Dynamic Duality

A core faculty of the Institute for Medical Engineering & Science (IMES), Collin Stultz works double-duty. Earning his MD from Harvard Medical School and PhD in biophysics from Harvard University, he is both (1) a practicing cardiologist and (2) an MIT faculty research scientist in the Electrical Engineering and Computer Science (EECS) department. His focus at MIT is twofold, he says: “small things you can’t see with the naked eye and big things that you can.”

The “small things”—alpha synuclein and amyloid beta, two proteins in the brain that can dangerously build up into plaques—have big implications in the study of two diseases: Alzheimer’s and Parkinson’s. And Stultz’s study has helped depolarize the research community.

“It’s interesting when things are controversial. There were two camps on what alpha-synuclein looked like. So we thought, ‘why don’t we use some of the computational techniques that we’ve developed and see?'” says Stultz. “We reached out to a researcher on one side of the debate, and he shared his experimental data with us.”

The result was a game-changing, gap-bridging study that modeled alpha-synuclein in both floppy and rigid forms, a crucial insight to help move beyond debate and toward disease dynamics. (See related story https://imes.mit.edu/sorting-out-the-structure-of-a-parkinsons-protein/ )

Today Stultz is optimistic about his group’s further research of alpha synuclein. Recent data suggests the earliest phases of the dementia-causing aggregates are the biggest culprits in neuron damage.

“We’re interested in finding common structural motifs, common species, and what makes these small, loose aggregates neurotoxic,” says Stultz. “If we can have a better sense of these early structures, perhaps therapies can be designed—something that will get to where these plaques are being formed and prevent them from aggregating, that will target these early neurotoxic species and get rid of them. That’s the endgame.”

Stultz says studying brain proteins was “a natural progression” for him. As a student, he took time off from medical school for formative PhD study with Martin Karplus, winner of the 2013 Nobel Prize in Chemistry, who helped invent the field of molecular simulations of proteins. At MIT, Stultz’s team first studied collagen, a protein involved in arteriosclerosis (a.k.a. hardening of the arteries), where they made important discoveries. Today he continues to study “big things” in the cardiovascular sphere.

“We use machine learning to try and predict patients at high risk of death after heart attack,” he says. “The holy grail in cardiovascular medicine is finding out who to worry about. Physicians have lots of expensive tools—MRIs, CT scans, very fancy stress tests. But in many parts of the world you don’t have access to these. There’s a need to develop metrics to restratify patients in low cost settings, using data that are easy to get. Because not everybody lives in Boston, close to Mass General or Brigham and Women’s Hospital.”

Partnering with Professor John Guttag of the Computer Science and Artificial Intelligence Laboratory (CSAIL) allows Stultz’s team to analyze physiological data. Such powerful collaborations abound at MIT.

“I’ve got phenomenal colleagues. Just look at EECS: there is no place else in the world that has the breadth of expertise and depth of knowledge. When you apply these particular skillsets to medical problems, that’s the real strength of having an Institute for Medical Engineering and Science at MIT. Arup Chakraborty* deserves a tremendous amount of credit. When you look at how IMES has grown, the faculty it has recruited, I think it is poised to leave an indelible imprint on the Institute.”

Stultz himself, who credits his informally educated Jamaican mother with encouraging him, hopes to leave an indelible imprint on human health. Times two.

“My clinical experience impacts the direction of the research. Knowing what you should work on is not always transparent to people without a medical background,” he says. “And the always-questioning aspect is really good for a clinician. You want to do the best for your patient, to make decisions in the most evidence-based way.

“What motivates me comes directly from patients that I have treated and have interacted with. We want to do things that will benefit sick people in the long run. That’s what motivates my group. That’s our modus operandi.”

*Arup Chakraborty is Director, Institute for Medical Engineering & Science; Robert T. Haslam Professor of Chemical Engineering; and Professor of Physics, Chemistry, and Biological Engineering.