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Application of Combined 'omics Platforms to Accelerate Biomedical Discovery in Diabesity

Application of Combined 'omics Platforms to Accelerate Biomedical Discovery in Diabesity

Monday, April 16, 2012

The New York Academy of Sciences

The explosive rise in obesity and attendant diabetes (diabesity), threatens the health of children and adults in Western and developing Asian countries. This symposium focuses on the breakthrough discovery potential of metabolomics. Metabolomics, in concert with high-content data from other 'omics technologies, can reveal the connections between metabolic phenotype and molecular underpinnings of diabesity, identifying new therapeutic targets and developing new and innovative targeted therapies. In addition to a day of outstanding science by academic thought leaders, industry leaders will contribute to a panel discussion on the emerging revolution in bioinformatic platforms that enable multi-omic metabolic pathway analysis. These new platforms are expected to provide a game-changing acceleration of future biomedical discoveries.

This event will also be broadcast as a webinar.

Please note: Transmission of presentations via the webinar is subject to individual consent by the speakers. Therefore, we cannot guarantee that every speaker’s presentation will be broadcast in full via the webinar. To access all speakers’ presentations in full, we invite you to attend the live event in New York City where possible.

Reception to follow.

Registration Pricing

Student / Postdoc Member$10
Nonmember (Academia)$60
Nonmember (Corporate)$80
Nonmember (Non-profit)$60
Nonmember (Student / Postdoc / Resident / Fellow)$40


Presented by

  • The New York Academy of Sciences
  • The Sackler Institute for Nutrition Science


* Presentation times are subject to change.

Monday, April 16, 2012

8:30 AM

Registration and Continental Breakfast

9:00 AM

Welcome and Introduction
Jennifer Henry, PhD, The New York Academy of Sciences
Steven S. Gross, PhD, Weill Cornell Medical College

9:15 AM

Fuel Switching Dysregulation in Diabesity Models: Characterization by Use of Combined ’omics
Irwin Kurland, MD, PhD, Albert Einstein College of Medicine

10:00 AM

Multi-omics Approaches for Unraveling Cardiometabolic Disease Mechanisms
Christopher B. Newgard, PhD, Duke University Medical Center

10:45 AM

Coffee Break

11:15 AM

Leveraging Omics to Find New Diabetes Treatments
Domenico Accili, MD, Columbia University

12:00 PM

From Affymetrix to Lipidomics and the Discovery of a Novel Class of Lipids
Barbara B. Kahn, MD, Beth Israel Deaconess Medical Center & Harvard Medical School

12:45 PM

Networking Lunch

2:00 PM

Food for Thought: Fatty Acid Metabolism, Diabesity and the Brain
Gabriele V. Ronnett, MD, PhD, The Johns Hopkins University School of Medicine

2:45 PM

Tools for Integration, Visualization and Interpretation of Metabolomic and mRNA Expression Data in Diabetes and Obesity Research
Charles Burant, MD, PhD, University of Michigan Medical School, Ann Arbor

3:30 PM

Coffee Break

4:00 PM

Industry Panel Discussion: Breakthrough Technologies (moderated by Irwin Kurland)
Steven M. Fischer, PhD, Agilent Technologies
Suma Ramagiri, PhD, AB SCIEX
John A. Ryals, PhD, Metabolon, Inc.
Mark Sanders, PhD, Thermo Fisher Scientific
Joe Shambaugh, MS, Genedata Expressionist
John Shockcor, PhD, Waters Corporation

5:00 PM

Networking Reception

6:00 PM




Steven Gross, PhD

Weill Cornell Medical College

Steven S. Gross is Professor of Pharmacology, Director of the Mass Spectrometry Core Facility and Director of Advanced Training in Pharmacology at the Weill Cornell Medical College. The American Chemical Society recently awarded Dr. Gross with a 2011 award for "Achievements in Mass Spectrometry". His primary research interest is in cell–cell communication, with a focus on nitric oxide (NO) and reactive molecules as mediators of cell signaling. In the late 1980s, Dr Gross and colleagues made the initial identification of L-arginine as the precursor of NO in blood vessels. They were also first to establish that NOS inhibition elevates blood pressure in animals, demonstrating that NO plays a physiological role in controlling blood pressure and vascular tone. Since then, research efforts have been directed toward elucidating the enzymes and mechanisms that regulate NO synthesis in cells. His basic studies have provided fundamental insights into the therapeutic control of NO synthesis, resulting in core technologies for the creation of ArgiNOx Inc., a biotech start-up that seeks to develop novel NO-based drugs. Dr. Gross' research is supported in part by a MERIT Award from the NHLBI. He is a founder and Board Director of the Nitric Oxide Society and chairs the Steering Committee of the Biochemical Pharmacology Discussion Group (BPDG) at NYAS. Dr Gross received his PhD in Biomedical Science from the Mount Sinai School of Medicine in New York City.

