RTI International

Metabolomics to Provide and Mechanistic Insights

Susan Sumner, PhD Director NIH Eastern Regional Comprehensive Resource Core Systems and Translational Sciences Program RTI International [email protected] www.rti.org\rcmrc 919-541-7479

RTI International is a trade name of Research Triangle Institute. www.rti.org RTI International About RTI International

. RTI is an independent not-for-profit research institute established in 1958 in Research Triangle Park, NC.

. RTI’s mission is to improve the human condition by turning knowledge into practice.

. RTI has 9 offices in the United States, 8 offices worldwide, and has projects in more than 40 countries.

. RTI is staffed with more than 4,000 employees working in health and pharmaceuticals, laboratory and chemistry services, advanced technology, statistics, international development, energy and the environment, education and training, and surveys.

. RTI has more than 800,000 square feet (ft2) of laboratory and office facilities in RTP, NC.

. The metabolomics facility in the Research Triangle Park consists of ~22,000 ft2 laboratory space. RTI International Metabolomics

. Metabolomics involves the broad spectrum analysis of the low molecular weight complement of cells, tissues, or biological fluids.

. Metabolomics makes it feasible to uniquely profile the of an individual, or system, apart from, or in addition to, the genome. – Metabon(l)omics is used to determine the pattern of changes (and related metabolites) arising from disease, dysfunction, disorder, or from the therapeutic or adverse effects of xenobiotics; including applications in plant and mammalian studies.

. This leading-edge method is now coming to the fore to reveal biomarkers for the early detection and diagnosis of disease, to monitor therapeutic treatments, and to provide insights into biological mechanisms. RTI International

Why Metabolomics?

Specific genes can be identified that define individuals’ at risk for a disease, dysfunction, or disorder, or response to treatments.

Some diseases or responses can occur at the level of the proteome; and proteins and metabolites can inform us about the state of a disease, dysfunction or disorder at any given time.

4 RTI International Fluids, Cells, and Tissues

Cells / Organ System Released metabolites

Serum Urine Saliva Breath Plasma CSF

Signatures or Profiles

Cytosolic metabolites Discrete peaks Diagnostics 5 RTI International The Metabotype

Studies have shown metabolomics signatures (the metabotype) to correlate with gender, race, age, ethnicity, drugs, chemicals, stress, weight status, mental health status, blood pressure, disease state, nutrition, gut microbiome, etc.

6 RTI International Comparing states of wellness and sickness

Protein Expression

THE NEEDS Pathways More sensitive and early markers for disease detection and staging Metabolite Levels Markers to monitor treatment for • efficacy • adverse response • relapse Traditional Clinical Parameters • transplantation

Mechanistic insights from pathway analysis

7 RTI International NIH Common Fund is Investing in Metabolomics

NIH Funded Six Regional Comprehensive Metabolomics Resource Cores to – increase our National capacity to provide metabolomics profiling and data analysis services to basic, translational, and clinical investigators – foster collaborative efforts that will advance translational research using metabolomics approaches – facilitate institutional development of pioneering research, metabolomics training, and outreach – establish National standards . RTI (Susan Sumner), UC Davis (Oliver Fiehn) and U Michigan (Chuck Burant), UK (Rick Higashi), UF (Art Edison), Mayo Clinic (Sree Nair) . Metabolomics DRCC (Shankar Subramaniam, PI, UCSD) . Metabolomics Training (Martin Kohlmeier, UNC-CH; Stephen Barnes, UAB)

. Metabolite Standards Synthesis Cores (Herb Seltzman, RTI; Mary Tang, 8 SRI)

RTI RCMRC RTINIH International Eastern Regional Comprehensive Metabolomics Resource Core at RTI

Data Sample Sample Preparation Reduction & Support for Receipt Visualization Discovery Experimental Data Capture & Communicating QC Standards Design Entry into & Storage Pathway Results BSI II Empirical & Mapping Pooled Samples Standards Library Matching

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__ R T O A A R D G E S T P E E D C T R U M 9 RTI International NMR Targeted and Broad Spectrum Metabolomics

