Although genome sequencing has shown promise as a tool for the type of preventive care that will be necessary for successful accountable care, several drawbacks--such as the potential for over-treatment--remain, according to a Wall Street Journal article.
In particular, over-treatment could result from unique genetic variations in each patient that could, at first, raise concerns, but ultimately might not cause any disease, Michael Watson, executive director of the American College of Medical Genetics and Genomics, told WSJ.
Additionally, the article points out that genetics are only one of several causes of conditions such as heart disease, meaning that genome sequencing won't always be able to help with prediction and treatment plans. The article also mentions diabetes as one diseases that has causes beyond genes, although Stanford University researcher Michael Snyder was able to uncover his own genetic predisposition to type 2 diabetes, according to a study published in March in the journal Cell. Snyder ultimately developed diabetes, but changed his health habits early enough to keep it under control.
"These results have important implications and suggest new paradigm shifts," the authors wrote in Cell. "First, genome sequencing can be used to direct the monitoring of specific diseases and second, by following large numbers of molecules, a more comprehensive view of disease states can be analyzed to follow physiological states."
Still, the price of a full genetic map is expected to fall quickly, according to the article. Additionally, such tests likely will become increasingly automated, according to a blog post on Genomes Unzipped by Daniel MacArthur, a genetics researcher at Massachusetts General Hospital.
"With every genome we analyze, we get better at automating the easy steps, fix mistakes in our databases that might otherwise lead to wild goose chases and obtain more unambiguous evidence about the clinical significance of each mutation," MacArthur said. "The genome interpretation of 2017 won't be a drawn-out process involving constant back-and-forth between highly paid specialists. It will be a complex but thoroughly automated series of analysis steps, resulting in only a few potentially interesting results to be passed on to geneticists and clinicians for manual checking and signing off."