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NMR-Based Metabolomics pp 453–470Cite as

Processing and Analysis of Untargeted Multicohort NMR Data

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 2037))

Abstract

NMR data from large studies combining multiple cohorts is becoming common in large-scale metabolomics. The data size and combination of cohorts with diverse properties leads to special problems for data processing and analysis. These include alignment, normalization, detection and removal of outliers, presence of strong correlations, and the identification of unknowns. Nonetheless, these challenges can be addressed with suitable algorithms and techniques, leading to enhanced data sets ripe for further data mining.

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References

  1. Albanes D, Moore S, Ulrich C, Stolzenberg-Solomon R, Poole E, Temprosa M et al (2017) COnsortium for METabolomics studies (COMETS): leveraging resources to accelerate scientific discovery. FASEB J 30(1):lb129

    Google Scholar 

  2. Soininen P, Kangas AJ, Wurtz P, Suna T, Ala-Korpela M (2015) Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics. Circ Cardiovasc Genet 8(1):192–206

    Article  CAS  PubMed  Google Scholar 

  3. Elliott P, Posma JM, Chan Q, Garcia-Perez I, Wijeyesekera A, Bictash M et al (2015) Urinary metabolic signatures of human adiposity. Sci Transl Med 7(285):285ra62

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Holmes E, Loo RL, Stamler J, Bictash M, Yap IK, Chan Q et al (2008) Human metabolic phenotype diversity and its association with diet and blood pressure. Nature 453(7193):396–400

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Keun HC, Ebbels TM, Antti H, Bollard ME, Beckonert O, Schlotterbeck G et al (2002) Analytical reproducibility in (1)H NMR-based metabonomic urinalysis. Chem Res Toxicol 15(11):1380–1386

    Article  CAS  PubMed  Google Scholar 

  6. Dumas ME, Maibaum EC, Teague C, Ueshima H, Zhou B, Lindon JC et al (2006) Assessment of analytical reproducibility of (1)H NMR spectroscopy based metabonomics for large-scale epidemiological research: the INTERMAP study. Anal Chem 78(7):2199–2208

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Dona AC, Jimenez B, Schafer H, Humpfer E, Spraul M, Lewis MR et al (2014) Precision high-throughput proton NMR spectroscopy of human urine, serum, and plasma for large-scale metabolic phenotyping. Anal Chem 86(19):9887–9894

    Article  CAS  PubMed  Google Scholar 

  8. Viant MR, Bearden DW, Bundy JG, Burton IW, Collette TW, Ekman DR et al (2009) International NMR-based environmental metabolomics intercomparison exercise. Environ Sci Technol 43(1):219–225

    Article  CAS  PubMed  Google Scholar 

  9. Jimenez B, Holmes E, Heude C, Tolson RFM, Harvey N, Lodge SL 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(20):11962–11971

    Article  CAS  PubMed  Google Scholar 

  10. Karaman I, Ferreira DL, Boulange CL, Kaluarachchi MR, Herrington D, Dona AC et al (2016) Workflow for integrated processing of multicohort untargeted 1H NMR metabolomics data in large-scale metabolic epidemiology. J Proteome Res 15(12):4188–4194

    Article  CAS  PubMed  Google Scholar 

  11. Chambers JC, Obeid OA, Refsum H, Ueland P, Hackett D, Hooper J et al (2000) Plasma homocysteine concentrations and risk of coronary heart disease in UK Indian Asian and European men. Lancet 355(9203):523–527

    Article  CAS  PubMed  Google Scholar 

  12. Bild DE, Bluemke DA, Burke GL, Detrano R, Diez Roux AV, Folsom AR et al (2002) Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol 156(9):871–881

    Article  PubMed  Google Scholar 

  13. Ikram MA, Brusselle GGO, Murad SD, van Duijn CM, Franco OH, Goedegebure A et al (2018) The Rotterdam study: 2018 update on objectives, design and main results. Eur J Epidemiol 32(9):807–850

    Article  Google Scholar 

  14. Beckonert O, Keun HC, Ebbels TM, Bundy J, Holmes E, Lindon JC et al (2007) Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nat Protoc 2(11):2692–2703

    Article  CAS  PubMed  Google Scholar 

  15. Karakach TK, Wentzell PD, Walter JA (2009) Characterization of the measurement error structure in 1D 1H NMR data for metabolomics studies. Anal Chim Acta 636(2):163–174