Bruker Avance III 950 MHz (DHMRI) • Equipped with cryogenically cooled triple resonance (1H, 13C, and 15N) probes

Bruker Avance III 700 MHz (DHMRI) • Equipped with cryogenically cooled QNP probes (with four nucleus: 1H, 13C, 15N, and 31P) and a Bruker SampleJet autosampler (rack of 480 samples)

Bruker Avance III 950 MHz Bruker Avance III 600 MHz (DHMRI) • Equipped with cryogenically cooled probe

Varian Unity Innova 500 MHz (RTI) • Inova Performa II pulsed field gradient module • 15N ‐31P with 1H decoupling variable‐ temperature probe • Indirect 1H detection with 15N ‐31P decoupling variable‐temperature probe • 3H ‐1H switchable probe Varian Unity Bruker Avance III 700 MHz NMR data acquisition is performed by using methods cited in Beckonert Innova 500 MHz et al. (2007), Nature Protocols, 2 (11), 2692‐2703, as appropriate. RTI International GC-MS Targeted and Broad Spectrum Metabolomics

LECO Pegasus 4D GCxGC TOF‐MS ‐ broad spectrum analysis

Agilent 7890A GC + Agilent 5975C MS

Agilent 7890‐MS with Agilent 7000B triple quadrupole MS with EI and CI source options

Agilent 6890 GC with Agilent 5973 MS

Agilent G1530A/5973 MS, GC/MS/ATD

Agilent 7890 GC/MS

LECO Pegasus 4D GCxGC TOF‐MS RTI International LC-MS Core – Ion Mobility and UPLC-MSn High resolution MS/MSMS platforms available for targeted and broad spectrum metabolomics

UPLC-QToF Platform UPLC-Orbitrap Platform

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Acquity UPLC coupled SYNAPT G2 ion mobility QToF HDMS Acquity UPLC coupled Orbitrap (Waters Corporation) Velos with ETD (Thermo Fisher Scientific) 12 RTI International Example Workflow

Peak Binned Alignment NMR QC Check Data

Fourier NMR Raw NMR Processed NMR Multivariate Sample Transform Phase Statistical data Spectrum Data Pathway Preparation Data and Baseline Analysis Analysis Analysis Acquisition (FID) Correction 1r, cnx, esp, jdx

Library Matched Data RTI International Design and Analysis Considerations . Study Design – Gender, race, ethnicity, age, exposures (drugs, chemicals, stress, city, etc..) all contribute to the metabotype

. Sample Collection and Storage – Consistency in collection and processing . blood to serum (over ice?), or blood to plasma (anticoagulant?) – Storage consistency (vials, temperature, freeze thaws, etc.) – Selection of chemicals for extraction of samples

. Instrument Response and Drift – Consistency in parameters for each sample run – Create phenotypic pools as well pre- and post- run standards

. Data Analysis – Data quality, spectral alignment, formatting, etc. 14 – Check the standards and the pooled samples!! RTI International

Adolescent Obesity

We worked with David Collier, MD, PhD at ECU to understand more about why and how some adolescents lose weight when adopting healthy life styles, while others do not have a positive response.

We are collecting psychosocial inventories and biological data to reveal signatures associated with a positive response to treatment that will aid clinicians in providing treatment and care.

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15 RTI International Predicting Response to Exercise and Nutrition Intervention

. Serial urine samples were At baseline the branched-chain amino acids obtained from adolescents (BCAA) valine, leucine, and 2-oxoisocaproate were at lower levels in responders compared participating in a 3 week with non-responders to weight loss. healthy weight camp. Investigators have found high levels of plasma BCAA (valine, isoleucine, phenylalanine, . Metabolomics of urine tyrosine & leucine ) to be predictive of indicated significant changes development of diabetes. in the metabolome over the 3

concentrations_11Nov2010.M3 (OPLS/O2PLS-DA), OPLS-DA All Classed by Response 1 week period. t[Comp. 1]/to[XSide Comp. 1] 2 Colored according to classes in M3

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160 . Metabolite profiles correlated 140 9 120

