218. doi:10.1007/978-3-030-51652-9_14

Huart, J., Leenders, J., Taminiau, B., Descy, J., Saint-Remy, A., Daube, G., et al. (2019). Gut Microbiota and Fecal Levels of Short-Chain Fatty Acids Differ upon 24-Hour Blood Pressure Levels in Men. *Hypertension* 74, 1005–1013. doi:10.1161/HYPERTENSIONAHA.118.12588

Huart, J., Cirillo, A., Saint-Remy, A., Krzesinski, J.-M., de Tullio, P., and Jouret, F. (2021a). The Faecal Abundance of Short Chain Fatty Acids Is Increased in Men with a Non-dipping Blood Pressure Profile. *Acta Cardiol.* 76, 1–4. doi:10.1080/00015385.2021.1901020

Huart, J., Cirillo, A., Taminiau, B., Descy, J., Saint-Remy, A., Daube, G., et al. (2021b). Human Stool Metabolome Differs upon 24 H Blood Pressure Levels and Blood Pressure Dipping Status: A Prospective Longitudinal Study. *Metabolites* 11, 282. doi:10.3390/metabo11050282

Izquierdo-Garcia, J. L., Comella-del-Barrio, P., Campos-Olivas, R., Villar-Hernández, R., Prat-Aymerich, C., De Souza-Galvão, M. L., et al. (2020). Discovery and Validation of an NMR-Based Metabolomic Profile in Urine as TB Biomarker. *Sci. Rep.* 10, 22317. doi:10.1038/s41598-020-78999-4

Jacob, M., Lopata, A. L., Dasouki, M., and Abdel Rahman, A. M. (2019). Metabolomics toward Personalized Medicine. *Mass. Spec. Rev.* 38, 221–238. doi:10.1002/mas.21548

Ji, X., Bornet, A., Vuichoud, B., Milani, J., Gajan, D., Rossini, A. J., et al. (2017). Transportable Hyperpolarized Metabolites. *Nat. Commun.* 8, 13975. doi:10.1038/ncomms13975

Jiménez, B., Holmes, E., Heude, C., Tolson, R. F., Harvey, N., Lodge, S. L., et al. (2018). Quantitative Lipoprotein Subclass and Low Molecular Weight Metabolite Analysis in Human Serum and Plasma by 1H NMR Spectroscopy in a Multilaboratory Trial. *Anal. Chem.* 90, 11962–11971. doi:10.1021/acs.analchem.8b02412

Jobard, E., Trédan, O., Bachelot, T., Vigneron, A. M., Aït-Oukhatar, C. M., Arnedos, M., et al. (2017). Longitudinal Serum Metabolomics Evaluation of Trastuzumab and Everolimus Combination as Pre-operative Treatment for
Emwas, A.-H., Roy, R., McKay, R. T., Ryan, D., Brennan, L., Tenori, L., et al. (2016). Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis. *J. Proteome Res.* 15, 360–373. doi:10.1021/acs.jproteome.5b00885

Emwas, A.-H., Roy, R., McKay, R. T., Tenori, L., Saccenti, E., Gowda, G. A. N., et al. (2019). NMR Spectroscopy for Metabolomics Research. *Metabolites* 9, 123. doi:10.3390/metabo9070123

Everett, J. R. (2017). NMR-based Pharmacometabonomics: A New Paradigm for Personalised or Precision Medicine. *Prog. Nucl. Magn. Reson. Spectrosc.* 102-103, 1–14. doi:10.1016/j.pnmrs.2017.04.003

Fan, T. W., Lane, A. N., Higashi, R. M., Farag, M. A., Gao, H., Bousamra, M., et al. (2009). Altered Regulation of Metabolic Pathways in Human Lung Cancer Discerned by 13C Stable Isotope-Resolved Metabolomics (SIRM). *Mol. Cancer* 8, 41. doi:10.1186/1476-4598-8-41

