Could pre-existing conditions hold the clue to new COVID-19 drugs?

The deadliest cases of COVID-19 often arise in patients with a variety of pre-existing conditions, known to medicine as “comorbidity.” A Morgridge Institute for Research project will investigate those disease relationships in the search for new drug treatments.

Morgridge investigator Ron Stewart, associate director of bioinformatics; and Kalpana Raja, postdoctoral research associate; have devised a literature-based discovery system called TripleMiner that could speed up the race to repurpose drugs to help in the battle against COVID-19. The duo received an award from the Wisconsin Alumni Research Foundation’s new Accelerator Challenge devoted to novel COVID-19 ideas.

Kalpana Raja

TripleMiner’s data frontier is the enormous PubMed database, which contains more than 30 million abstracts of published medical research articles dating back decades. By pairing searches for COVID-19 treatments, of which more than 40,000 articles have already been produced, with known related diseases, they hope to find a bounty of drug candidates worthy of deeper investigation and clinical trials.

“People with COVID-19 are frequently diagnosed with multiple comorbid diseases, such as diabetes and hypertension,” says Raja. “So, people are taking new drugs for COVID-19 along with the drugs they are already taking.” 

“On one hand, it is possible that interactions will happen between the repurposed drug and the comorbid diseases that cause side effects and drug intolerance,” she adds. “On the other hand, we can find and repurpose drugs with comorbidity in mind, limiting the number of drugs needed.”

The ideal outcome would be to find drug candidates or genetic clues that are helpful for both COVID-19 and for many comorbid diseases, leading doctors to prescribe fewer, but more effective treatments. Drug discovery is commonly a multi-year process — a timeline we can’t afford with COVID-19, Stewart notes. The goal of TripleMiner is to compress that timeline down to months.

In addition to diabetes and hypertension, known comorbidities with COVID include dyspnea (shortness of breath), lymphopenia (a shortage of essential white blood cells) and abnormal blood clotting. One exciting aspect of TripleMiner, says Stewart, is it may help to identify new comorbidities that can help physicians better understand COVID-19.

Ron Stewart
Ron Stewart

There are remarkably few studies in the published literature looking at COVID-19 disease connections, so the team hopes to find some low-hanging fruit in their searches. In the first proof of concept of TripleMiner, Raja looked for connections with lymphopenia, and found seven “hits” of drugs that are connected to both conditions. Some of those drugs, such as remdesivir, are already known to clinicians and are in active clinical trials. But many others represent potential new candidates.

Triple Miner is a system based on the pioneering work of the late Don Swanson, a former dean of the University of Chicago Library School who invented the practice of literature-based discovery. His first highly successful inquiry used the vast Medline research paper database to find drugs that might act against Raynaud’s disease, a condition that causes blood flow problems in fingers, toes and other extremities. The investigation led to the discovery of fish oil as a possible treatment, which was later validated by clinical trials and is now one of the world’s most commonly used drugs to reduce blood viscosity.

The beauty of TripleMiner is, like the Swanson example, the capability to find a useful drug from a totally unexpected source — something that may have been reported decades ago. But this is only the first step, Stewart emphasizes, and the team needs to find collaborators who can test promising drugs for effectiveness.

“We have a lot of work to do, it’s a very ambitious project,” Stewart says.