100 20 1 80 11 9 2 2 with the responsivity (BMI 60 14 15 7 9 40 11 4 20 116 13 2 0 13 decline, weight loss, to[1] 15 20 -20 3 3 3 4

-40 16 16 11 7 -60 13 psychosocial parameters) to 14 7 -80 17 15 -100 16

-120 treatment. 17 -140 17 -160

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-90 -80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 70 80 90 t[1]

Pathmasiri et al., 2012 R2X[1] = 0.0510651 R2X[XSide Comp. 1] = 0.35649 Ellipse: Hotelling T2 (0.95) SIMCA-P+ 12.0.1 - 2010-11-15 11:42:43 (UTC-5) RTI International Predicting Response to Vaccination . Genomic study results* indicate that 3 genes play a significant role in modulating antibody response – MARCO, TNFAIP3, CXCL12

. TNFAIP3 and CXCL12 were significantly associated with increased vibriocidal titers

. For the metabolomics analysis, 112 subjects were selected based on their response to the vaccination – Antibody response was based on the bioplex assay – Response = ln (day 28 – day 0) . Only high and low responders were selected

. Serum samples were analyzed using the Bruker Avance III 950 MHz NMR spectrometer 17 *Majumder PP, Sarkar-Roy N, Staats H, et al (2012). Genomic correlates of variability in immune response to an oral cholera vaccine. European Journal of Human Genetics doi: 10.1038/ejhg.2012.278. RTI International Biomarkers to Predict Response to Vaccination

PopGen_BinningResults_Regions_Removed.01.09.2013.M3 (PLS-DA), Day 0 All Subjects high t[Comp. 1]/t[Comp. 2] low Colored according to classes in M3 Positive 10 9 Response 8

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R2X[1] = 0.130952 R2X[2] = 0.112839 Ellipse: Hotelling T2 (0.95) SIMCA-P+ 12.0.1 - 2013-01-18 15:22:47 (UTC-5)

Subset of Metabolites that Influence the Separation of Subjects at Day 0 (VIP ≥ 1 or p-value ≤ 0.1) Isoleucine** Creatinine** Leucine** Cysteine** Valine Histidine 3-Methyl-2-oxo- isovalerate Choline 3-Hydroxybutyrate Glucose Lactate Betaine Preliminary results Alanine TMAO Receptor ligands/binding proteins related to Acetate** Glycine gene markers from genetics analysis. Proline* Glycerol Majumder et al. 2012, Eur. J. Human Genetics, Glutamate** Serine 1-7 Glutamine** Creatine Metabolites that linked to the receptor ligand binding Pyruvate Tyrosine* 18 2-Oxoisocaproate Histidine proteins Methylguanidine** Tryptophan Formate Phenylalanine RTI RCMRC; Sumner et al., in preparation RTI RCMRC RTI International Metabolomics and primary glomerulonephritides:

. Metabolomics of serum and urine from patients with membranous nephropathy showed: – Serum: increases in citric acid, asparagine, serine, threonine and pyroglutamic acid – Urine: increases in dicarboxylic acids, phenolic acids and cholesterol

19 Jian, S. et al. “The primary glomerulonephritides: a systems biology approach” Nat. Rev. Nephrol. 9, 500-512 (2013); RTI International

Metabolomics to Monitor Kidney Transplantation

. NMR metabolomics study Follow-Up of urine collected from Stage Post- patients following kidney Operation transplantation . 15 subjects (9 male and 6 female) provided at least 9 samples each during the graft recovery process Pre- Discharge . Metabolomics enabled identification of patients Fig. A. PCA analysis with score plot: All individuals presenting 3 who were not progressing clusters corresponding to the 3 recovery stages of patients; postoperation (circle), predischarge (triangle), and follow-up within the normal range (cross) 20

Calderisi et al. (2013) “Using Metabolomics to Monitor Kidney Transplantation Patients by Means of Clustering to Spot Anomalous Patient Behavior” Transplantation Proceedings, 45, 1511-1515. RTI International Metabolomics to Monitor Kidney Transplantation (2/2)