Fan, T. W.-M., Lorkiewicz, P. K., Sellers, K., Moseley, H. N. B., Higashi, R. M., and Lane, A. N. (2012). Stable Isotope-Resolved Metabolomics and Applications for Drug Development. *Pharmacol. Ther.* 133, 366–391. doi:10.1016/j.pharmthera.2011.12.007

Féraud, B., Govaerts, B., Verleysen, M., and de Tullio, P. (2015). Statistical Treatment of 2D NMR COSY Spectra in Metabolomics: Data Preparation, Clustering-Based Evaluation of the Metabolomic Informative Content and Comparison with 1H-NMR. *Metabolomics* 11, 1756–1768. doi:10.1007/s11306-015-0830-7

Féraud, B., Leenders, J., Martineau, E., Giraudeau, P., Govaerts, B., and de Tullio, P. (2019). Two Data Pre-processing Workflows to Facilitate the Discovery of Biomarkers by 2D NMR Metabolomics. *Metabolomics* 15, 63. doi:10.1007/s11306-019-1524-3

Féraud, B., Martineau, E., Leenders, J., Govaerts, B., de Tullio, P., and Giraudeau, P. (2020). Combining Rapid 2D NMR Experiments with Novel Pre-processing Workflows and MIC Quality Measures for Metabolomics. *Metabolomics* 16, 42. doi:10.1007/s11306-020-01662-6

Fei, Q., Wang, D., Jasbi, P., Zhang, P., Nagana Gowda, G. A., Raftery, D., et al. (2019). Combining NMR and MS with Chemical Derivatization for Absolute Quantification with Reduced Matrix Effects. *Anal. Chem.* 91, 4055–4062. doi:10.1021/acs.analchem.8b05611

Finch, G., Yilmaz, A., and Utz, M. (2016). An Optimised Detector for *In-Situ* High-Resolution NMR in Microfluidic Devices. *J. Magn. Reson.* 262, 73–80. doi:10.1016/j.jmr.2015.11.011

Frédéric, M., Pirotte, B., Fillet, M., and de Tullio, P. (2016). Metabolomics as a Challenging Approach for Medicinal Chemistry and Personalized Medicine. *J. Med. Chem.* 59, 8649–8666. doi:10.1021/acs.jmedchem.5b01335

Gebretsadik, T., Linert, W., Thomas, M., Berhanu, T., and Frew, R. (2019). LC-NMR for Natural Products Analysis: A Journey from an Academic Curiosity to a Robust Analytical Tool. *Sci* 1, 31. doi:10.3390/sci1010031

Gil, M., Samino, S., Barrilero, R., and Correig, X. (2019). "Lipid Profiling Using 1H NMR Spectroscopy," in *NMR-Based Metabolomics: Methods and Protocols Methods in Molecular Biology*. Editors G. A. N. Gowda and D. Raftery (New York, NY: Springer), 35–47. doi:10.1007/978-1-4939-9690-2_3

Giraudeau, P., and Frydman, L. (2014). Ultrafast 2D NMR: An Emerging Tool in Analytical Spectroscopy. *Annu. Rev. Anal. Chem.* 7, 129–161. doi:10.1146/annurev-anchem-071213-020208

Giraudeau, P. (2020). NMR-based Metabolomics and Fluxomics: Developments and Future Prospects. *Analyst* 145, 2457–2472. doi:10.1039/D0AN00142B

Giskeødegård, G. F., Andreassen, T., Bertilsson, H., Tessem, M.-B., and Bathen, T. F. (2019). The Effect of Sampling Procedures and Day-To-Day Variations in Metabolomics Studies of Biofluids. *Analytica Chim. Acta* 1081, 93–102. doi:10.1016/j.aca.2019.07.026

Gogiahvili, M., Nowacki, J., Hergenröder, R., Hengstler, J. G., Lambert, J., and Edlund, K. (2019). HR-MAS NMR Based Quantitative Metabolomics in Breast Cancer. *Metabolites* 9, 19. doi:10.3390/metabo9020019