    Article  CAS  PubMed  Google Scholar 

  16. Tredwell GD, Bundy JG, De Iorio M, Ebbels TMD (2016) Modelling the acid/base 1H NMR chemical shift limits of metabolites in human urine. Metabolomics 12(10):1–10

    Article  CAS  Google Scholar 

  17. Pearce JTM, Athersuch TJ, Ebbels TMD, Lindon JC, Nicholson JK, Keun HC (2008) Robust algorithms for automated chemical shift calibration of 1D 1H NMR spectra of blood serum. Anal Chem 80(18):7158–7162

    Article  CAS  PubMed  Google Scholar 

  18. Veselkov K, Lindon J, Ebbels T, Volynkin V, Crockford D, Holmes E et al (2009) Recursive segment-wise peak alignment of biological 1H NMR spectra for improved metabolic biomarker recovery. Anal Chem 81(1):56–66

    Article  CAS  PubMed  Google Scholar 

  19. Blaise BJ, Shintu L, Elena B, Emsley L, Dumas M-E, Toulhoat P (2009) Statistical recoupling prior to significance testing in nuclear magnetic resonance based metabonomics. Anal Chem 81(15):6242–6251

    Article  CAS  PubMed  Google Scholar 

  20. Sousa SAA, Magalh+úes A, Ferreira MMC (2013) Optimized bucketing for NMR spectra: three case studies. Chemom Intell Lab Syst 122(0):93–102

    Article  CAS  Google Scholar 

  21. Hao J, Astle W, De Iorio M, Ebbels TM (2012) BATMAN--an R package for the automated quantification of metabolites from nuclear magnetic resonance spectra using a Bayesian model. Bioinformatics 28(15):2088–2090

    Article  CAS  PubMed  Google Scholar 

  22. Ravanbakhsh S, Liu P, Bjordahl TC, Mandal R, Grant JR, Wilson M et al (2015) Accurate, fully-automated NMR spectral profiling for metabolomics. PLoS One 10(5):e0124219

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Dieterle F, Ross A, Schlotterbeck G, Senn H (2006) Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in H-1 NMR metabonomics. Anal Chem 78(13):4281–4290

    Article  CAS  PubMed  Google Scholar 

  24. Kohl S, Klein M, Hochrein J, Oefner P, Spang R, Gronwald W (2012) State-of-the art data normalization methods improve NMR-based metabolomic analysis. Metabolomics 8(1):146–160

    Article  CAS  PubMed  Google Scholar 

  25. Craig A, Cloarec O, Holmes E, Nicholson JK, Lindon JC (2006) Scaling and normalization effects in NMR spectroscopic metabonomic data sets. Anal Chem 78(7):2262–2267

    Article  CAS  PubMed  Google Scholar 

  26. Sysi-Aho M, Katajamaa M, Yetukuri L, Orešič M (2007) Normalization method for metabolomics data using optimal selection of multiple internal standards. BMC Bioinformatics 8(1):1–17

    Article  CAS  Google Scholar 

  27. Bro R, Smilde AK (2014) Principal component analysis. Anal Methods 6(9):2812–2831

    Article  CAS  Google Scholar 

  28. van Velzen EJJ, Westerhuis JA, Van Duynhoven JPM, Van Dorsten FA, Hoefsloot HCJ, Jacobs DM et al (2008) Multilevel data analysis of a crossover designed human nutritional intervention study. J Proteome Res 7(10):4483–4491

    Article  PubMed  CAS  Google Scholar 

  29. Karaman İ, Nørskov NP, Yde CC, Hedemann MS, Bach Knudsen KE, Kohler A (2015) Sparse multi-block PLSR for biomarker discovery when integrating data from LC–MS and NMR metabolomics. Metabolomics 11(2):367–379

    Article  CAS  Google Scholar 

  30. Couto Alves A, Rantalainen M, Holmes E, Nicholson JK, Ebbels TMD (2009) Analytic properties of statistical total correlation spectroscopy (STOCSY) based information recovery in 1H NMR metabolic data sets. Anal Chem 81(6):2075–2084

    Article  CAS  Google Scholar 

  31. Chadeau-Hyam M, Ebbels TM, Brown IJ, Chan Q, Stamler J, Huang CC et al (2010) Metabolic profiling and the metabolome-wide association study: significance level for biomarker identification. J Proteome Res 9(9):4620–4627