Irwin Kurland, MD, PhD

Albert Einstein College of Medicine

Irwin Kurland, MD, PhD is an Associate Professor of Internal Medicine, and Director of the Stable Isotope and Metabolomics Core Facility at the Albert Einstein College of Medicine. Dr Kurland's laboratory has helped, for over a decade, establish stable isotope phenotyping methodology for assessing inter-organ fuel switching, and the characterization of 'silent' metabolic phenotypes. This is a key issue for translational medical research in the field of diabetes metabolism. As Type II diabetes evolves, with re-feeding there is impairment in metabolic flexibility, that is, in the ability for organs, such as skeletal muscle to 'switch off' using fatty acids and use predominately glucose instead, or the liver to 'switch off' glucose production, or adipose tissue to 'switch off' lipolysis. Disturbances in metabolic flexibility underlie the hyperglycemic/hyperlipidomic phenotype seen in Diabesity. Dr Kurland's personal research program centers on a multi-omic approach for elucidation of mechanisms governing tissue specific metabolic flexibility. Stable isotope fluxomics, metabolomics, lipidomics, and proteomics/global acetylome profiling are utilized to determine molecular mechanisms linking feedback via key metabolites, to dysfunctional regulation of the metabolic network in states of insulin resistance, in order to understand the molecular mechanisms underlying the (dys)regulation of metabolic flexibility in the fasted to fed transition. Recent papers by the Kurland laboratory illustrate the regulatory role, in the fasted to fed transition, of lysine acetylation on enzymes in tissue specific metabolic networks (Yang et al., J. Proteome Res. 2011), and the linkage between disturbances in fasted/re-fed acetyl CoA levels and subsequent dysregulated global lysine acetylation, on the metabolic network response (Vaitheesvaran et al., PLOS One 2012). Dr Kurland received his MS in Electrical Engineering from the Polytechnic Institute of New York, his MD from University of Southern California, and his PhD in Molecular Physiology and Biophysics from Vanderbilt University, Nashville, TN. After his internal medicine residency at the University of Cincinnati, he was an Endocrine Fellow at SUNY Stony Brook, and has been on the faculties of UCLA and SUNY Stony Brook before joining Einstein.

Jennifer Henry, PhD

The New York Academy of Sciences


Domenico Accili, MD

Columbia University

Dr. Domenico Accili is the Russell Berrie Foundation Professor of Diabetes at Columbia University in New York CIty. He also serves as an Attending Physician at New York's Presbyterian Hospital. His work is concerned with the pathophysiology of insulin resistance and pancreatic beta cell dysfunction. His main scientific contribution lies in the elucidation of the metabolic role of transcription factors of the Foxo family, and in the identification of their properties to modulate aspects of cellular differentiation that impinge on metabolic homeostasis, such as adipocyte and pancreatic endocrine cell differentiation.

Charles Burant, MD, PhD

University of Michigan Medical School, Ann Arbor

Charles Burant, MD, PhD is a Professor of Internal Medicine, and the Robert C. and Veronica Atkins Professor of Metabolism at the University of Michigan Medical School as well as Professor of Environmental Health Sciences in the Michigan School of Public Health. Dr. Burant is Director of the Michigan Metabolomics and Obesity Center and the NIH-sponsored Michigan Metabolomics and Obesity Center which provides training and infrastructure for basic, clinical and translational research in metabolic diseases. Dr. Burant’s personal research program centers on the interaction between genetics and environmental factors in the development of insulin resistance, obesity and β-cell failure leading to the development of diabetes. His laboratory is taking advantage of recent technological advances, including metabolomic profiling, which have made biological, chemical, behavioral and imaging tools readily available to study an individual’s response to environmental factors, such as nutrition. In collaboration with clinicians and support staff in the Investigational Weight Management Clinic, efforts are under way to understanding the metabolic adaptations to weight loss and why despite profound improvements in health, weigh loss almost invariably results in weight regain. By collecting a broad range of phenotypic data, including clinical, psychological and metabolic data from people in the clinical setting and using computational tools to integrate and analyze the data, a more complete picture of the phenotypic changes associated with obesity and weight loss can be obtained. One of the efforts associated with the program is to make analytical tools available to researchers to more easily handle and analyze data generated by high throughput technologies.

