Connecting Metabolomic Data with Context


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Overview of network mapping and its application to metabolomic data.

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Connecting Metabolomic Data with Context

  1. 1. Connecting Data with Context Dmitry Grapov, PhD FiehnLab Seminar 112013
  2. 2. Cycle of Scientific Discovery Hypothesis Hypothesis Generation Data Acquisition Data Processing Data Analysis Data
  3. 3. Analysis at the Metabolomic Scale
  4. 4. Network Mapping 1. Generate Connections 2. Calculate Mappings 3. Create Network Grapov D., Fiehn O., Multivariate and network tools for analysis and visualization of metabolomic data, ASMS, June 08, 2013, Minneapolis, MN
  5. 5. Connections and Contexts Biochemical (substrate/product) •Database lookup •Web query Chemical (structural or spectral similarity ) •fingerprint generation BMC Bioinformatics 2012, 13:99 doi:10.1186/1471-2105-13-99 Empirical (dependency) •correlation, partial-correlation
  6. 6. Biochemical Relationships
  7. 7. Structural Similarity
  8. 8. Linking Experimental Observations: malignant vs. normal tissue purine and pyrimidine metabolism seems to be increased select amino acid metabolism is decreased Question: How are these changes related?
  9. 9. Empirical Associations How are the variables related given my experiment? Types of associations: •Correlation •Partial correlation •Bayesian •Other association based on data
  10. 10. Correlation based relationships: •simple to calculate •can offer insight when the biology is unknown Complex lipids correlation network in mouse serum
  11. 11. Correlation based relationships: •can be difficult to interpret •poorly discriminate between direct and indirect associations Complex lipids correlation network in mouse heart tissue
  12. 12. Partial correlations can help simplify networks and preference direct over indirect associations. 10.1007/978-1-4614-1689-0_17 Complex lipids partial correlation network in human plasma
  13. 13. Combining biochemical and empirical information Are theses changes related?
  14. 14. Learning from experiments partial correlation network between top predictors for cancer A B The observed changes can be summarized into three groups, A, B and central inversely correlated group
  15. 15. A) 1. increase in 5′-Deoxy-5′-(methylthio)adenosine (MTA) suggests deficiency of enzyme 5'-methylthioadenosine phosphorylase (MTAP) important for Sadenosylmethionine (AdoMet) salvage shown to be decreased in cancer • inhibits spermidine synthase [PMID:6896990, PMID:21135097] vital for cell survival 2. increased 5,6-dihydrouracil is observed in prostate cancer [PMID:23824564] 3. increased xanthine indicates tissue depletion of ATP [PMID:3062020] and product uric acid is a pro-oxidant (in cells) [PMID:18600514] 4. biosynthesis of UDP-GlcNAc involves glutamate B) 1. ornithine and citrulline linked through ornithine transcarbamylase [PMID:11849441] 2. decrease in citrulline, allantoic acid and biuret may suggest reduction in urea cycle 3. nicotinamide induces L-ornithine decarboxylase [PMID: 153228, heart] which is necessary for putrescine synthesis
  16. 16. Variable relationships can be independently assessed for differing experimental groups
  17. 17. Mass Spectral Connections Watrous J et al. PNAS 2012;109:E1743-E1752
  18. 18. Linking the Known and Unknown mass spectral similarity + empirical association
  19. 19. Network Mapping Tool
  20. 20. Miscellaneous 2012-2013 Projects Data Analysis As a Service (DAAS) over 20 studies $20K earnings Automated Data Analysis and Reporting
  21. 21. Primary Metabolomics 1. Dmitry Grapov, Caitlin Campbell, Oliver Fiehn, Carol J. Chandler, Dustin J. Burnett, Elaine C. Souza, John K. Meissen, Kohei Takeuchi, Gretchen A. Casazza, Mary B. Gustafson, Nancy L. Keim, John W. Newman, Gary R. Hunter, Jose R. Fernandez, W. Timothy Garvey, Mary-Ellen Harper, Charles L. Hoppel, and Sean H. Adams, Altered patterns of plasma metabolites of endogenous and gut origin in insulin-resistant obese women following a weight loss and fitness intervention, Nov. 2013, Plos ONE (accepted) 2. Dmitry Grapov, Johannes Fahrmann, Manami Hara, Oliver Fiehn, Type 1 diabetes associated metabolic perturbations. (in preparation) 3. William R. Wikoff, Dmitry Grapov, Brian Defelice*, Oliver Fiehn*, Suzanne Miyamoto, William Rom, Harvey Pass, Karen Kelly, David Gandara, Kyoungmi Kim, Early Stage Adenocarcinoma Affects Multiple Metabolic Pathways in Lung Tissue. Cancer research (in preparation) 4. Brian D. Piccolo, Dmitry Grapov, W. Timothy Garvey, Mary-Ellen Harper, Oliver Fiehn, Sean H. Adams, John W. Newman, Impact of a human missense UCP3 polymorphism on the plasma metabolomic profile: support for a mitochondrial fuel-partitioning role for UCP3 (in preparation)
  22. 22. Lipidomics 1. Dmitry Grapov, Stuart G. Snowden, Heli Nygren,Magnus Settergren, Fabio Luiz D’Alexandri, Jesper Z. Haeggström, Tuulia Hyötyläinen, Theresa L. Pedersen, John W. Newman, Matej Orešič, John Pernow, Craig E. Wheelock, High dose simvastatin exhibits enhanced lipid lowering effects relative to simvastatin/ezetimibe combination therapy. Circulation Cardiovascular Genetics, Nov. 2013 (submitted) 2. Schuster GU, Bratt JM, Jiang X, Pedersen TL, Grapov D, Adkins Y, Kelley DS, Newman JW, Kenyon NJ, Stephensen CB. Dietary Long-Chain Omega-3 Fatty Acids do not Diminish Eosinophilic Pulmonary Inflammation in Mice. Am J Respir Cell Mol Biol. 2013 Oct 17. 3. Denis J. Glenn, Michelle C. Cardema, Wei Ni, Yan Zhang, Yerem Yeghiazarians, Dmitry Grapov, Oliver Fiehn and David G. Gardner, Cardiac Steatosis Potentiates Angiotensin II Effects in the Heart. Sept. 2013, Circulation (in review)
  23. 23. Glycomics and Proteomics 1. Smilowitz, J.T., Totten S.M.,Huang J., Grapov D., Durham H.A., LammiKeefe C.J., Lebrilla C., German J.B. , Human Milk Secretory Immunoglobulin A and Lactoferrin N-Glycans Are Altered in Women with Gestational Diabetes Mellitus. J Nutr, 2013. 2. Dmitry Grapov, Smilowitz, J.T., Gestational diabetes related changes in milk colostrum proteins. (in preparation)
  24. 24. Bioinformatics 1. Dmitry Grapov, Oliver Fiehn, MetaMapR: a Metabolomic Network Generation and Analysis Tool. Bioinformatics (in preparation) 2. Dmitry Grapov, Oliver Fiehn, Devium: Dynamic Multivariate Data Analysis and Visualization Platform. Bioinformatics (in development) Method Development 1. Dmitry Grapov, Theresa Pedersen, John W. Newman, Quantitative analysis of Sterol Ester, Triglyceride and Phospholipid Bound Fatty Acids and Oxylipins. (in preparation)