Researchers at the University of Georgia's Center for Tropical and Emerging Global Diseases have developed the first test to determine whether treatment for Chagas disease was effective.
An estimated 6 million to 8 million people worldwide are infected with Trypanosoma cruzi, the parasite that causes Chagas disease.
"Currently during drug trials, we can only determine if a drug fails," said Rick Tarleton, Regents' Professor in the UGA Franklin College of Arts and Sciences. "A test of cure can indicate if a drug succeeds in clearing the infection."
Part of the problem in determining if T. cruzi infection is cured by treatment is that the immune system is often very good at controlling the infection. Current tests are not sensitive enough to detect low levels of parasites.
Rick Tarleton
"If you have a cup a tea with a little bit of tea leaf in it you may not get a tea leaf in every sip," Tarleton said. "When there are so few parasites in the blood stream, it decreases the chances that a blood draw will contain any.
"We've taken two samples from the same individual at the same time-one sample tests positive, and the other tests negative. Which is right?"
Thousands die from Chagas each year
Chagas disease kills more than 10,000 people every year, mainly in Central and South America. But it is also a concern in the United States, where the Centers for Disease Control and Prevention estimates there are 280,000 people living with this disease.
And it's not only humans that suffer from this disease. Many mammals, including wildlife and dogs, can also become infected.
The Tarleton group conducted large-scale PCR testing of samples from naturally infected macaque monkeys, dogs and humans. The team also fragmented the DNA to more evenly distribute it within the sample. Standard PCR testing doesn't fragment DNA.
"If we go back to Rick's tea leaf example, it's like taking the whole tea leaf, breaking it up into tiny bits and then stirring the tea before taking a sip," said Brooke White, lead researcher of the study. "This increases the chances of detecting DNA."
New test accurately detects parasite infection in monkeys, dogs and humans
The naturally infected macaques were monitored over 12 months with monthly blood tests. A subset also had blood samples drawn seven times over four weeks. In addition to the exhaustive PCR testing, the researchers grew T. cruzi cultures from the blood samples, which confirmed that the new protocol accurately detects infection even when the parasite number is very low.
"Since the macaques acquired the infection in the same way as humans and dogs and their disease progression is the same, we are confident that this test will work in other species," said Tarleton.
Collaborators at Texas A&M and in Argentina also provided naturally infected dog and human samples, respectively. The researchers saw similar results to the macaques.
A need for better drug treatment for Chagas disease
There is a need for new drug treatments for Chagas disease. But without a true test of cure, researchers only know what does not work. While the new protocol is effective, the researchers noted that it is also labor intensive and time consuming, which translates into being costly.
As part of the study, the researchers sought out technologies that could make the process faster and cheaper.
"This test of cure is a real game changer for drug treatment studies," said White. "We are already working with other research groups in hopes of creating a quicker and cheaper method of testing parasite load in their drug treatment studies in macaques, dogs and humans."
The researchers began collaborating with Countable Labs whose new technology allows for larger samples to be assayed faster. Reducing costs and increasing efficiency makes it much more likely for this test to be used in a clinical setting.
"Our goal now is to move this test out of the research lab and into a clinical diagnostic lab where it will be widely accessible for detecting human and dog infections and tracking treatment outcomes," said Tarleton.
The study was co-authored by Daniel Hall of the UGA Department of Statistics. Additional co-authors include Carolyn Hodo, Sarah Hamer, Ashley Saunders and Susana Laucella.
