VGER: The Vanderbilt Genome-Electronic Record project An important potential enabling resource for Personalized Medicine is the combination of a DNA repository with Electronic Medical Record (EMR) systems sufficiently robust to provide excellence in clinical care and to serve as resources for analysis of disease susceptibility and therapeutic outcomes across patient populations. The Vanderbilt EMR is a state of the art clinical and research tool (that includes >1.4 million records), and is associated with a DNA repository which has been in development for over 3 years;these are the key components of VGER, the Vanderbilt Genome-Electronic Records project proposed here. The VGER model acquires DNA from discarded blood samples collected from routine patient care, and can link these to de-identified data extracted and readily updated from the EMR. The phenotype we will analyze here is the QRS duration on the electrocardiogram, since slow conduction (indicated by longer QRS duration) is a marker of arrhythmia susceptibility. This will not only exploit the power of Genome-Wide Association (GWA) approaches to generate new biologic knowledge that impacts an area of public health concern, but also provides a platform for the development of tools, such as Natural Language Processing approaches, to optimally mine EMRs. This project brings together a team of investigators with nationally recognized records of accomplishment in genome science, medical ethics, bioinformatics, de-identification science, and translational and cardiovascular medicine to address four Specific Aims: (1) perform a GWA comparing samples from subjects with QRS durations at the extremes of the normal range, and validate by genotyping high likelihood associations in prospectively ascertained clinical trial sets for QRS duration and for arrhythmia susceptibility;(2) evaluate the validity and utility of structured and unstructured components of EMR data for genome-phenome correlations;(3) assess the ethical, scientific, and societal advantages and disadvantages of the VGER model, and determine best practices for oversight, community involvement, and communication as the resource grows;and (4) develop and evaluate formal privacy protection models for data derived from databanks and EMRs, establishing data sharing and integration practices. We also include here a proposal to develop the Administrative Coordinating Center whose mission will be to facilitate communication and collaboration among nodes in this network, the NHGRI, and external advisors. We subscribe to a vision of Personalized Medicine in which genomic and other patient-specific information drives personalized, predictive, preemptive, and participatory health care, and VGER represents an important step in that direction.
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