A single test result can only be as good as the test itself, and we haven’t yet created a test that performs with truly perfect precision and accuracy. Yesterday’s plenary “Towards Precision Medicine” showed how precision medicine is seeking—and finding—an extraordinary new depth of knowledge that can inform not only diagnosis and treatment, but our understanding of human disease.

In his talk, Euan Ashley, MD, explored the possibilities now unfolding from our ability to sequence the human genome rapidly for under a thousand dollars. He presented compelling cases from the Undiagnosed Disease Network (UDN) that demonstrated the potential of precision medicine to better characterize the tens of millions of individuals in the U.S. living with a rare disease. The UDN is an NIH funded study that bridges the gap between clinical care and research using genetic data to diagnose and treat rare diseases. To date the network has evaluated over 600 individuals and has found a diagnosis for over a third of them. In each of the cases Ashley presented, genome sequencing allowed for a deeper understanding of disease, enabling more targeted therapy in 20% of the cases. We can ultimately save money and prevent patients from jumping from one doctor to another by sequencing patients early, noted Ashley.

Accurate and precise analysis and interpretation of large-scale data, however, remains the bottleneck in pinpointing the diagnosis of these rare diseases. To overcome this bottleneck, technology and analysis algorithms must be optimized, with special attention to quality metrics and standardizing data interpretation, Ashley emphasized. This will ultimately enable global sharing of accurate data. Improvements and new methodologies in sequencing and algorithms will allow for coverage and identification of regions that are currently problematic—such as regions of the genome that are repetitive, polymorphism hotspots, G-C rich, and structural variants—as well as increased quality coverage of sequencing data. For example, the use of long-read sequencing technology has enabled his team to identify a structural variant in a less characterized area of the genome to identify Carney Complex, a rare disease characterized by multiple benign tumors.

Ashley also introduced a new way of looking at precision healthcare, which includes the use of digital health technologies for disease prevention and health promotion. “There is great power in digital interventions,” Ashley said. “No drug can equal the potential of physical activity in lowering the risk of cardiovascular disease.”

Wearable digital devices can provide a complete picture of physical activity, sleep, and exercise, Ashley said, and this information can be used to reduce the risk of future disease. For example, in 2015, the app-based MyHeart Counts study was introduced through Apple’s research kit. It allows users to track sensor-based parameters of their physical activity along with a questionnaire to capture sleep, life-style factors, and other parameter of disease risk or predisposition. Results from this study demonstrated that it now feasible to consent and engage a large population of mobile device users, to gather large scale de-identified data in real time from these devices, and identify types of activity patterns that relate to presence of disease, Ashely said.

It is clear that new technologies are being adopted very rapidly. And the potential for these technologies to predict and prevent disease is becoming more clear. At the same time, researchers and clinical scientists must deploy these tools carefully, Ashley emphasized. “We have to think carefully about what we are doing and how we use these technologies,” he said.