Dr. Kaddurah-Daouk trained in biochemistry at the American University of Beirut with post graduate training in molecular biology and genetics at Johns Hopkins where she worked with Nobel Laureate Hamilton Smith. She did subsequent training at the Massachusetts General Hospital followed by appointment in the Biology department at the Massachusetts Institute of Technology. She is currently Associate Professor at the Duke Medical Center and head of the newly established Pharmacometabolomics Center. Dr. Kaddurah-Daouk has been a seminal force in the development and evolution of the metabolomics field. She cofounded the Metabolomics Society, served as its founding president and for over four years organized national and international meetings and workshops on metabolomics and brought membership of society to over 500. She also cofounded a leading biotechnology company devoted to metabolomics applications. Dr. Kaddurah-Daouk has extensive experience in assembling teams of researchers to work collaboratively on large scientific projects and has lead scientific programs from an early stage of discovery through clinical trials. She established and leads the Metabolomics Research Network with funding from NIGMS (R24 grant and RC2 stimulus funding) with the goal of integration of metabolomics and clinical pharmacology in an effort to personalize treatment. This network allowed the applicant to test and refine the premises that underlie the current proposal and to assemble a superb multi disciplinary team that will implement the project. Additionally she has built a comprehensive metabolomics program at Duke for mapping biochemical underpinnings of neuropsychiatric diseases. Her work with the creatine kinase system earlier in her career resulted in the identification of neuroprotective properties of creatine and partnerships she established between academia, NIH, biotech and the non profit organizations lead to phase III clinical trials that are ongoing in over 50 centers for Parkinson's and Huntington’s Diseases with one of the largest investment from NIH for a natural compound for the treatment of a CNS disease.
Dr. Weinshilboum’s career has been devoted to studies of mechanisms responsible for individual variation in drug response, with an emphasis on pharmacogenetics and pharmacogenomics; the study of the role of inheritance in variation in drug response phenotypes. His pharmacogenetic studies extend from the biochemical genetic era to the current era of genome-wide studies. For example, Dr. Weinshilboum’s laboratory discovered and characterized the clinically important thiopurine S-methyltransferase (TPMT) genetic polymorphisms that have a striking influence on variation in response to thiopurine drugs such as like 6-mercaptopurine, drugs that are used to treat diseases such as childhood acute lymphoblastic leukemia and Crohn’s disease. The TPMT genetic polymorphisms were the first example selected by the FDA for public hearings on the incorporation of pharmacogenetic information into drug relabeling. The TPMT studies represent only one aspect of a systematic program of pharmacogenetic studies of “phase II” drug-metabolizing enzymes, enzymes that catalyze conjugation, especially methyltransferases and sulfotransferases, that have been performed in Dr. Weinshilboum’s laboratory over several decades. Those studies began with biochemical genetic experiments, but expanded to include cDNA and gene cloning, polymorphism discovery and translational application. Dr. Weinshilboum has been principal investigator of the Mayo Clinic-NIH Pharmacogenetics Research Network (PGRN) Center since that NIH-funded network originated in 2000 – with a focus for the Mayo PGRN on pharmacogenomic studies of drugs used to treat breast cancer and depression. During the initial funding cycle for that NIH network, he was Chair of the PGRN. More recently, he is now Chair of the Steering Committee for the NHGRI-funded Genome-wide Association Randomized Trials Network (GARNET).
Dr. Zhu was trained at North Carolina State University Bioinformatics Research Center and Department of Statistics, where his research was mainly focused on computational systems biology, including “omics” data analysis and integration, pathway and network modeling, and related statistical methodologies such as model selection and dimension reduction. As an active member of the PMRN, he has developed and applied over the last four years statistical and bioinformatics tools to mine complex metabolomics data. Working closely with the clinical, pharmacological, analytical, biochemical and genetic groups, he performs and coordinates data mining for the depression, statin, anti-hypertensive, and anti-platelet projects. The extensive experience has enabled him to design and implement a pipeline for in-depth mining of metabolomics data.
My research interest has focused on assessing risk factors in the development of hypertension, type 2 diabetes and cardiovascular disease. As a postdoctoral fellow at both the Duke University School of Medicine and the Karolinska Institute in Sweden, I coordinated and evaluated multi-site intervention studies on the effects of diet, exercise and stress management in hypertensive and cardiac patients. For the past 5 years I have been an Assistant Research Professor at Duke University School of Medicine working on examining bio-behavioral mechanisms in the development of type 2 diabetes. Currently, I am a key member of the administrative team of the Pharmacometabolomics Network lead by Dr Kaddurah-Doauk. In addition to coordinating shipments of samples to the metabolomics labs I am working on the development and implementation of standard operating procedures for the acquired clinical meta-data. I am also assisting in the data management in close collaboration with the data governance team at Duke, as well as taking active part in the interpretation of the statistical analysis conducted by the NC State statistical analysis teams. Lastly, I am a key participant in the writing and publication of manuscripts.
