Tropical disease researchers develop new tool to improve diagnosis of schistosomiasis

Neglected tropical diseases refer to a group of diseases that affect millions of people around the world, often in poverty-stricken regions, and yet do not receive the scientific attention they deserve. One such disease is schistosomiasis, a persistent parasitic infection that affects an estimated 250 million people in 78 countries, including Africa and Latin America.

Because schistosomiasis is understudied, improving diagnostic tools and treatments is often an afterthought. Diagnostics currently available to test for and treat schistosomiasis do not always detect the infection in its early stages or when the infection is mild. And blood tests often cannot distinguish active infections from past infections. Undiagnosed and untreated, schistosomiasis can lead to serious bladder or liver complications.

Now a team of researchers, including Jessica Fairley, an infectious disease specialist and associate professor at Emory University School of Medicine, has found ways to detect schistosomiasis where other, less sensitive tests cannot. not, leading to earlier treatment that may improve long-term outcomes. Their conclusions, reported in Scientific translational medicine, show promise for the development of a clinical antibody test capable of quickly and easily detecting even low levels of infection.

The research team used interpretable machine learning to separate actively infected individuals from those who had already been infected. Comparison of healthy and infected individuals in two human cohorts from Brazil and Kenya revealed previously uncharacterized signatures of active disease, which can be used for more precise diagnosis.

A partnership between science and engineering

Aniruddh Sarkar, co-author of the paper and a biomedical engineer at Emory and the Georgia Institute of Technology, primarily focuses his research on micro- and nano-scale fluid behavior on electronic chips. Since all biology takes place in fluids and microchips operate on the same microscopic scale that cells and biomolecules exist, Sarkar partnered with Fairley to tailor his expertise “to probe the processes biological at a very basic level,” as he puts it.

Fairley and Sarkar combined their knowledge of infectious diseases and biological data analysis to create a new and previously unknown way to diagnose schistosomiasis.

“The traditional gold standard is microscopic visualization of eggs of the schistosoma parasite,” says Fairley. “You look under a microscope, and it takes a long time. It can also miss an infection.”

By collaborating with Sarkar and machine learning specialist Jishnu Das of the University of Pittsburgh, another co-author of the paper, they were able to develop a machine learning platform capable of identifying groups of biomarkers of schistosomiasis which contained the most information on how the disease works. developed in specific patients. Sarkar says that basing diagnosis on the qualities of groups of antibodies rather than the quantity of a single marker will do a better job of detecting the disease early and reliably.

“When you look at these hundreds of measurements with just the human eye, even if you plot them with bar or pie charts, it can be difficult to find patterns,” says Sarkar. “It will look like a mess. That’s where these technologies come in. They highlight the part of the data that really matters.”

The researchers’ ultimate goal is to expand the antibody test to the point where it could replace many other diagnostic techniques and be used quickly and easily in rural areas where schistosomiasis is often most prevalent.

Fairley is optimistic that the partnership between infectious disease knowledge and machine-assisted data analysis can make a much greater contribution to public health.

“Introducing Jishnu and Aniruddh to the world of neglected infectious diseases allowed us to leverage their analytical expertise to create new diagnostics,” says Fairley. “And this interdisciplinary partnership shows that we can give understudied diseases like schistosomiasis the attention they deserve and advance global public health.”