. Stages of Recovery: – Post-operation: immediately following Follow-Up Post- intervention (kidney is not functioning) Stage Operation – Pre-Discharge: kidney is starting to function and the organism moving toward a new homeostasis – Follow-up Stage: homeostatic condition characteristic of the typical health of transplant recipients Pre- . The development of a global Discharge model enabled these researchers to describe groups of patients and evaluate a single-patient model. Fig. B. PCA analysis with score plot: 3 chosen subjects presenting 3 clusters corresponding to the 3 recovery stages of patients; postoperation (circle), predischarge (triangle), and follow-up (cross) 21 Calderisi et al. (2013) “Using Metabolomics to Monitor Kidney Transplantation Patients by Means of Clustering to Spot Anomalous Patient Behavior” Transplantation Proceedings, 45, 1511-1515. RTI International

Metabolomics and ureteral 48 h 12 h 72 Pre- Post-Op Post-Op obstruction Post-Op operation

. NMR metabolomics study to evaluate a method for predicting renal function recoverability after the relief of obstructive uropathy – 16 bilateral ureteral obstruction patients (BUO) and 9 unilateral ureteral obstruction patients (UUO) . Metabolomics may help stratify patients according to disease stages, provide prognostic information, and be useful for post-operative surveillance

Dong et al. (2012) “Application of 1H-NMR Metabolomics in 22 Predicting renal function recoverability after the relief of obstructive uropathy in adult patients” Clinical Biochemistry Volume 46, Isues 4-5 Pg:346-353 RTI International Early-stage biomarkers for diabetic kidney disease

- Diabetic kidney disease is a complication that affects an estimated third of patients with type 1 diabetes mellitus

- 52 type 1 diabetic patients with normal urinary albumin excretion rate (AER)

- Metabolite profiles could distinguish between progressive and nonprogressive normo-albuiminuric

- Metabolites significant to the differentiation included acyl- carnitines, acyl-glycines and compounds related to tryptophan metabolism 23 Van Der Kloet et al (2012). Discovery of early-stage biomarkers for diabetic kidney disease using MS-based metabolomics (FInnDiane Study). Metabolomics. 8: 109 - 119 RTI International NMR Metabonomics: Diabetic Nephropathy Screening

Clinical practice to diagnose diabetic nephropathy is a tedious procedure to measure albumin and determine the excretion rate in consecutive 24 hr urine samples.

182 diabetic and 21 non-diabetic serum metabolic profiles were readily distinguished using NMR metabonomics

Serum metabolic characteristics of T1DM with normo, macro, or micro albuminuria were also distinguished using NMR metabonomics.

Mäkinen et al. 2006. Diagnosing diabetic nephropathy by 1H NMR metabonomics of serum. Magn Reson Mater Phy. 19: 281 - 296 RTI International Metabonomics Analysis of Diabetic Nephropathy and Type 2 Diabetes DN -UPLC coupled with orthogonal acceleration time-of-flight (oaTOF) was utilized in this T2DM study Healthy

-Study distinguished the global serum profiles of 8 diabetic nephropathy (DN) patients, 33 type 2 diabetes mellitus (T2DM) patients and 25 healthy volunteers

Significant changes in the serum level of leucine, dihyodrosphingosine and phytoshpingosine were noted, indicating the perturbations of amino PCA Scores plots derived form the UPLC-TOF spectra of the sera. (A) acid metabolism and phospholipid Positive mode and (B) negative mode. In Fig. 2B, exclusive separation metabolism in diabetic diseases. between the patients and controls was also achieved with negative25 mode, however DN and T2DM groups scatter into each other Zhang et al 2009. Metabonomics research of diabetic nephropathy and type 2 diabetes mellitus based on UPLC – oaTOF-MS system RTI International Urinary Metabolomics for RCC Detection

RCC . Fifty urine samples were obtained from (Renal Cell Carcinoma) RCC and Healthy patients from two institutions

Control . Hydrophilic interaction chromatography-mass spectrometry was used to determine metabolites that differentiated the RCC and Healthy subject samples

