In 2015, then-President Barack Obama launched a precision medicine initiative, saying his promise was "to deliver the right treatments, on time, every time to the right person." A biomedical engineer at the University of Washington in St. Louis answered the call, taking a significant step toward precision medicine for patients with a life-threatening irregular heartbeat, determining in which patients a commonly used drug treatment would be more beneficial.
Jonathan Silva, associate professor of biomedical engineering at the School of Engineering and Applied Sciences, was part of an international team that determined which patients would benefit most from a commonly used drug treatment.
The results of the survey are published online in Circulation Search on December 18th.
Silva joined the author Wandi Zhu, a doctorate candidate in his laboratory, and colleagues at the University of Pavia, Italy. Together, they investigated the effectiveness of the drug mexiletine in patients with a genetic mutation that causes Long QT syndrome, a disorder that arises from the inability of the heart to adequately repolarize, leading to irregular heartbeat – or arrhythmia. The drug was given to patients with long QT syndrome for a decade but was ineffective, sometimes even harmful, for most. Silva's team wanted to know why.
Traditionally, researchers have only been able to observe certain variables in the heart. Silva's laboratory approach was to create a statistical model that connected the variable properties of a patient's phenotype or the physical expressions of a genetic trait. Using fluorometry, a technique that measures changes in the environment of a fluorescent molecule, they understood the nanoscale interaction of mexiletine within the heart's sodium channel.
"What this told us was that there was a particular part in the Domain III voltage sensing domain that was actually related to the drug's effect," Silva said. "Although theories before us have linked the regulation of drug blockage to a certain channel driving state, we have linked it to a specific part of the channel. This better understanding of how the channel works and how that part affects drug blockade has enabled us to make that prediction about whether patients would react or not. "
To test their theory, Silva and his team analyzed 15 different mutations of patients who were diagnosed with long QT syndrome and found a very strong correlation with one of the electrical gates of the sodium channel known as the Domain III voltage sensing domain, but not with the traditional variables that are used.
"This gave us a lot of confidence that the three-voltage domain domain is controlling the patient's response to the drug," he said.
The team then applied their theory to the blind data of eight Priori patients in Italy. When Silva's team members sent their predictions back to the researchers, they found they had correctly predicted seven of the eight patients.
Then the team plans to conduct a larger clinical trial of their method.
"Now that we have strong evidence that this part of the channel is regulating the drug block, we want to use a similar approach for a much larger set of patients," he said. "We want to see if we can use these methods that are applicable to a rare disease and use a similar approach to understand how commonly prescribed drugs affect more common arrhythmias."
This article has been republished from materials provided by the University of Washington in St. Louis. Note: Material may have been edited for length and content. For more information, please contact the cited source.
Zhu, W., Mazzanti, A., Voelker, T., Hou, P., Moreno, J.D., Angsarararux, P .; . . Silva, J.R. (2018). Predicting Patient Response to Mexiletine Antiarrhythmic Based on Genetic Variation: Personalized Medicine for Long QT Syndrome. Circulation Search. doi: 10.1161 / circresaha.118.314050