Barbara B. Kahn, MD

Beth Israel Deaconess Medical Center & Harvard Medical School

Barbara Kahn, MD is the George Minot Professor of Medicine at Harvard Medical School and Vice-Chair for Research Strategy in the Department of Medicine at Beth Israel Deaconess Medical Center. She has made major contributions to understanding the molecular pathogenesis of obesity and type 2 diabetes. Her studies continue to elucidate the role of the adipocyte in insulin resistance and the regulation of energy balance. Dr. Kahn received her MD from Stanford University and an MS from the University of California, Berkeley. After internal medicine residency, she was an Endocrine Fellow at NIH. She is a member of the Institute of Medicine of the National Academy of Sciences.

Christopher B. Newgard, PhD

Duke University Medical Center

Christopher B. Newgard, PhD is the Director of the Sarah W. Stedman Nutrition and Metabolism Center and the W. David and Sarah W. Stedman Distinguished Professor of Pharmacology and Cancer Biology at the Duke University Medical Center. Prior to coming to Duke in 2002, Dr. Newgard was the Gifford O. Touchstone Jr. and Randolph G. Touchstone Distinguished Professor, Department of Biochemistry, and Co-Director of the Touchstone Center for Diabetes Research, University of Texas Southwestern Medical Center, Dallas. Dr. Newgard’s research focuses on application of an interdisciplinary approach for understanding of diabetes and obesity mechanisms involving gene discovery, metabolic engineering, and comprehensive tools of metabolic analysis (“metabolomics”) such as mass spectrometry-based metabolic profiling and NMR-based metabolic flux analysis. Dr. Newgard has authored over 230 peer-reviewed and review articles, and has been the recipient of several awards, including the Kayla Grodsky Award for Outstanding Basic Science Research from the Juvenile Diabetes Research Foundation (1999), the Outstanding Scientific Achievement (Lilly) Award from the American Diabetes Association (2001), a Merit Award from the NIH (2001), the Solomon Berson Prize of the American Physiological Society (2003), and a Freedom to Discover Award in Metabolic Research from Bristol-Meyers Squibb (2006). See for more information.

Gabriele V. Ronnett, MD, PhD

The Johns Hopkins University School of Medicine

Dr. Ronnett is a Professor in the Departments of Neuroscience and Neurology. She received her BA, MD, and PhD degrees from Johns Hopkins. Dr. Ronnett has contributed in two principal areas—the use of the olfactory system as a model of neuronal development and of developmental diseases, and the role of brain signaling pathways in regulating energy balance and food intake. Her contributions in the field of neurology include understanding the molecular basis of Rett Syndrome, a form of autism, and using the olfactory system as a developmental model to understand the factors involved in maintaining health of nerve cells. Her contribution in the field of feeding is the discovery of novel brain pathways that control food intake and the development of compounds that may eventually be used to control appetite and weight gain. Her studies of neuronal energy metabolism have revealed master energy sensing pathways in the brain that may serve as targets for neuroprotection strategies. Dr. Ronnett has authored over 125 papers. She has received various postdoctoral awards and a McKnight Scholars Award and is currently the recipient of several federal grants from the NIH, specifically from the NINDS, NIDCD, NIDDK, and NICHD.


Steven M. Fischer, PhD

Agilent Technologies

Steven Fischer received his bachelors in chemistry (1981) and masters in chemistry (1991) at California State University, Hayward. In 1986, he joined Agilent Technologies in Santa Clara (previously part of Hewlett-Packard Company) where he has designed and applied HPLC/MS instrumentation for analytical problems for 20 years. He has over 40 United States issued patents in the field of mass spectrometry. He was the 2007 Bill Hewlett Award recipient for outstanding instrument design innovation. He currently is the Marketing Manager, Metabolomics and Proteomics responsible for Agilent’s world wide metabolomics and proteomics program. In that position he has focused his attention on developing solutions to metabolomics and proteomics analysis with the goal of using the experimental data synergistically to yield deeper biological insight.

Suma Ramagiri, PhD


Dr. Suma Ramagiri is a strategic application scientist at the AB SCIEX product development and application lab based in Concord, Canada. She obtained her BSc in Biochemistry, MSc in Organic Chemistry in India. She did her PhD in Analytical Chemistry and after that post-doctoral study at University of Tennessee Health Sciences, TN, USA. In her current role at AB SCIEX, she drives worldwide efforts for to enhance lipidomics and metabolomics applications, in part using an unique lipid database (part of LipidView software on the Triple TOF and QTRAP MS) to help discover lipid specific biomarkers in diabetes and obesity research. LipidView software contains a dedicated in silico lipid database, with 53 lipid classes, able to uniquely identify approx. 27,000 lipid species using characteristic lipid fragment lists, that may prove to be of particular interest to Diabesity researchers.