I assist the PMRN with data management and analysis for their RC2 projects, and also projects in Depression , Alzheimer's, and Schizophrenia. I manage regulatory compliance with the Duke Health System's IRB for the PMRN. Previously I have been associated with a number of clinical trials conducted by the Anxiety and Traumatic Stress program in the department of Psychiatry and Behavioral Sciences, along with the Durham VA. In addtion, I am managing the content of the PMRN website.
Data Governance Team
Research in my laboratory spans several areas of bioinformatics, systems biology and medicine. In bioinformatics we are involved in developing novel strategies for identifying protein interaction networks, intracellular localization of proteins and identification of functional networks in cells. In systems biology we are involved in deciphering mammalian cellular networks from high throughput and phenotypic data and in developing strategies for modeling cellular signaling networks. In systems medicine, I have been a Core Director of Bioinformatics and Data Coordination for two NIGMS Glue Grants, the Alliance for Cellular Signaling and LIPID MAPS. My laboratory has created, arguably, the best infrastructure for cellular signaling and lipidomics. The infrastructure now presented jointly by UCSD and Nature Publishing Group can be seen in http://www.signalinggateway.org and http://www.lipidmaps.org.
I have operated a well-funded and productive laboratory for 15 years that pursues cutting-edge research in bioinformatics, metabolomics and pharmaceutical sciences. I have also been involved in several successful projects that integrated clinical studies with large-scale “omics” studies. Because of these past experiences, we have developed a wide range of bioinformatics tools, databases laboratory information management systems and scientific database management systems that can be used and easily adapted for use by clinicians and molecular “omics” researchers. These software tools include the HMDB, DrugBank, SMPDB and MetaboLIMS. We have also developed novel metabolomic methods, that allow us to identify and quantify up to 3500 compounds from blood or urine samples. These quantitative metabolomic capabilities are quite unique and will allow members of our team to gain unique and useful insights into the influence of drugs on the metabolome.
My area of expertise is in Systems Biology modeling and computational analysis of cellular metabolism. I am a member of the National Academy of Engineering, co-author of almost 300 scientific articles and 20 U.S. patents, many of which are in the area of metabolic modeling, metabolic engineering, mammalian cell line protein production, hematopoetic stem cell (HSC) transplantation, HSC culture technology, bioreactor design, and gene transfer. My contributions have been through the development of methods to analyze metabolic dynamics (flux-balance analysis, and modal analysis), and the formulation of complete models of selected cells (the red blood cell, E. coli, hybridoma, and several human pathogens). I sit on the editorial broad of several leading peer-reviewed bioengineering and biotechnology journals. I have previously held a faculty position at the University of Michigan for 11 years and was named the G.G. Brown Associate Professor at Michigan in 1989, a Fulbright fellow in 1995, and an Ib Henriksen Fellow in 1996. I am currently a Professor of Bioengineering and Medicine at UCSD. Additionally, and of particular importance to this SBIR application, I have previously co-founded a biotechnology company (Aastrom Biosciences) where I served as the Vice President of Developmental Research, and Aastrom is now a publicly traded company. I am also the founder of a biotechnology company (Cyntellect) where I serve as Chairman of the Board. Additionally, I co-founded Genomatica and am the Chairman of the Scientific Advisory Board.
Shankar Subramaniam (See Bio Above)
My areas of expertise are quantitative and statistical genetics. In quantitative genetics, we are concerned with genetic basis of complex traits and biological pathways and processes that connect genes to phenotypes. In the early years, I completed many theoretical studies on modeling quantitative traits in responding to selection, drift and mutations. Then with the advent of genomics, I have developed some very popular statistical methods for mapping quantitative trait loci (QTL), such as composite interval mapping and multiple interval mapping, as well as the popular computer software, QTL Cartographer. With the advent of other omics technology, I have also worked on statistical methods for gene expression QTL analysis that connects DNA polymorphisms to gene expressions and to phenotypes. Metabolomics is an important link in the lpathways from genes to phenotypes, and a very important component in the systems oriented study of complex traits. In the last few years, I have worked in the Metabolomics Network on various projects to detect metabolomic signatures and establish metabolomic pathways in responding to medical treatments on human diseases. My long-term goal is to develop various statistical methods that can connect different omics data with clinical phenotypes and study designs towards a systems oriented study of complex traits.