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Castagne R, Boulange CL, Karaman I, Campanella G, Santos Ferreira DL, Kaluarachchi MR et al (2017) Improving visualization and interpretation of metabolome-wide association studies: an application in a population-based cohort using untargeted (1)H NMR metabolic profiling. J Proteome Res 16(10):3623–3633

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Filntisi A, Fotakis C, Asvestas P, Matsopoulos GK, Zoumpoulakis P, Cavouras D (2017) Automated metabolite identification from biological fluid 1H NMR spectra. Metabolomics 13(12):146

    Article  CAS  Google Scholar 

  34. Takis PG, Schäfer H, Spraul M, Luchinat C (2017) Deconvoluting interrelationships between concentrations and chemical shifts in urine provides a powerful analysis tool. Nat Commun 8(1):1662

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Tardivel PJC, Canlet C, Lefort G, Tremblay-Franco M, Debrauwer L, Concordet D et al (2017) ASICS: an automatic method for identification and quantification of metabolites in complex 1D 1H NMR spectra. Metabolomics 13(10):109

    Article  CAS  Google Scholar 

  36. Ludwig C, Viant MR (2009) Two-dimensional J-resolved NMR spectroscopy: review of a key methodology in the metabolomics toolbox. Phytochem Anal 21(1):22–32

    Article  CAS  Google Scholar 

  37. Dona AC, Kyriakides M, Scott F, Shephard EA, Varshavi D, Veselkov K et al (2016) A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments. Comput Struct Biotechnol J 14:135–153

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Cloarec O, Dumas ME, Craig A, Barton RH, Trygg J, Hudson J et al (2005) Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic 1H NMR data sets. Anal Chem 77(5):1282

    Article  CAS  PubMed  Google Scholar 

  39. Robinette SL, Lindon JC, Nicholson JK (2013) Statistical spectroscopic tools for biomarker discovery and systems medicine. Anal Chem 85(11):5297–5303

    Article  CAS  PubMed  Google Scholar 

  40. Posma JM, Garcia-Perez I, De Iorio M, Lindon JC, Elliott P, Holmes E et al (2012) Subset optimization by reference matching (STORM): an optimized statistical approach for recovery of metabolic biomarker structural information from 1H NMR spectra of biofluids. Anal Chem 84(24):10694–10701

    Article  CAS  PubMed  Google Scholar 

  41. Sumner LW, Amberg A, Barrett D, Beale MH, Beger R, Daykin CA et al (2007) Proposed minimum reporting standards for chemical analysis. Metabolomics 3:211–221

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

I.K. and T.E. acknowledge support from the EU PhenoMeNal project (Horizon 2020, 654241). I.K. acknowledges support from the UK Dementia Research Institute, which is supported by the MRC, the Alzheimer’s Society and Alzheimer’s Research UK. T.E. and G.G. acknowledge support by National Institutes of Health (R01HL133932).

Author information

Authors and Affiliations

  1. Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College, London, UK

    Timothy M. D. Ebbels & Gonçalo Graça

  2. Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK

    Ibrahim Karaman

  3. UK Dementia Research Institute, Imperial College London, London, UK

    Ibrahim Karaman

Authors
  1. Timothy M. D. Ebbels
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  2. Ibrahim Karaman
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  3. Gonçalo Graça
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Corresponding author

Correspondence to Timothy M. D. Ebbels .

Editor information

Editors and Affiliations

  1. Northwest Metabolomics Research Center, Mitochondria and Metabolism Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA

    G. A. Nagana Gowda

  2. Northwest Metabolomics Research Center, Mitochondria and Metabolism Center, Department of Anesthesiology and Pain Medicine, University of Washington, Fred Hutch Cancer Research Center, Seattle, WA, USA

    Daniel Raftery

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Ebbels, T.M.D., Karaman, I., Graça, G. (2019). Processing and Analysis of Untargeted Multicohort NMR Data. In: Gowda, G., Raftery, D. (eds) NMR-Based Metabolomics. Methods in Molecular Biology, vol 2037. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9690-2_25

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  • DOI: https://doi.org/10.1007/978-1-4939-9690-2_25

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9689-6

  • Online ISBN: 978-1-4939-9690-2

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