John A. Ryals, PhD

Metabolon, Inc.

Following his postdoctoral work at the Institute of Molecular Biology, University of Zurich in 1984, Dr. Ryals worked in various research and management positions including Head, Agricultural Biotechnology Research, Vice-President of Biotechnology, Vice-President, Research for Novartis Crop Protection, Inc. and Head of the Biotechnology and Genomics Center of Novartis, Inc. In 1997, Dr. Ryals co-founded Paradigm Genetics, Inc., an early systems biology company, and served as the Chief Executive Officer, Chief Science Officer and President and taking the company public in 2000. After leaving Paradigm Genetics in 2002, Dr. Ryals co-founded Metabolon, Inc. and has served as Chief Executive Officer and President for the past ten years. Dr. Ryals research interest has been in the development of metabolomics to aid in the development of pharmaceutical drug discovery, diagnostics and nutrition.

Mark Sanders, PhD

Thermo Fisher Scientific

Joe Shambaugh, MS

Genedata Expressionist

Joe Shambaugh received his bachelors in chemistry (1987) at Ohio University and masters in information systems management (2006) at Case Western Reserve University. He has 24 years experience in biological research and data analysis, including 12 years implementing enterprise information systems for life science research organizations. At Genedata, he has focused on integrated computation platforms to enable analysis of combined 'omics data to address complex biological questions. This includes processing and analysis of data from disparate sources such as Mass Spec based proteomics and metabolomics, microarray based transcriptomics, next-gen sequencing and other high-content technologies.

John Shockcor, PhD

Waters Corporation

Dr. Shockcor is a the Director of Strategic Operations at Waters Corporation, a Visiting Fellow in the department of Biochemistry at the University of Cambridge and a Visiting Professor in the department of Surgery and Cancer at Imperial College. He is a Fellow of the Royal Society of Chemistry with over 35 years of experience in analytical chemistry using NMR spectroscopy and mass spectrometry. He has been involved in metabolic profiling studies for the past 25 years and has extensive experience in drug metabolism and metabolomics and lipidomics.

Additional biographies coming soon.


Fuel Switching Dysregulation in Diabesity Models: Characterization by Use of Combined ’omics
Irwin Kurland, MD, PhD, Albert Einstein College of Medicine

While multi-omic approaches foster discovery via information integration, sometimes “casting a larger net” seems at odds with the goal of research resulting from hypothesis driven investigations. An integrative framework for metabolomic/fluxomic investigations will be shown that uses fluxomics to generate hypotheses for pursuing proteomic, metabolomic and lipidomic profiling, instead of simply collecting just another “omic” for mining. At each step in the framework, the phenotype is further elucidated, and the next “omic” profiling decision becomes more focused. Examples of multi-omic hypothesis driven investigations for elucidation of disorders in fuel switching and tissue specific metabolic flexibility will be shown from our recent work in pre-diabetic and Type II diabetic mouse models. Multi-omic analyses on fuel and energy homeostasis of a new pre-diabetic mouse model, the FAAH (fatty acid amide hydrolase) deficient mouse (Vaitheesvaran et al PLOS One 2012), and an illustrative Type II diabetic mouse model, the MKR mouse (Vaitheesvaran et al Diabetologia 2010) will be described, along how one would use global acetylome profiling we have developed, for understanding tissue specific feedback (dys)regulation in the fasted and re-fed states (Yang et al J. Proteome Res. 2011). The purpose of this talk is to stimulate discussion on how to best construct a framework, and guide investigators seeking to begin multi-omic investigations in Diabesity.