González-Ruiz, V., Schvartz, D., Sandström, J., Pezzatti, J., Jeanneret, F., Tonoli, D., et al. (2019). An Integrative Multi-Omics Workflow to Address Multifactorial Toxicology Experiments. *Metabolites* 9, 79. doi:10.3390/metabo9040079

Gouilleux, B., Marchand, J., Charrier, B., Remaud, G. S., and Giraudeau, P. (2018). High-throughput Authentication of Edible Oils with Benchtop Ultrafast 2D NMR. *Food Chem.* 244, 153–158. doi:10.1016/j.foodchem.2017.10.016

Gouilleux, B., Farjon, J., and Giraudeau, P. (2020). Gradient-based Pulse Sequences for Benchtop NMR Spectroscopy. *J. Magn. Reson.* 319, 106810. doi:10.1016/j.jmr.2020.106810

Goulitquer, S., Croyal, M., Lalande, J., Royer, A.-L., Guitton, Y., Arzur, D., et al. (2018). Consequences of Blunting the Mevalonate Pathway in Cancer Identified by a Pluri-Omics Approach. *Cell Death Dis.* 9, 1–12. doi:10.1038/s41419-018-0761-0

Gowda, G. A. N., and Djukovic, D. (2014). Overview of Mass Spectrometry-Based Metabolomics: Opportunities and Challenges. *Methods Mol. Biol.* 1198, 3–12. doi:10.1007/978-1-4939-1258-2_1

Gross, R. W., and Han, X. (2011). Lipidomics at the Interface of Structure and Function in Systems Biology. *Chem. Biol.* 18, 284–291. doi:10.1016/j.chembiol.2011.01.014

Gu, H., Pan, Z., Xi, B., Asiago, V., Musselman, B., and Raftery, D. (2011). Principal Component Directed Partial Least Squares Analysis for Combining Nuclear Magnetic Resonance and Mass Spectrometry Data in Metabolomics: Application to the Detection of Breast Cancer. *Analytica Chim. Acta* 686, 57–63. doi:10.1016/j.aca.2010.11.040

Guo, R., Chen, Y., Borgard, H., Jijiwa, M., Nasu, M., He, M., et al. (2020). The Function and Mechanism of Lipid Molecules and Their Roles in the Diagnosis and Prognosis of Breast Cancer. *Molecules* 25, 4864. doi:10.3390/molecules2504864

Hao, J., Astle, W., De Iorio, M., and Ebbels, T. M. D. (2012). BATMAN--an R Package for the Automated Quantification of Metabolites from Nuclear Magnetic Resonance Spectra Using a Bayesian Model. *Bioinformatics* 28, 2088–2090. doi:10.1093/bioinformatics/bts308

Hermkens, N. K. J., Eshuis, N., van Weerdenburg, B. J. A., Feiters, M. C., Rutjes, F. P. J. T., Wijmenga, S. S., et al. (2016). NMR-Based Chemosensing via P-H2 Hyperpolarization: Application to Natural Extracts. *Anal. Chem.* 88, 3406–3412. doi:10.1021/acs.analchem.6b00184

Holzgrabe, U., Deubner, R., Schollmayer, C., and Waibel, B. (2005). Quantitative NMR Spectroscopy-Applications in Drug Analysis. *J. Pharm. Biomed. Anal.* 38, 806–812. doi:10.1016/j.jpba.2005.01.050

Hu, R., Li, T., Yang, Y., Tian, Y., and Zhang, L. (2021). "NMR-Based Metabolomics in Cancer Research," in *Cancer Metabolomics: Methods And Applications Advances in Experimental Medicine and Biology*. Editor S. Hu (Cham: Springer International Publishing), 201–218. doi:10.1007/978-3-030-51652-9_14

Huart, J., Leenders, J., Taminiau, B., Descy, J., Saint-Remy, A., Daube, G., et al. (2019). Gut Microbiota and Fecal Levels of Short-Chain Fatty Acids Differ upon 24-Hour Blood Pressure Levels in Men. *Hypertension* 74, 1005–1013. doi:10.1161/HYPERTENSIONAHA.118.12588

