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Databases of the Heart

A computational biologist takes on the world’s number one killer.

Written by Philip Baker
Bohdan Khomtchouk Headshot

When Alexandra Ligay, a student in the Master of Science in Biomedical Informatics (MScBMI) Program, joined the lab of Dr. Bohdan Khomtchouk for her Capstone project, Dr. Khomtchouk’s plan was for her to extend important research pursued by previous MScBMI Capstone students in his group.

An instructor in the Section of Computational Biomedicine and Biomedical Data Science at UChicago Medicine’s Institute for Genomics and Systems Biology and sponsor of Capstone projects for UChicago’s MScBMI program, Khomtchouk leverages bioinformatics and computational biology methods to illuminate novel cardiovascular, renal, and metabolic biology with the goal of enabling new therapeutics.

With former Capstone students, he was building a database that aimed to collect all the existing single-cell genomic data relevant to cardiovascular disease. Combining databases like this with the power of machine learning lets researchers see wider and deeper into the genetic factors driving cardiovascular disease than ever before.

Shortly after Ligay’s arrival, however, the Khomtchouk Lab made the surprising discovery of a formerly unknown vascular cell.

“Once we saw a path leading to an interesting paper we took it and ultimately it paid off,” Khomtchouk notes. The paper describes new potential drug targets to treat atherosclerosis and coronary artery disease. In the press release for the publication, Khomtchouk compares finding a new vascular cell to discovering new star clusters in the sky.

The study is among the first to leverage big data, single-cell sequencing, and genomics to find new drug targets in heart disease. It’s a perfect example of the type of translational research that Khomtchouk sees as pivotal to the development of cardioinformatics, a field he brought into view by coining the term cardioinformatics in a 2019 paper.

“At the end of the day, it’s about pharmaceuticals because that’s what can actually help people,” he says. “You can have all the fanciest findings in the world about mechanism, but mechanism that never translates into a drug is kind of useless for healthcare as a system. Our goal is to find druggable mechanisms and druggable targets that can be modulated by therapeutic approaches.  And we do that by using data science and a vast array of computational techniques.”

Battling complexity with data

Despite being the world’s number one killer, research into cardiovascular disease from a computational perspective has generally lagged behind oncology and neurology. This is largely due to its forbidding complexity, with diseases like heart failure typically arriving along with a host of additional comorbidities, like type 2 diabetes or chronic kidney disease.  Meanwhile, clinical indications like heart failure with preserved ejection fraction (HFpEF) or dilated cardiomyopathy (DCM) are made especially computationally challenging due to their complex genetic heterogeneity. 

“There is so much more complexity to identifying precision treatment for cardiovascular disease than for cancer and other areas,” says Khomtchouk. “In the case of cancer, you can biopsy a tumor and genetically sequence it and then fit the right drug to that profile. That’s precision oncology. But when a patient presents with cardiovascular disease, you don’t have the option of going in there and cutting out a piece of their heart or vasculature and sequencing it etcetera.”

Traditional risk factors, like high cholesterol and blood pressure, have been useful measures for treating heart disease up until now, but Khomtchouk explains that they’re ultimately a fairly blunt approach when contending with genetic variation in the general population. “It’s like when you’re a hammer and everything looks like a nail,” he says. “It’s not the most optimal treatment on an individual patient-by-patient basis and so there’s a lot of unmet need for safer more efficacious heart drugs.”

What’s more, Khomtchouk knows that time is pressing. As the population above sixty-five triples in the next thirty years, the cardio drug discovery landscape and further strains on the medical healthcare system are set to become all the more challenging.

The answer lies in building larger, more complete databases. With them, researchers can develop fuller pictures of the human genome along with the patterns and connections taking place within patients with heart failure and other disease indications with high clinical unmet need. 

“I think patients with heart conditions in the not-so-distant future will be able to get very precise therapeutics to treat their illnesses in a way that’s specific to their genomic make-up,” Khomtchouk says. “That’s at least the goal of precision cardiology that we’re all aiming for, which will ultimately decrease death and thereby cut cost on the healthcare system in the long term.”

Connections with industry

Meeting these objectives means attracting more students and researchers to the cardioinformatics field, a fact that makes Khomtchouk’s collaboration with the MScBMI program a productive two-way partnership. With plenty of low-hanging fruit, students have the opportunity to experience a dynamic and fast-evolving landscape while also making a difference. 

“It’s not like big tech where you spend your days optimizing a search engine or social media platform,” he says. “Here you’re optimizing drug delivery and drug development. You’re saving future lives. A lot of the students I’ve worked with have gone on to very nice bioinformatics positions at places like AbbVie and Pfizer and some other big pharma and biotech companies.”

Khomtchouk is also the founder of Dock Therapeutics Inc., a biotech startup company spun out of his lab during NSF i-Corps, an accelerator program hosted through the UChicago Polsky Center for Entrepreneurship and Innovation and Booth School of Business. The company has already built relationships with some of the biggest names in pharma and is presently conducting the largest computational study to-date looking at heart failure with preserved ejection fraction (HFpEF), a notoriously complex indication.  Dock’s Chief Medical Officer, Dr. Michael H. Davidson, is a world-renowned cardiologist and nationally recognized expert in lipidology and heart disease, with >250 publications in leading medical journals and >1000 clinical trials.  Having sold Corvidia Therapeutics last year to Novo Nordisk for $2.1B, and Omthera Pharmaceuticals to AstraZeneca for $443M in 2016, Dr. Davidson brings on invaluable physician-scientist and entrepreneurial expertise to Dock’s mission statement, which is to build better drugs through computation.  

A central goal of Dock Therapeutics is to solve a limitation that researchers face when investigating cardiovascular disease using computational methods. Today’s databases are still overwhelmingly comprised of the genetic data of white Europeans. Because of this, even the determinants of events as common as stroke remain out of reach.

“We are missing a huge sector of the general population,” Khomtchouk says. “And that means we’re missing out on all the disease heterogeneity and genetic variation in the population. There’s so much missing data on Black, Hispanic, and Pacific Islander populations. Integrating that would be a huge part of unlocking and harnessing the power of genetic data when it comes to the more complicated indications, stroke among them.”

Dock Therapeutics’ aim, a task too big for a single lab or department, is to raise funding to put together the world’s largest human disease data registry relevant to cardiovascular/renal/metabolic indications in historically underrepresented racial and ethnic groups. For Khomtchouk, it’s the crucial next step for a field—cardioinformatics—he’s always imagined as foundationally translational and in search of real-world impact.

“What we’ve been trying to do all along is show that cardioinformatics is not just a scholarly pursuit in and of itself,” Khomtchouk says. “It’s a translational large-scale initiative focused on enabling better therapeutics. Ultimately, that means better more transformative drugs, improved patient care, and less death.”

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