I have Ph.D. training in statistics, with speciality and expertise in high dimensional regression analysis, dimension reduction, variable selection. I have demonstrated record of productive publications and am currently supported by a National Science Foundation grant as the sole PI.
I have a successful 20-year record of developing metabolic pathway databases and software tools. My interest is to extend the approach we have developed for the E. coli metabolic network to the human metabolic network.
I have pioneered developments and applications in metabolomics since 1998 with over 100 publications to date. My interest is in unifying other metabolomics labs in a collaborative effort to provide the most extensive and most in-depth analysis of metabolites in blood plasma using a range of validated protocols. We aim at integrating new approaches or technologies as these become available. I provide data for samples for primary metabolism based on automatic liner exchange/cold injection GC-TOF mass spectrometry. I have chaired efforts in establishing metabolomic databases, libraries and standardizing metabolomic reports, including for the Metabolomics Society, e.g. for assessing the selectivity and specificity of biomarkers. This aspect is of great importance in the proposed research and for clinical applications in general.
My research interest is in the development of innovative analytical strategies for metabolomics-driven systems biology in personalized health. With my strong background in analytical chemistry and my experience in data analysis of metabolomics data, I am convinced that reliable metabolomics data are key for pharmacometabolomics. Therefore I have organized my research group such that in the main lab we develop new analytical tools for metabolomics such as comprehensive LCxLC-MS and new LC-MS interfaces, new strategies for identification of metabolites based on MSn fragmentation trees and innovative minimal invasive sampling strategies; we use microfluidics devices where helpful, which we produce in our own recently realized small clean room. My laboratory analyzes more than 10000 samples per year. Since it is clear that important progress can only be realized in combining expertise in multidisciplinary projects, I have initiated the Netherlands Metabolomics Centre, for which I received a grant for a research program of 50M€; together with other metabolomics groups at academia, clinical centres, research institutes and industry we aim to develop metabolomics tools, which are currently not available, and apply them to improve personal health and quality of life.
After two years of research in heavy metal pollution at UM, I co founded a company (ESA Inc) to bring one of my inventions in trace metal analysis to bear on the problem of childhood lead poisoning. My group used with this technology with support from the CDC to define the national extent of the problem in a 30 city study in 1970-1972. In 34 years at ESA I received some 100+ patents and my group brought the instruments derived from them through the processes of 510K, PMA, and CLIA waiver approvals for a variety of clinical tests in the US, Japan, and Europe. One of these instruments was the LCECA system that we began to apply in the late 1980s to what is now Metabolomics. I have since moved my laboratory to the Bedford VA where I was asked to develop systems biochemistry group with the mission “bring new technology bench to bedside through multicenter multidisciplinary collaborations”. My personal goal and interest is in finding approaches to that small class of social problems that have technical solutions. One such social problem is the cost of medical care and the potential solution is in objective tests to specify treatment and eventually detect risk factors and avoid the necessity of treatment.
I have a broad background in lipid biochemistry, lipidomics, mass spectrometry, neuroscience, and cell biology, with specific training and expertise in key research areas for this application. As an investigator or co-investigator on over ten previous NIH-funded grants, I provided a foundation for the proposed research by developing a powerful technology for lipidomics. In addition, I have successfully administered the projects (e.g. staffing, research protections, budget) and produced several peer-reviewed publications from each project, resulting in a total of 134 peer-reviewed publications. Collectively, I have a demonstrated record of successful and productive research projects in multiple research areas related to lipidomic profiling, lipid metabolism, trafficking, and function.
The Raftery research group focuses on the development of new methods in NMR and MS-based metabolite profiling as well as their implementation and use in a number of diagnostic applications in various human diseases. We have developed advanced isotope tagging methods for NMR-based metabolite profiling that allow dramatically increased resolution and sensitivity. In addition, our work in microcoil NMR methods allows the identification of low concentration metabolites of interest in complex samples like biofluids. We have worked closely with a number of clinical collaborators on previous metabolomics projects such as breast, liver and colon cancer.
