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NMR and Mass Spectrometry approaches to metabolomics in man and mouse

NMR and Mass Spectrometry approaches to metabolomics in man and mouse. Dr. Julian Griffin jlg40@mole.bio.cam.ac.uk Dept of Biochemistry, University of Cambridge. Overview. What is metabolomics and why do we need it? Type II diabetes Man, mouse and rat CAD and cardiovascular disease

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NMR and Mass Spectrometry approaches to metabolomics in man and mouse

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  1. NMR and Mass Spectrometry approaches to metabolomics in man and mouse Dr. Julian Griffin jlg40@mole.bio.cam.ac.uk Dept of Biochemistry, University of Cambridge

  2. Overview • What is metabolomics and why do we need it? • Type II diabetes • Man, mouse and rat • CAD and cardiovascular disease • Markers of drug efficacy • Type I diabetes • Biomarker discovery

  3. The basis of metabolomics • Metabolomics/metabonomics • the quantitative measurement of metabolic responses to pathophysiological stimuli or genetic modification • Measure small molecule concentrations through a global approach • NMR spectroscopy • Mass Spectrometry • Use pattern recognition to define metabolism in a multidimensional space • metabolic phenotype • metabotype

  4. Type II diabetes • Metabolism is very easily compared across animal models and back to humans • With Roger Cox, Michael Cheeseman and Tertius Hough looked at the effects of age and gender on the profile of diabetic urine • Ignored glucose! • Identified a number of novel perturbations • E.g. NMN and nucleotide metabolism PCA of 160 urine samples from a diabetic mouse model (dbdb mouse maintained at MRC Harwell). Class 1 – Male Wild Type/Heterozygous; Class 2 - Male Homozygous; Class 3 - Female WT/Heterozygous; Class 4 - Female Homozygous. Salek RM, Physiol Genomics 2007

  5. CAD and cardiovascular disease • Predict the occurrence and severity of coronary artery disease using blood serum. • Blood sera collected at Papworth hospital as part of trials concerning statins • Such systems may produce significant financial savings • angiography, currently the gold standard for diagnosis. Brindle JT et al., 2002. Nat Med. 8(12), 1439-45.

  6. However, on closer inspection: • ‘Biomarkers’ are rather generic • Gender and statin treatment effect the same ‘biomarkers’ of disease • Groups must be stratified • Over fitting of the pattern recognition models is a problem Kirschenlohr et al., Nature Medicine, 2006

  7. Mouse models of atherosclerosis • Mice - C57Bl/6, LDLR-/- • Diet - Control RM1 Diet (SDS), HFCC Diet (Hope Farms) • Blood plasma (and urine)

  8. Class 2, Control High fat diet Class 2, Control Normal diet (Week 0) Class 1, Control Normal diet Class 4, LDLR-/- Normal diet (Week 0) Class 3, LDLR-/- Normal diet Class 4, LDLR -/- High fat diet Cheng KK, Physiol Genomics, 2010

  9. ANOVA-PCA Source: Analytica Chimica Acta 629 (2008) 47-55

  10. Genotype effect Diet effect RM1 diet HFCC diet LDLR -/- B6 LDLR -/- HFCC diet B6 RM1 diet ANOVA-PCA Diet + error ANOVA-PCA Gen + error

  11. Discussion & Conclusion • Metabolomics can now be used as a high throughput phenotyping tool in mice • Metabolism is also very translatable across species • Reduced variability in phenotype can simplify biomarker discovery • Mass spectrometry is much more sensitive if you know what you are looking for • Database tools are also in place to conduct this across multiple sites

  12. Acknowledgements • Collaborators • Roger Cox, Michael Cheeseman & Tertius Hough, MRC Harwell • Anne Cooke & Paola Zaccone • Andy Nicholls & John Haselden, GSK • Funders: BBSRC, EU, BHF, GlaxoSmithKline, MRC, Syngenta, Unilever & Wellcome Trust. • JLG Group (present) • Zsuszi Ament • Michael Baker • Cecilia Castro • Martin Coleston • Sue Connor • Melanie Gulston • Cheng Kian Kai • Steve Murphitt • Lee Roberts • Reza Salek • Ben Tucker • Baljit Ubhi • Xinzhu Wang • James West

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