Multi-omics Approaches for Unraveling Cardiometabolic Disease Mechanisms
Christopher B. Newgard, PhD, Sarah W. Stedman Nutrition and Metabolism Center & Department of Pharmacology & Cancer Biology, Duke University Medical Center

We seek to integrate metabolomics with other “omics” technologies such as genomics and transcriptomics for understanding of mechanisms underlying chronic human diseases and conditions such as diabetes, obesity, and cardiovascular disease, and for predicting disease progression and intervention outcomes. For example, we have identified strong associations between circulating levels of branched-chain amino acids (BCAA—Leu, Val, Ile) and related metabolites with insulin resistance in multiple human cohorts (Newgard, et al. Cell Metabolism, 2009; Huffman, et al. Diabetes Care, 2010; Tai, et al. Diabetologia, 2010), and have shown that the cluster is prognostic for improvement in insulin sensitivity when measured at baseline prior to a dietary/behavioral weight loss intervention (Shah, et al. Diabetologia, 2012). Similarly, we have identified a cluster of metabolites (small-medium chain dicarboxylated acylcarnitines) that predict incident cardiovascular events (Shah, et al. Circ. Cardiovasc. Genetics, 2010). We view these metabolic signatures as intermediate phenotypes that describe the evolution of cardiometabolic diseases, and seek to understand underlying genetic architecture via two major approaches. First, we are performing metabolic phenotyping in large human disease cohorts (e.g. the Duke CATHGEN cohort) for which whole genome SNP and/or exomic sequence data is available. Second, we are collaborating with Drs. Alan Attie (Univ. Wisconsin) and Gary Churchill (Jackson Labs) to perform multi-omics analysis of the 300 novel recombinant mouse strains generated by the Collaborative Cross consortium. These initiatives will be discussed in the context of insights that theymay provide into disease mechanisms.

Leveraging Omics to Find New Diabetes Treatments
Domenico Accili, MD, Columbia University

This presentation will review recent findings on the integrated pathophysiology of insulin signaling to illustrate examples of new candidate pathways identified through metabolomics and gene profiling approaches that hold promise as druggable targets to combat obesity and diabetes.

From Affymetrix to Lipidomics and the Discovery of a Novel Class of Lipids
Barbara B. Kahn, MD, Beth Israel Deaconess Medical Center & Harvard Medical School

Abstract will be available soon.

Food for Thought: Fatty Acid Metabolism, Diabesity and the Brain
Gabriele V. Ronnett, MD, PhD, The Johns Hopkins University School of Medicine

A role for fatty acid metabolism in the regulation of energy balance has been considered only recently, and generated the hypothesis that pharmacological alteration of fatty acid flux might affect food intake. Among the enzymes that facilitate fatty acid synthesis, utilization, and degradation, our working group has focused on three candidates as targets for obesity intervention. Fatty acid synthase (FAS) is a lipogenic enzyme that catalyzes the condensation of acetyl-CoA and malonyl-CoA to generate long-chain fatty acids. Carnitine palmitoyl-transferase-1 (CPT-1) is pace-setting enzyme for the entry of fatty acids into mitochondria for oxidation. Glycerol-3-phosphate acyltransferase (GPAT) controls the rate-limiting step in triglyceride synthesis. We have examined the effects of small molecules that modulate fatty acid metabolic flux on food intake, peripheral metabolism, and glucose tolerance. When administered centrally or peripherally, they reduce food intake and cause profound and reversible weight loss. In diet-induced obese mouse models, glucose tolerance is improved, and inflammatory cytokines are reduced. We hypothesize that that mechanisms of these effects are multiple. One mechanism may involve AMP-activated protein kinase (AMPK), a known peripheral energy-sensing kinase. Collectively, these data suggest a role for fatty acid metabolism in the perception and regulation of energy balance, and as possible targets for treatment of metabolic syndrome.

Tools for Integration, Visualization and Interpretation of Metabolomic and mRNA Expression Data in Diabetes and Obesity Research
Charles Burant, MD, PhD, University of Michigan Medical School, Ann Arbor

Large-scale ‘omics’ studies have been successful at revealing differences in gene expression, protein and metabolite abundance and post-translational protein modifications, thus providing the opportunity for an integrated view of molecular processes that lead to disease phenotypes. For biologist interested in using omics technologies, a daunting problem is the ability to handle, visualize and ultimately integrate the large amounts of data that is generated to provide new insights into biological processes. Molecular pathway databases and metabolic maps that contain computationally predicted and literature-derived information provide a path to connecting these views together.

We will present tools that we have been built to visualize metabolomic data that was developed with the biologist in mind. Cool Map is an R-based tool to rapidly visualize high volume data that is derived from metabolomic or other omics or phenotypic outputs and can provide multiple levels of views of the data. We will show how clustering of the data output can be used to derive pathway information and how this may lead to the identification of unknown metabolites derived from untargeted metabolomics output. We will also present the utility of a redesigned version of our tool Metscape that allows users to enter experimental data for metabolites, genes and pathways and display them in the context of relevant metabolic networks.


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