David Wishart (See Bio Above)
My field of expertise is in the development and application of high throughput clinical assays using mass spectrometry and other new technologies. I am interested in development of diagnostic assays and biomarker research, with particular emphasis on small molecules related to inherited and acquired metabolic disorders. I am director of the Biochemical Genetics Laboratory and co-founder of the Metabolomics Laboratory at my Duke University Medical Center. My main research accomplishments include the development of the first clinical tests to use tandem mass spectrometry, especially the acylcarnitine profile that is now the standard of care for diagnosis of fatty acid oxidation disorders, and the first multiplex test for over 30 inborn errors of metabolism, now used in newborn screening programs worldwide. My current research focus is on the development, validation and application of assays for biomarkers related to oxidative damage and one-carbon pathway metabolism. I am also interested in the applications of “digital microfluidics”, a novel lab-on-a-chip technology, to screen newborns and at-risk infants for metabolic and infectious diseases, both inexpensively and in challenging environments.
My interest is in using systems biology to understand and treat complex (i.e. non-Mendelian) diseases, using both human patients and animal disease models. My work in the diverse areas of neurological pathology, immunology, the enteric microbiome, and kidney transport, have shown that metabolomics can be applied to problems far beyond questions that directly involve central metabolism. I am the current chair of the ABRF Metabolomics Research Group, which is organizing one of the first metabolomics inter-laboratory studies. My interest here is in deriving clear biological and biochemical interpretations of the pharmacometabolomics data and integrating it with other data streams, such as transcriptomics and proteomics experiments.
Stable Isotopes Resolved Metabolomics Team
An important area of metabolmics research is to understand the functional basis of gene polymorphism in relation to drug efficacy. As part of the research strategy, novel stable isotope-resolved metabolomic (SIRM) approach can be employed in relevant model system studies to facilitate a mechanistic understanding on the role of metabolic, protein, and/or genetic marker(s) uncovered from the proposed human patient studies. I have over 25 years of experience in applying metabolite profiling to the understanding of metabolic mechanism of stress response in organisms, including anti-cancer agents and neuropsychiatric drugs. In the past 6 years, I have organized a metabolomic center (CREAM, funded by the National Science Foundation) to establish state-of-the-science instrument infrastructure. CREAM enables the development and integration of SIRM with Metabolomics-Edited Transcriptomics Approach (META) to explore dysregulations resulting from human disease development and exposure to chemopreventive and therapeutic agents. This integrated approach has been demonstrated on systems ranging from model cells and animals to human subjects. I have also been expanding and applying my biochemical knowledge to reconstruct pathways based on SIRM and META data. This knowledge will facilitate the biochemoinformatic development for pathway reconstruction and subsequent kinetic modeling, which is a part of my long-term goal.
Dr. Lane is a professor in the Department of Medicine at the University of Louisville and leader of the Structural Biology Program. He is responsible for management of the Nuclear Magnetic Resonance core facilities at the James Graham Brown Cancer Center and is an associate director of U of L's Center for Regulatory Environmental Analytical Metabolomics CREAM). His research interests concern the biophysical mechanism of regulation of gene expression and metabolic networks and how loss of these control processes leads to cancer.
My role in this is the development of chemical moiety model creation tools, model optimization tools, and model selection tools for the analysis of FT-ICR-MS isotopologue data from SIRM experiments. I have published expertise in the development of these bioinformatics tools, as well as, significant experience in methods development across an array of bioinformatics projects. I have unique education and research experience that allows me to work in both computational and biological fields and facilitate the collaboration between computational and biological scientists.
My role in the SIRM is the development of chemical moiety model creation tools, model optimization tools, and model selection tools for the analysis of FT-ICR-MS isotopologue data from SIRM experiments. I have published expertise in the development of these bioinformatics tools, as well as, significant experience in methods development across an array of bioinformatics projects. I have unique education and research experience that allows me to work in both computational and biological fields and facilitate the collaboration between computational and biological scientists. Furthermore, I have 10 years experience working in a large and highly collaborative project, the Northeast Structural Genomics Consortium.
Richard Weinshilboum (See Bio Above)
Dr. David Mrazek has been working to define how genetic variations influence both vulnerability to psychopathology and response to treatment over the course of his career. For the past decade, Dr. Mrazek has lead the Department of Psychiatry and Psychology at the Mayo Clinic and has worked in close collaboration with both the Department of Laboratory Medicine and Pathology and the Department of Molecular Pharmacology and Experimental Therapeutics to better define the relationship between pharmacokinetic and pharmacodynamic gene variations and medication response. During this time he has worked closely with Dr. Richard Weinshilboum and has participated as a Principal Investigator in the Mayo Clinic/NIH Pharmacogenetics Research Network (PGRN) Center since 2005. He also currently serves as the principal investigator of an NIAAA Developing Research Center grant entitled, “The Mayo Clinic Center for Individualized Treatment of Alcohol Dependence”, which is committed to the development of a P-50 NIAAA proposal to study pharmacogenomic influences on treatment response for drugs used to treat alcohol addiction. He is the sole author of the first textbook devoted to psychiatric pharmacogenomics which was published in 2010 by Oxford University Press.
