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| About Jessica Tenenbaum (Duke Translational Medicine Institute) |
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Dr. Jessica D. Tenenbaum is Associate Director for Bioinformatics for the Duke Translational Medicine Institute. In this role, she promotes translational research through strategic and operational support for informatics research infrastructure within Duke and among Clinical and Translational Science Award (CTSA) Institutions. Broadly, her work involves storage, management, retrieval, and analysis of large biomedical datasets. Her own research focuses on integrating disparate “omics” data types with clinical information to detect molecular biosignatures that are predictive of disease progression or response to therapy. Other research interests include proteomics, regulatory and signaling networks, systems biology, machine learning, and human-computer interaction.
After earning her bachelor’s degree in biology from Harvard University, with a minor in computer science, Dr. Tenenbaum worked as a program manager at Microsoft Corporation in Redmond, WA for six years. She first worked on the website product Sidewalk.com (later bought by Citysearch), and subsequently, on Smartphone devices in the Windows Mobile division. She also taught evening classes in computer science at the University of Washington Extension School.
In 2007, Dr. Tenenbaum received her PhD in Biomedical Informatics from Stanford University. Her doctoral research focused on integration and analysis of disparate, omic-scale datasets, and mining publicly available data for insights into human disease. As a doctoral Fellow in science policy at the Institute of Medicine in 2006, she helped to organize the Roundtable on Evidence-Based Medicine and assisted in early planning stages for a workshop on health information technology.
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The MURDOCK Study: An Inter-omics Approach to Reclassifying Disease through Biomarker Discovery
Jessica D. Tenenbaum (Associate Director for Bioinformatics, Duke Translational Medicine Institute)
Introduction: The MURDOCK Study is a long-term epidemiological study to improve disease classification and population health. Researchers at Duke University, in partnership with the citizens and health care providers of Cabarrus County in North Carolina, are working to re-classify disease by applying post-genomic era technologies to major chronic illnesses. In doing so, we will identify underlying linkages across some of today's leading causes of illness and death, aid in the retooling of healthcare practices, and enable improved preventive practices among patients.
Background: Throughout the history of medical practice, the classification of disease has relied primarily upon macroscopic observation. Patients have been diagnosed based on symptoms at the systemic or, at best, the cellular level. However, recent advances in high throughput biomolecular assays have enabled both sub-classification of disease and the detection of previously unrecognized similarities between seemingly unrelated diseases. These new insights can have important implications for decisions regarding therapeutic intervention.
Methods: The MURDOCK study consists of three project “horizons.” Horizon 1 involves the generation and analysis of molecular data for existing large, clinically well-annotated cohorts of four distinct diseases: Cardiovascular disease, Osteoarthritis, Obesity, and Hepatitis C. Biological assays were performed across these different cohorts, including genomic, proteomic, metabolomic, and imaging techniques. The objective for this horizon is to establish biosignatures that can help predict disease progression and response to treatment. Horizon 1.5 consists of the creation and population of a 50,000 person, volunteer subject registry for prospective studies designed to validate and extend hypotheses generated in Horizon 1. Enrollment has been ongoing since February, 2009, with blood and urine being collected, along with clinical data through a questionnaire. When available, additional information is extracted from electronic health records, with the volunteer’s consent. Horizon 2 will validate the hypotheses generated in Horizon 1 using the volunteers enrolled in Horizon 1.5. Horizon 3 and beyond will extend the study to additional diseases of interest.
Results: Clinical data collected through the case report forms for four individual studies has been mapped to overlapping common data elements, where possible. Preliminary molecular and imaging data analysis has yielded promising biosignatures. Creation of the MURDOCK Integrated Data Respository (MIDR) is underway to bring together clinical and molecular data, as well as sample and study metadata.
Discussion: The MURDOCK study represents a new model of translational investigation, a whole much greater than the sum of its parts. The old paradigm of biomedical research involved studying one gene, one protein, and one disease a time. As biological assays improve and expand, and as well-defined standards are agreed upon for common data elements, new approaches to biomedical research become feasible where they would have been impossible only a decade ago.
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