Huart, J., Cirillo, A., Saint-Remy, A., Krzesinski, J.-M., de Tullio, P., and Jouret, F. (2021a). The Faecal Abundance of Short Chain Fatty Acids Is Increased in Men with a Non-dipping Blood Pressure Profile. *Acta Cardiol.* 76, 1–4. doi:10.1080/00015385.2021.1901020

Huart, J., Cirillo, A., Taminiau, B., Descy, J., Saint-Remy, A., Daube, G., et al. (2021b). Human Stool Metabolome Differs upon 24 H Blood Pressure Levels and Blood Pressure Dipping Status: A Prospective Longitudinal Study. *Metabolites* 11, 282. doi:10.3390/metabo11050282

Izquierdo-Garcia, J. L., Comella-del-Barrio, P., Campos-Olivas, R., Villar-Hernández, R., Prat-Aymerich, C., De Souza-Galvão, M. L., et al. (2020). Discovery and Validation of an NMR-Based Metabolomic Profile in Urine as TB Biomarker. *Sci. Rep.* 10, 22317. doi:10.1038/s41598-020-78999-4

Jacob, M., Lopata, A. L., Dasouki, M., and Abdel Rahman, A. M. (2019). Metabolomics toward Personalized Medicine. *Mass. Spec. Rev.* 38, 221–238. doi:10.1002/mas.21548

Ji, X., Bornet, A., Vuichoud, B., Milani, J., Gajan, D., Rossini, A. J., et al. (2017). Transportable Hyperpolarized Metabolites. *Nat. Commun.* 8, 13975. doi:10.1038/ncomms13975

Jiménez, B., Holmes, E., Heude, C., Tolson, R. F., Harvey, N., Lodge, S. L., et al. (2018). Quantitative Lipoprotein Subclass and Low Molecular Weight Metabolite Analysis in Human Serum and Plasma by 1H NMR Spectroscopy in a Multilaboratory Trial. *Anal. Chem.* 90, 11962–11971. doi:10.1021/acs.analchem.8b02412

Jobard, E., Trédan, O., Bachelot, T., Vigneron, A. M., Aït-Oukhatar, C. M., Arnedos, M., et al. (2017). Longitudinal Serum Metabolomics Evaluation of Trastuzumab and Everolimus Combination as Pre-operative Treatment for
HER-2 Positive Breast Cancer Patients. *Oncotarget* 8, 83570-83584. doi:10.18632/oncotarget.18784

Johnson, H., Puppa, M., Merwe, M., and Tipirneni-Sajja, A. (2021). CRAFT for NMR Lipidomics: Targeting Lipid Metabolism in Leucine-supplemented Tumor-bearing Mice. *Magn. Reson. Chem.* 59, 138–146. doi:10.1002/mrc.5092

Jung, Y.-S., Hyeon, J.-S., and Hwang, G.-S. (2016). Software-assisted Serum Metabolite Quantification Using NMR. *Analytica Chim. Acta* 934, 194–202. doi:10.1016/j.aca.2016.04.054

Juwowski, K., Kochan, K., Walczak, J., Barańska, M., Piekoszewski, W., and Buszewski, B. (2017). Analytical Techniques in Lipidomics: State of the Art. *Crit. Rev. Anal. Chem.* 47, 418–437. doi:10.1080/10408347.2017.1310613

Karaman, İ., Norskov, N. P., Yde, C. C., Hedemann, M. S., Bach Knudsen, K. E., and Kohler, A. (2015). Sparse Multi-Block PLSR for Biomarker Discovery when Integrating Data from LC-MS and NMR Metabolomics. *Metabolomics* 11, 367–379. doi:10.1007/s11306-014-0698-y

Kelly, R. S., Giorgio, R. T., Chawes, B. L., Palacios, N. I., Gray, K. J., Mirzakhani, H., et al. (2017). Applications of Metabolomics in the Study and Management of Preeclampsia: A Review of the Literature. *Metabolomics* 13, 86. doi:10.1007/s11306-017-1225-8

