Leveraging Long-term Health Data and Exome Sequencing for Autism-Related Gene Discovery

Healthcare providers, government agencies and research groups are using data drawn from decades of electronic medical records to improve patient care and to identify the genetic mutations responsible for conditions such as autism spectrum disorders. Called the Learning Health System model, the approach is helping transform the health care system into one that can more rapidly learn, adapt and improve.

In this lecture, Dr. David Ledbetter will describe Geisinger Health System’s Precision Health Center. The center makes available more than 20 years’ worth of electronic health data for research and innovation. In partnership with Regeneron Genetics Center, Geisinger now has exome sequence data for more than 92,000 patient-participants, with an ultimate goal of 250,000. Those data have already led to the successful identification of new drug targets, improved prevalence estimates of the most common Mendelian disorders (FH, BRCA, Lynch) and the identification of autism spectrum and neuropsychiatric CNV disorders in 0.8 percent of the dataset’s adult participants. These results are already having a positive impact on individual participants, their family members and their primary care physicians.