ABSTRACT. This program will establish a new Center for Excellence in Genomics at Morehouse School of
Medicine, enabling a comprehensive genomics initiative to be established at a HBCU focused on increasing
the representation of under-represented minority students (URM) students in genomics research training,
enhancing retraining of faculty and whose focus is the reduction of health disparities in minority populations.
We propose this CEGS program in collaboration with our Partners at Emory University, Georgia Institute of
Technology, Children’s Health Care of Atlanta, and the Oak Ridge National Laboratories. We focus the
research on the application of genomic technologies to point of care utility, with a specific focus on the impact
of race, sex, and age on testing accuracy. The program will spur the development of education and training
opportunities for URM students withing the Atlanta University Center, (4 HBCUS in Atlanta) and therefore
enhance the training and retraining of genomic researchers from URMs.
The central premise of the research component of this center is that blood transcriptome analysis may
offer an innovative approach to diagnose disease or injury for many clinical conditions. The gal of this study is
to push this technology approach closer to clinical practice by understanding key elements of the approach and
to learn generalizable rules for implementation. To do this we use three interlinked studies on healthy, acute
brain injury and long-term cardiovascular disease, to test reproducibility, and prediction accuracy. We utilize
established research programs to enable a rapid testing of the approaches, and the computational expertise of
the Oak Ridge National Laboratories to harness AI mathematic modeling to enhance prediction accuracy. At
the end of the research program, we will have established a series of best practices for dissemination and
future use of the approach. The specific research aims are 1). What is the variance of gene expression in
blood? 2). Determine the accuracy of blood RNA expression profile to predict the clinical diagnosis of an acute
medical event? 3). Can a blood RNA expression signature identify a patient’s outcome or disease trajectory
(prognosis)? Is RNA expression’s effect on patient’s outcome or disease trajectory (prognosis) associated with,
independent of, or modified by social determinants of health (SDH).
To organize the efficient performance of the program, we establish a research management structure to
enable continuous assessment with key go/no go decisions. To translate this research into enhanced
education opportunities and retraining, we propose an education core that will focus on adapting an
established Masters of Clinical Research course, developing new training modules for students and staff in
computational skills and bioinformatics, a small grant program to enhance investigator development. Our final
goal is to start to develop a pipeline from undergraduate colleges to enhance bioinformatics and genomics
training and research opportunities to help diversify the current genomics workplace.