The problem is that this criterion is very insensitive,” Trayanova says. “Of the patients with implanted defibrillators, only about 5 percent of those defibrillators ever fire because of an arrhythmia. In addition, the criterion misses any patients at risk for sudden cardiac death. We need a better way to stratify these patients.”
Her lab is working with cardiologist Katherine Wu ’89 in the School of Medicine to conduct retrospective tests on patients who have already received defibrillators. The tests are in the early phase, but Trayanova’s researchers have successfully predicted in 13 of 13 cases, to date, whether the defibrillator would fire. Those retrospective tests will continue through about 60 cases before moving to the next phase.
“Much of the work we do is about connecting the dots between the cell, which is heavily studied by one group of people, and the organ, which is heavily studied by a completely different group of people. That’s one of the fascinating things: How do you sort it all out?” Tom O’Hara
Studies with clinical potential are under way in three other areas. Atrial fibrillation is the most common form of arrhythmia and one that puts patients at higher risk for stroke. In patients with fibrotic remodeling in their atria, ablation currently has a very low level of success. Trayanova’s lab is working on predicting what would be the optimal ablation targets in these patients.In defibrillation, patients receive a painful electric shock that resets the rhythm of the heart to a normal beat. However, in patients with congenital heart disease, a transvenous approach to ICD lead placement is not possible. Trayanova’s lab is working on predicting, in a patient-specific manner, the optimal device placement in these patients. In addition, they are looking to use the patient-specific models to suppress the nerves that carry pain signals while administering the shock.
“The way we envision all of this working in clinical settings, the patients would get scanned and the images would get shipped to a company that specializes in this kind of modeling,” Trayanova says. “It would work just like in a lab test, and they’d come back the next day to say, ‘Here are our predictions for which therapy is best for this individual.’”
While this focus on clinical applications has been generating quite a bit of recent excitement, the Computational Cardiology Lab remains as focused as ever on work that aims to build a stronger base of knowledge about the mechanistic workings of heart disease.
Tom O’Hara came to Trayanova’s lab in the fall of 2011 after earning his doctoral degree from Washington University in St. Louis. His research focus is on finding out what’s going on in individual cells during heart failure.
“There are so many really interesting questions still out there about heart failure,” he says. “We know that older people and fatter people have a higher prevalence of heart failure, but exactly how and why that is true is not actually that obvious. Arrhythmia is something that happens on the organ level, but it’s probably based on things happening on a very small scale.”
O’Hara is working with colleagues at Imperial College London who have developed a novel way to run topographic scans of individual cells. So what happens to the cells in ailing heart?
“The heart cell is typically drawn like it’s a cylinder, but it’s actually more like a sponge,” he says. “There’s all kinds of holes in it that allow the outside environment to communicate with the core of cell.”
These indentations, called transverse tubules (or T-tubules, for short), tend to disappear in heart disease, making the cells less like the sponges they’re supposed to be and more like cylinders.
“There are functional consequences to this at the cell level,” O’Hara says. “My job as a modeler is to take that structural change at the cell level and say, ‘How does that change affect things in the whole heart? How severe—or not severe—are the consequences of this?’ ”
The postdoctoral work of Patrick Boyle focuses on optogenetics, in which low-energy light is used to stimulate and control cell behavior. The field is much further along in neurology, but Boyle is working with colleagues at Stony Brook University to understand its potential in cardiology.
“It’s a new technology, just coming on to the scene,” Boyle says. “And we think it could be used as an experimental tool where we can sort of prompt heart tissue to behave in certain ways so that we can get a better understanding of how arrhythmias come about.”
Down the road, Trayanova sees potential clinical applications in optogenetics as well.
“We are nowhere near there yet with optogenetics,” she says. “But the vision would be this: Instead of using paddles to deliver a shock to the heart, can we accomplish the same thing by shining a light? That would be so much less painful for patients.”
Boyle and O’Hara view the field of computational cardiology as a vital link to the research of colleagues working in more traditional avenues of medical research.
“Much of the work we do is about connecting the dots between the cell, which is heavily studied by one group of people, and the organ, which is heavily studied by a completely different group of people,” O’Hara says. “That’s one of the fascinating things: How do you sort it all out?” Boyle sees modeling as “a way of pulling back the veil.”
“We want to say, ‘OK, now that we know something is happening at the cellular level, what does this mean once we assemble all of the pieces?’” he says. “One of the most important pillars of our work is creating new questions and identifying new experiments for people to try.” Along with the fresh perspective of computational medicine come the fresh eyes of scientists in nontraditional disciplines delving into fields such as cardiology.
And so Trayanova’s lab is as focused on asking questions as it is on answering them. “We span the whole range—from clinical studies to subcellular studies,” Trayanova says. “Our goal is to see how what’s happening at the molecular level manifests itself in the level of the whole heart.”