. Metabolic changes associated with RCC persisted after removal of primary tumor, so that the post-OP urine metabolic profiles were similar to Fig. 5. Prediction of group membership using linear discriminant the Pre-OP profiles analysis (LDA) for the choice of k = 4. LDA analysis was performed on all samples for California samples (a and b) and Texas samples (c Kim et al., 2009. Urine Metabolomics Analysis for and d). The posterior probabilities for the groups are shown on the y axis. The absolute posterior probability is the probability Kidney Cancer Detection and Discovery. of assigning a samples to each group. Op, operative Molecular & Cellular . RTI International Urine Metabolomic Analysis of Kidney Cancer

Ultra high performance LC/GC- MS with tandem mass spectrometry used to identify metabolites in kidney cancer patients’ urine

Determined that quinolinate, 4-hydroxybenzoate, and gentisate differentiate experimental groups

These metabolites are involved in common pathways of specific amino acid and energetic metabolism, consistent with high tumor protein breakdown and utilization, and the Warburg effect

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Kim et al., 2011. Urine Metabolomics Analysis Identified Potential Biomarkers and Pathogenic Pathways in Kidney Cancer. OMICS A Journal of Integrative Biology RTI International Pilot and Feasibility Studies Program

. Consistent with an objective of the NIH Common Fund, an aim of the pilot and feasibility program is to foster collaborations and promote the use of metabolomics.

. Applications will be accepted at least once per year – Up to $50K in RTI RCMRC metabolomics collaboration.

. Awardees must agree to deposit data into the DRCC.

. Studies are selected based on innovation, relevancy, investigator merit, and collaborative potential for future funding.

. Applications may include technology development with RTI RCMRC.

. RTI RCMRC will use the P&F studies program as a means to ensure a sustainability model. 28 . For more information, go to: www.rti.org/rcmrc RTI International RCMRC 2013 Pilot and Feasibility Awards

Collaborator Application Collaborator Application Richard F. Loeser Herman Staats Osteoarthritis Peanut Allergy Wake Forest Univ. Duke University Mark C. Chappell Steroids & Fetal Rachel Alison Adcock Mental Health Wake Forest Univ. Programming Duke University

Eric B. Haura Joseph A. Houmard Lung Cancer Diabetes Moffitt Cancer Center East Carolina Univ. Melinda Beck Influenza Snezana Petrovic UNC-Chapel Hill Kidney Disease Wake Forest Univ. Melissa Troester Breast Cancer UNC-Chapel Hill Robert Williams Clay B. Marsh Diet & Genetics Sepsis The Univ. of TN Ohio State Univ. Bernd Schnabl Martin J. Blaser Liver Disease Antibiotic Exposure UC San Diego New York Univ. Carla Bann Lee M. Graves Leukemia Kinase Clinomics RTI International UNC-Chapel Hill Inhibitors RTI International Acknowledgements NIH Common Fund Metabolomics Program 1U24DK097193: Sumner, RTI, PI “NIH Eastern Regional Comprehensive Metabolomics Resource Corel” 5R25GM103802: Martin Kohlmeier, UNC-CH, PI “Online learning platform introducing clinicians and researchers to metabolomics”

NIDDK 1UMDK10086601: William Smoyer, Nationwide Children’s Hospital and Larry Greenbaum, Emory, Multiple PIs “Integrated Proteomics and Metabolomics for Pediatric Glomerular Disease”

RTI RCMRC NMR Core: Wimal Pathmasiri, Jason Burgess, Andrew Novokhatny, Rod Snyder LC-MS Core: Suraj Dhungana, Alex Kovach, Megan Grabenauer, Brian Thomas GC-MS Core: Wimal Pathmasiri, Jim Carlson, Jocelyn Deese-Spruill, Jim Raymer Postdoctoral Scientist: Delisha Stewart Interns: Darya Cheng, Aastha Ghimire, Jon Brodish DHMRI Collaborators: Jason Winnike and Kevin Knagee Biochemistry and Data Analysis: Tim Fennell, Susan McRitchie, Bob Clark, Grier Page 30 Special thanks to Andrew Novokhatny who reviewed the metabolomics literature relevant to nephrology and prepared slides for this presentation.