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Schistosomiasis isn't usually diagnosed until the late stages of the disease.
Our study provides a clear path forward to improving early detection and diagnosis by identifying the hidden information in blood that signals active, early stage infection.
Your body responds to a schistosomiasis infection by mounting an immune response involving several types of immune cells, as well as antibodies specifically targeting molecules secreted by or present on the worm and eggs. Our study introduces two ways to screen for certain characteristics of antibodies that signal early infection.
The first is an assay that captures a quantitative and qualitative profile of immune response, including various classes of antibodies and characteristics that dictate how they communicate with other immune cells. This allowed us to identify specific facets of the immune response that distinguish uninfected patients from patients with early and late-stage disease.
Second, we developed a new machine learning approach that analyzes antibodies to identify latent characteristics of the immune response linked to disease stage and severity. We trained the model on immune profile data from infected and uninfected patients and tested the model on data that wasn’t used for training and data from a different geographical location. We identified not only biomarkers for the disease but also the potential mechanism that underlies infection.
Why it matters
Schistosomiasis is a neglected tropical disease that affects over 200 million people worldwide, causing 280,000 deaths annually. Early diagnosis can improve treatment effectiveness and prevent severe disease.
In addition, unlike many machine learning methods that are black boxes, our approach is also interpretable. This means it can provide insights into why and how the disease develops beyond simply identifying markers of disease, guiding future strategies for early diagnosis and treatment.
What still isn’t known
The schistosomiasis infection signatures we identified remain stable across two geographical regions across two continents. Future research could explore how well these biomarkers apply to additional populations.
Further, our work identifies a potential mechanism behind disease progression. We found that a particular immune response against a specific protein on the surface of the worm signals an intermediate stage of infection. Understanding how the immune system responds to this understudied antigen could improve diagnosis and treatment.
What’s next
Besides improving our understanding of how the immune system responds to different stages of infection, our findings identify key antigens that could pave the way for designing cost-effective and efficient approaches to diagnosis and treatments. Our next steps will include actually deploying these strategies in the field for early detection and management of disease.
The Research Brief is a short take about interesting academic work.
Trirupa Chakraborty is affiliated with Light Up non-profit organisation, based in India. The organisation does not have any connection with or benefits from this article.
Aniruddh Sarkar has received grant funding from the NIAID, BARDA, Task Force for Global Health (TFGH), Atlanta Center for Point-of-Care Technologies (ACME POCT), Center for Childhood Infections & Vaccines (CCIV) and the Bernie Marcus Early Career Professorship at Georgia Tech
Jishnu Das has research grant funding from the NIH (NIAID, NHGRI, NIAMS, NEI, NCI, NHLBI, NIMH), DoD and the Rainin Foundation. He consults for Seromyx on a case-by-case basis and receives corresponding financial compensation including stock options. Seromyx has no direct connection to (including benefitting from financially or otherwise) this article.
Source: The Conversation