Khakimov, B., Mobaraki, N., Trimigno, A., Aru, V., and Engelsen, S. B. (2020). Signature Mapping (SigMa): An Efficient Approach for Processing Complex Human Urine 1H NMR Metabolomics Data. *Analytica Chim. Acta* 1108, 142–151. doi:10.1016/j.aca.2020.02.025

Kim, H. K., Kostidis, S., and Choi, Y. H. (2018). NMR Analysis of Fecal Samples. *Methods Mol. Biol.* 1730, 317–328. doi:10.1007/978-1-4939-7592-1_24

Kohler, I., Verhoeven, A., Derks, R. J., and Giera, M. (2016). Analytical Pitfalls and Challenges in Clinical Metabolomics. *Bioanalysis* 8, 1509–1532. doi:10.4155/bio-2016-0090

Kohler, I., Hankemeier, T., van der Graaf, P. H., Knibbe, C. A. J., and van Hasselt, J. G. C. (2017). Integrating Clinical Metabolomics-Based Biomarker Discovery and Clinical Pharmacology to Enable Precision Medicine. *Eur. J. Pharm. Sci.* 109, S15-S21. doi:10.1021/ejps.2017.05.018

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Kostara, C. E., Tsimihodimos, V., Elisaf, M. S., and Bairaktari, E. T. (2017). NMR-Based Lipid Profiling of High Density Lipoprotein Particles in Healthy Subjects with Low, Normal, and Elevated HDL-Cholesterol. *J. Proteome Res.* 16, 1605–1616. doi:10.1021/acs.jproteome.6b00975

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Labaki, W. W., Gu, T., Murray, S., Curtis, J. L., Yeomans, L., Bowler, R. P., et al. (2019). Serum Amino Acid Concentrations and Clinical Outcomes in Smokers: SPIROMICS Metabolomics Study. *Sci. Rep.* 9, 11367. doi:10.1038/s41598-019-47761-w

Lacy, P., McKay, R. T., Finkel, M., Karnovsky, A., Woehler, S., Lewis, M. J., et al. (2014). Signal Intensities Derived from Different NMR Probes and Parameters Contribute to Variations in Quantification of Metabolites. *PLOS ONE* 9, e85732. doi:10.1371/journal.pone.0085732

Lambert, V., Hansen, S., Schoumacher, M., Lecomte, J., Leenders, J., Hubert, P., et al. (2020). Pyruvate Dehydrogenase Kinase/lactate axis: a Therapeutic Target for Neovascular Age-Related Macular Degeneration Identified by Metabolomics. *J. Mol. Med.* 98, 1737–1751. doi:10.1007/s00109-020-01994-9

Lane, A. N., and Fan, T. W.-M. (2017). NMR-based Stable Isotope Resolved Metabolomics in Systems Biochemistry. *Arch. Biochem. Biophys.* 628, 123–131. doi:10.1016/j.abb.2017.02.009

Lane, A. N., Fan, T. W.-M., Bousamra, M., Higashi, R. M., Yan, J., and Miller, D. M. (2011). Stable Isotope-Resolved Metabolomics (SIRM) in Cancer Research with Clinical Application to NonSmall Cell Lung Cancer. *OMICS: A J. Integr. Biol.* 15, 173–182. doi:10.1089/omi.2010.0088

Lane, A. N., Higashi, R. M., and Fan, T. W.-M. (2016). Preclinical Models for Interrogating Drug Action in Human Cancers Using Stable Isotope Resolved Metabolomics (SIRM). *Metabolomics* 12, 118. doi:10.1007/s11306-016-1065-y

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Leaptrot, K. L., May, J. C., Dodds, J. N., and McLean, J. A. (2019). Ion Mobility Conformational Lipid Atlas for High Confidence Lipidomics. *Nat. Commun.* 10, 985. doi:10.1038/s41467-019-08897-5

Lee, K.-M., Jeon, J.-Y., Lee, B.-J., Lee, H., and Choi, H.-K. (2017). Application of Metabolomics to Quality Control of Natural Product Derived Medicines. *Biomol. Ther.* 25, 559–568. doi:10.4062/biomolther.2016.249

