A more than 15-year study led by Robert W. Williams, PhD, chair of the Department of Genetics, Genomics and Informatics at the University of Tennessee Health Science Center (UTHSC), and the UT-Oak Ridge National Laboratory Governor’s Chair in Computational Genomics, establishes the relationship between DNA and disease risk and proves that the genetic code is remarkably robust and can tolerate many types of errors without causing abnormalities or disease.
Twenty-six research scientists and clinicians from across the United States and Switzerland studied mice and human gene function and disease risk. Each team member offered unique expertise, data research and analytical abilities to contribute to the study of large data sets of mice and humans, including the world-class electronic health records of mice at UTHSC and of humans at Vanderbilt University.
Published in Nature Communications, the study found that of the 20,000 genes each human has, the 0.1 percent that are non-functioning typically do not have any adverse effects because the body has a well-tuned back up system. In addition the study, titled “Joint mouse-human phenome-wide association to test gene function and disease risk,” takes a step toward President Obama’s Precision Medicine Initiative.
“Because each human is unique, providing individualized predictive medicine is complex and will require many more years of research,” explains Dr. Williams. “That said, this study establishes the relationship between DNA and disease risk, which combined with other factors, such as the environment and age, can help determine a patient’s health status.”
“There has already been progress in effectively treating patients based on genetics, but currently the scope of genes we work with is limited,” adds Dr. Williams. “In the future, we hope to know how all 20,000 genes work in relationship to health and environmental factors.”
Dr. Williams is excited about taking the study a step further by delving deeper into the data. “We have the DNA and the RNA data. Now we want to go higher up the chain and gather more data on protein.”