Ms. Snyder has been involved in psychiatric research for over twenty years and is currently the program coordinator for the GENE unit research program in psychiatry at Mayo Clinic. She oversees both the SSRI and AI trials in the Mayo PGRN and the administration of Dr. David Mrazek's NIAAA-funded P20 center grant. Ms. Snyder has worked with Dr. Mrazek in the development and management of his genomic research program at Mayo Clinic over the past ten years. In this role, she participated in the development of numerous research projects, educational initiatives, and built and managed a team of over twenty allied health professionals. Ms. Snyder has also functioned as liaison with Mayo groups and business partners involved in the translation of pharmacogenomics to the clinical practice of psychiatry through the development and testing of a medication advice algorithm based on pharmacogenomics.
The overall objectives of my research program are to identify mechanisms responsible for genetic, dietary, and pharmacologic effects on atherogenic dyslipidemia, and to utilize this information for devising and evaluating the effectiveness of interventions aimed at reducing risk for cardiovascular disease. Among my earlier accomplishments was the discovery of multiple LDL subclasses that led in turn to the identification of a common genetically influenced atherogenic lipoprotein phenotype characterized by a predominance of small, dense LDL particles. This phenotype, which is more commonly referred to as atherogenic dyslipidemia, is a major component of the metabolic syndrome, and is a growing concern connected with the increasing prevalence of excess adiposity and insulin resistance. We and others have demonstrated that higher carbohydrate diets can induce atherogenic dyslipidemia, and more recently we have shown that this dyslipidemia can be effectively reversed by both reduced dietary carbohydrate and weight loss. Notably, we found that these beneficial effects are independent of saturated fat intake, which primarily influences levels of larger LDL particles that we and others have shown are weakly related to cardiovascular disease risk. As noted above, however, our preliminary data suggest that high intake of red meat may modify the impact of saturated fat on LDL metabolism, leading to greater increases in all lipoprotein particles including small, dense LDL. The principal of the current project is to determine the influence of dietary protein source on changes in atherogenic lipoproteins induced by saturated fat. Based on my recent findings, a major hypothesis is that adverse lipoprotein effects will be substantially greater with a diet high in both red meat and saturated fat than with diets containing similar levels of saturated fat together with sources of protein other than red meat. If confirmed, this would lead to re-assessment of current dietary guidelines that focus on a generalized restriction of total and saturated fat, with substantial potential impact on public health, as described further below.
As someone who has been deeply involved with the American Heart Association and the Institute of Medicine in evaluating and formulating dietary dietary recommendations for reducing cardiovascular disease risk, I feel that our previous findings together with the expected outcomes of the present proposal have major public health implications. The promotion of diets focused on limiting total and saturated fat has been accompanied by increased intake of cabohydrates, including sugars and refined starches, that have adverse metabolic effects. If limitation of red meat can be shown to attenuate the atherogenic impact of total and saturated fat, a focus on red meat rather than overall saturated fat restriction would facilitate adoption of healthful diets with a more favorable balance of fat and carbohydrate intake.
I am the Principal Investigator of the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) study that is funded as part of the NIH Pharmacogenetics Research Network (PGRN) (U01 GM074492). I will lead the efforts that relate to PEAR, including analysis of the metabolomics data relative to the PEAR phenotypes of interest, linking the metabolomics data with the pharmacogenomics data that arise from the PEAR grant, interpreting the findings, and leading the efforts to discover the functional underpinnings of discoveries we make through the metabolomics studies.
The major goal of our project is to discover novel metabolomic signatures that associate with drug response in well-characterized responders and non-responders. In particular, our group is focused on characterizing associations between metabolomic signatures and the antihypertensive response to beta-blockers and the anti-metabolic effects of thiazide diuretics. We are well prepared to undertake the proposed research as our research team has the expertise and resources to undertake this project; we have experience and ongoing research evaluating metabolomic signatures and antihypertensive response to atenolol. A clinical pharmacologist by training (and a licensed pharmacist), my research focuses on identifying factors that contribute to variability in drug response. In particular I have focused on drug metabolizing enzymes that contribute to pharmacokinetic variability observed with many drugs and natural products. My work in this area is currently supported by NIDCR and NIGMS. In collaboration with Drs. Kaddurah-Daouk and Johnson, I have led the initial project exploring metabolomic response to antihypertensive treatment. I serve on the editorial boards of Pharmacotherapy, The Open Drug Metabolism Journal, and Annals of Pharmacotherapy and as an ad-hoc reviewer for many journals, including Drug Metabolism and Disposition and Clinical Pharmacology and Therapeutics.