Leenders, J., Grootveld, M., Percival, B., Gibson, M., Casanova, F., and Wilson, P. B. (2020). Benchtop Low-Frequency 60 MHz NMR Analysis of Urine: A Comparative Metabolomics Investigation. *Metabolites* 10, 155. doi:10.3390/metabo10040155

Lerche, M. H., Yigit, D., Frahm, A. B., Ardenkjaer-Larsen, J. H., Malinowski, R. M., and Jensen, P. R. (2017). Stable Isotope-Resolved Analysis with Quantitative Dissolution Dynamic Nuclear Polarization. *Anal. Chem.* 90, 674–678. doi:10.1021/acs.analchem.7b02779

Letertre, M. P. M., Dervilly, G., and Giraudeau, P. (2021). Combined Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry Approaches for Metabolomics. *Anal. Chem.* 93, 500–518. doi:10.1021/acs.analchem.0c04371

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Li, S., Tian, Y., Jiang, P., Lin, Y., Liu, X., and Yang, H. (2021). Recent Advances in the Application of Metabolomics for Food Safety Control and Food Quality Analyses. *Crit. Rev. Food Sci. Nutr.* 61, 1448–1469. doi:10.1080/10408398.2020.1761287

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Lopez, J. M., Cabrera, R., and Maruenda, H. (2019). Ultra-Clean Pure Shift 1H-NMR Applied to Metabolomics Profiling. *Sci. Rep.* 9, 6900. doi:10.1038/s41598-019-43374-5

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Lee, K.-M., Jeon, J.-Y., Lee, B.-J., Lee, H., and Choi, H.-K. (2017). Application of Metabolomics to Quality Control of Natural Product Derived Medicines. *Biomol. Ther.* 25, 559–568. doi:10.4062/biomolther.2016.249

Leenders, J., Grootveld, M., Percival, B., Gibson, M., Casanova, F., and Wilson, P. B. (2020). Benchtop Low-Frequency 60 MHz NMR Analysis of Urine: A Comparative Metabolomics Investigation. *Metabolites* 10, 155. doi:10.3390/metabo10040155

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Letertre, M. P. M., Dervilly, G., and Giraudeau, P. (2021). Combined Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry Approaches for Metabolomics. *Anal. Chem.* 93, 500–518. doi:10.1021/acs.analchem.0c04371

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**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

**Publisher's Note:** All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Copyright © 2021 Letertre, Giraudeau and de Tullio. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Verhoeven, A., Slagboom, E., Wuhrer, M., Giera, M., and Mayboroda, O. A. (2017). Automated Quantification of Metabolites in Blood-Derived Samples by NMR. *Analytica Chim. Acta* 976, 52–62. doi:10.1016/j.aca.2017.04.013

Viant, M. R. (2009). Applications of Metabolomics to the Environmental Sciences. *Metabolomics* 5, 1–2. doi:10.1007/s11306-009-0157-3

Vignoli, A., Ghini, V., Meoni, G., Licari, C., Takis, P. G., Tenori, L., et al. (2019a). High-Throughput Metabolomics by 1D NMR. *Angew. Chem. Int. Ed.* 58, 968–994. doi:10.1002/anie.201804736

Vignoli, A., Tenori, L., Giusti, B., Takis, P. G., Valente, S., Carrabba, N., et al. (2019b). NMR-based Metabolomics Identifies Patients at High Risk of Death within Two Years after Acute Myocardial Infarction in the AMI-Florence II Cohort. *BMC Med.* 17, 3. doi:10.1186/s12916-018-1240-2

Vignoli, A., Risi, E., McCartney, A., Migliaccio, I., Moretti, E., Malorni, L., et al. (2021). Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer. *Int. J. Mol. Sci.* 22, 4687. doi:10.3390/ijms22094687

