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

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

4. Type II diabetes Metabolism is very easily compared across animal models and back to humans 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 With Roger Cox, Michael Cheeseman and Tertius Hough looked at the effects of age and gender on the profile of diabetic urine Ignored glucose! Ignored glucose! Identified a number of novel perturbations Identified a number of novel perturbations E.g. 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. Predict the occurrence and severity of coronary artery disease using blood serum. Blood sera collected at Papworth hospital as part of trials concerning statins Blood sera collected at Papworth hospital as part of trials concerning statins Such systems may produce significant financial savings Such systems may produce significant financial savings angiography, currently the gold standard for diagnosis. angiography, currently the gold standard for diagnosis. Brindle JT et al., 2002. Nat Med. 8(12), 1439-45.

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

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

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

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

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

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

13. Acknowledgements 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 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.