I have been investigating hypotheses centered around the metabolic effects of antihypertensive drugs for a number of years now, most recently on the link to adipose tissue and obesity. The research on the PEAR study samples will extend work previously completed on my lab and will fill in gaps in knowledge surrounding the mechanisms of thiazides and beta blocker induced dysglycemia.
My expertise is in cardiovascular pharmacology and pharmacogenomics and I have extensive experience in conducting clinical translational research. I have worked on the PEAR study for the past three years. I have an excellent understanding of the study designs, the available phenotypes, and the relevant clinical factors to consider for defining the pharmacometabolomic signatures we are investigating. I role in this project is contributing to the interpretation of the pharmacometabolomics data with the goal of defining metabolic pathways important for atenolol and hydrochlorothiazide response and adverse effects in the PEAR study.
Dr. Shuldiner’s major research interests lie in the molecular biology and genetics complex diseases and traits including of type 2 diabetes, obesity, osteoporosis, and cardiovascular disease, common disorders that contribute significantly to mortality, morbidity, and functional loss. He also works on the pharmaco- and nutri-genomics of these disorders. He is best known for his studies in the Old Order Amish, a homogeneous founder population ideal for genetic studies. His multidisciplinary research team uses state-of-the-art molecular genetic statistical and epidemiological methods including both candidate gene and genome wide association (GWA) approaches. He has authored more than 190 original articles in leading journals and 50 reviews and book chapters. As PI of an NIGMS Pharmacogenomics Research Network grant, he studies the pharmacogenomics of anti-platelet agents including clopidogrel and aspirin. He was the first to publish a GWA study of clopidogrel response variation which identified CYP2C19 as a major determinant of clopidogrel response.
Amber Beitelshees (See Bio Above)
Cardiovascular Translational Project
I have 15 years of clinical-translational research experience ranging from small single-center projects to large multinational randomized clinical trials to translational research using repositories of biospecimens and paired longitudinal clinical data for genomic analysis. One of my interests is to determine whether metabolic signatures of drug activity and/or metabolic signatures of good or poor mechanistic response (e.g., hsCRP-lowering or platelet response to ADP) to drugs commonly used in treating cardiovascular disease or its risk factors that are generated from the work other pre-clinical bridging projects are associated with clinical cardiovascular events (e.g., death or myocardial infarction). The long range implications of this work are to foster development of new clinical tools for classifying risk that can aid physicians in individualizing treatment to optimize benefit and reduce risk and cost.
Dr. Voora is an Instructor in the Division of Cardiology and Associate Investigator at the Institute for Genome Sciences & Policy (IGSP) at Duke University. At Washington University in St. Louis Dr. Voora led the first, prospective genotype-guided clinical study of warfarin therapy. At Duke, he has worked closely with Geoffrey Ginsburg MD, PhD at the IGSP to identify novel genetic variants associated with statin efficacy and toxicity. Currently, at the IGSP, Dr. Voora is a co-investigator on a NIGMS (RC1 mechanism) funded pharmacogenomics study using whole blood gene expression profiling to dissect the laboratory response to aspirin. The aim of this study is to identify novel genetic pathways that underlie the response to aspirin and to develop a translatable RNA biomarker that can be used to guide the aggressiveness of antiplatelet therapy. Ultimately, his research is aimed at associating "-omic" drug response signatures into with long term clinical events in patients with cardiovascular disease and tailoring therapies on the basis of these signatures to improve patient outcomes, quality of life, and cost.
Anastasia Georgiades (See Bio Above)
Depression Translational Project
Rima Kaddurah-Daouk (See Bio Above)
I have extensive experience in research into depression and related mood disorders. My experience includes work in differential diagnosis, treatment development and evaluation, use of baseline measures as moderators and predictors of treatment response, and in the pharmacology of depression/mood disorders. I have had experience in designing, conducting, and analyzing trials and other clinical research projects germane to the identification of biomarkers to either guide treatment selection or to monitor the course of illness.