Wallmeier, J., Samol, C., Ellmann, L., Zacharias, H. U., Vogl, F. C., Garcia, M., et al. (2017). Quantification of Metabolites by NMR Spectroscopy in the Presence of Protein. *J. Proteome Res.* 16, 1784–1796. doi:10.1021/acs.jproteome.7b00057

Wang, C., Zhang, B., Timári, I., Somogyi, Á., Li, D.-W., Adcox, H. E., et al. (2019). Accurate and Efficient Determination of Unknown Metabolites in Metabolomics by NMR-Based Molecular Motif Identification. *Anal. Chem.* 91, 15686–15693. doi:10.1021/acs.analchem.9b03849

Wang, C., Timári, I., Zhang, B., Li, D.-W., Leggett, A., Amer, A. O., et al. (2020). COLMAR Lipids Web Server and Ultrahigh-Resolution Methods for Two-Dimensional Nuclear Magnetic Resonance- and Mass Spectrometry-Based Lipidomics. *J. Proteome Res.* 19, 1674–1683. doi:10.1021/acs.jproteome.9b00845

Welsh, P., Rankin, N., Li, Q., Mark, P. B., Würtz, P., Ala-Korpela, M., et al. (2018). Circulating Amino Acids and the Risk of Macrovascular, Microvascular and Mortality Outcomes in Individuals with Type 2 Diabetes: Results from the ADVANCE Trial. *Diabetologia* 61, 1581–1591. doi:10.1007/s00125-018-4619-x

Wilson, D. M., Keshari, K. R., Larson, P. E. Z., Chen, A. P., Hu, S., Criekinge, M. V., et al. (2010). Multi-compound Polarization by DNP Allows Simultaneous Assessment of Multiple Enzymatic Activities *In Vivo*. *J. Magn. Reson.* 205, 141–147. doi:10.1016/j.jmr.2010.04.012

Wishart, D. S. (2016). Emerging Applications of Metabolomics in Drug Discovery and Precision Medicine. *Nat. Rev. Drug Discov.* 15, 473–484. doi:10.1038/nrd.2016.32

Wishart, D. S. (2019). NMR Metabolomics: A Look Ahead. *J. Magn. Reson.* 306, 155–161. doi:10.1016/j.jmr.2019.07.013

Yao, X., Cao, D., Wang, F., Zhang, W., Ma, C., and Song, M. (2019). An Overview of Omics Approaches to Characterize the Effect of Perfluoroalkyl Substances in Environmental Health. *TrAC Trends Anal. Chem.* 121, 115367. doi:10.1016/j.trac.2018.12.021

Yu, K.-H., and Snyder, M. (2016). Omics Profiling in Precision Oncology. *Mol. Cell Proteomics* 15, 2525–2536. doi:10.1074/mcp.O116.059253

Yu, B., Zanetti, K. A., Temprosa, M., Albanes, D., Appel, N., Barrera, C. B., et al. (2019). The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies. *Am. J. Epidemiol.* 188, 991–1012. doi:10.1093/aje/kwz028

Zacharias, H., Altenbuchinger, M., and Gronwald, W. (2018). Statistical Analysis of NMR Metabolic Fingerprints: Established Methods and Recent Advances. *Metabolites* 8, 47. doi:10.3390/metabo8030047

Zhang, B., Xie, M., Bruschweiler-Li, L., and Brüschweiler, R. (2016). Nanoparticle-Assisted Removal of Protein in Human Serum for Metabolomics Studies. *Anal. Chem.* 88, 1003–1007. doi:10.1021/acs.analchem.5b03889

Zimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R., and Goodman, A. L. (2019). Mapping Human Microbiome Drug Metabolism by Gut Bacteria and Their Genes. *Nature* 570, 462–467. doi:10.1038/s41586-019-1291-3

Zlatkis, A., and Liebich, H. M. (1971). Profile of Volatile Metabolites in Human Urine. *Clin. Chem.* 17, 592–594. doi:10.1093/clinchem/17.7.592

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

**Publisher's Note:** All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Copyright © 2021 Letertre, Giraudeau and de Tullio. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.