Connecting Metabolomic Data with Context

Connecting Data with Context

Dmitry Grapov, PhDFiehnLab Seminar

112013

Cycle of Scientific DiscoveryData Acquisition

DataData AnalysisHypothesis Generation

Data ProcessingHypothesis

Analysis at the Metabolomic Scale

Network Mapping

2. Calculate Mappings

1. Generate Connections

3. Create Network

Grapov D., Fiehn O., Multivariate and network tools for analysis and visualization of metabolomic data, ASMS, June 08, 2013, Minneapolis, MN

Connections and Contexts

Biochemical (substrate/product)• Database lookup• Web query

Chemical (structural or spectral similarity )• fingerprint generation

Empirical (dependency)• correlation, partial-correlation

BMC Bioinformatics 2012, 13:99 doi:10.1186/1471-2105-13-99

Biochemical Relationships

http://www.genome.jp/dbget-bin/www_bget?rn:R00975

Structural Similarity

http://pubchem.ncbi.nlm.nih.gov//score_matrix/score_matrix.cgi

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?

Empirical Associations

How are the variables related given my experiment?

Types of associations:

• Correlation

• Partial correlation

• Bayesian

• Other

association based on data

Complex lipids correlation network in mouse serum

Correlation based relationships:

• simple to calculate

• can offer insight when the biology is unknown

Correlation based relationships:

• can be difficult to interpret

• poorly discriminate between direct and indirect associations

Complex lipids correlation network in mouse heart tissue

Partial correlations can help simplify networks and preference direct over indirect associations.

Complex lipids partial correlation network in human plasma

10.1007/978-1-4614-1689-0_17

Combining biochemical and empirical information

Are theses changes related?

Learning from experiments

The observed changes can be summarized into three groups, A, B

and central inversely correlated group

A

B

partial correlation network between top predictors for cancer

A)1. increase in 5′-Deoxy-5′-(methylthio)adenosine (MTA) suggests deficiency of

enzyme 5'-methylthioadenosine phosphorylase (MTAP) important for S-adenosylmethionine (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 glutamateB)5. ornithine and citrulline linked through ornithine transcarbamylase [PMID:11849441]6. decrease in citrulline, allantoic acid and biuret may suggest reduction in urea cycle7. nicotinamide induces L-ornithine decarboxylase [PMID: 153228, heart] which is

necessary for putrescine synthesis

Variable relationships can be independently assessed for

differing experimental groups

Mass Spectral Connections

Watrous J et al. PNAS 2012;109:E1743-E1752

Linking the Known and Unknownmass spectral similarity + empirical association

Network Mapping Toolhttp://spark.rstudio.com/dgrapov/MetaMapR/

Miscellaneous 2012-2013 ProjectsData Analysis As a Service (DAAS)

over 20 studies

$20K earnings

Automated Data Analysis and Reporting

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)

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)

Glycomics and Proteomics

1. Smilowitz, J.T., Totten S.M.,Huang J., Grapov D., Durham H.A., Lammi-Keefe 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)

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

3. Dmitry Grapov, Theresa Pedersen, John W. Newman, Quantitative analysis of Sterol Ester, Triglyceride and Phospholipid Bound Fatty Acids and Oxylipins. (in preparation)