According to the Center for Disease Control and Prevention (CDC), heart disease is the leading cause of death for men, women, and people of most racial and ethnic groups in the United States. About 655,000 Americans die from heart disease each year, which is about one in every four deaths.
Calcific aortic valve disease, the third leading cause of heart disease overall, occurs when calcium starts to accumulate in the heart valves and vessels over time, causing them to gradually harden like bone. This leads to obstruction of blood flow out of the heart’s pumping chamber, causing heart failure. Unfortunately there is no treatment for this condition, leaving patients only with the option of surgery to replace the heart valve once the hardening is severe enough.
But thanks to a CIRM-funded ($2.4 million) study conducted by Dr. Deepak Srivastava and his team at the Gladstone Institutes, a potential drug candidate for heart valve disease was discovered. It has been found to function in both human cells and animals and is ready to move toward a clinical trial.
For this study, Dr. Srivastava and his team looked for drug-like molecules that had the potential to correct the mechanism in heart valve disease that leads to gradual hardening. To do so, the team first had to determine the network of genes that are turned on or off in the diseased cells.
Once the genes were identified, they used an artificial intelligence method to train a machine learning program to detect whether a cell was healthy or diseased based on the network of genes identified. They proceeded to treat the diseased human cells with nearly 1,600 molecules in order to identify any drugs that would cause the machine learning program to reclassify diseased cells as healthy. The team successfully identified a few molecules that could correct diseased cells back to a healthy state.
Dr. Srivastara then collaborated with Dr. Anna Malashicheva, from the Russian Academy of Sciences, who had collected valve cells from over 20 patients at the time of surgical replacement. Using the valve cells that Dr. Malashicheva had collected, Dr. Srivastara and his team conducted a “clinical trial in a dish” in which they tested the molecules they had previously identified in the cells from the 20 patients with aortic valve hardening. The results were remarkable, as the molecule that seemed most effective in the initial study was able to restore these patients’ cells as well.
The final step taken was to determine whether the drug-like molecule would actually work in a whole, living organ. To do this, Dr. Srivastava and his team did a “pre-clinical trial” in a mouse model of the disease. The team found that the therapeutic candidate could successfully prevent and treat aortic valve disease. In young mice who had not yet developed the disease, the therapy prevented the hardening of the valve. In mice that already had the disease, the therapy was able to halt the disease and, in some cases, reverse it. This finding is especially important since most patients aren’t diagnosed until hardening of the heart valve has already begun.
Dr. Christina V. Theodoris, a lead author of the study who is now completing her residency in pediatric genetics, was a graduate student in Dr. Srivastava’s lab and played a critical role in this research. Her first project was to convert the cells from patient families into induced pluripotent stem cells (iPSCs), which have the potential of becoming any cell in the body. The newly created iPSCs were then turned into cells that line the valve, allowing the team to understand why the disease occurs. Her second project was to make a mouse model of calcific aortic valve disease, which enabled them to start using the models to identify a therapy.
In a press release from Gladstone Institutes, Dr. Theodoris, discusses the impact of the team’s research.
“Our strategy to identify gene network–correcting therapies that treat the core disease mechanism may represent a compelling path for drug discovery in a range of other human diseases. Many therapeutics found in the lab don’t translate well to humans or focus only on a specific symptom. We hope our approach can offer a new direction that could increase the likelihood of candidate therapies being effective in patients.”
In the same press release, Dr. Srivastava emphasizes the scientific advances that have driven the team’s research to this critical point.
“Our study is a really good example of how modern technologies are facilitating the kinds of discoveries that are possible today, but weren’t not so long ago. Using human iPSCs and gene editing allowed us to create a large number of cells that are relevant to the disease process, while powerful machine learning algorithms helped us identify, in a non-biased fashion, the important genes for distinguishing between healthy and diseased cells.”
The full results of this study were published in Science.