Research Summary: This study identified plasma microRNAs (hsa-miR-21-5p, hsa-miR-150-5p, hsa-miR-3158-3p) as accurate, non-invasive biomarkers for detecting patients with cerebral malaria, enabling timely diagnosis and improved patient outcomes.
Author interview
Aditi Gupta is a biotechnology researcher focused on infectious-disease diagnostics, specializing in microRNA biomarkers and molecular epidemiology to improve early detection and management of severe malaria.
Lab: Dr. Himanshu Gupta , GLA University, Mathura
Lab social media: #Gupta-Sikkalab
What was the core problem you aimed to solve with this research?
Cerebral malaria, which is a complication of severe malaria, lacks reliable early biomarkers, delaying diagnosis and treatment and contributing to high mortality in Plasmodium falciparum infections. Our research sought to fill this critical diagnostic gap.
How did you go about solving this problem?
Plasma levels of six candidate microRNAs were quantified across well-defined patient groups using TaqMan RT-qPCR. Statistical analyses identified significant associations, and a random forest machine-learning model combining three key microRNAs achieved high diagnostic accuracy for patients with cerebral malaria at admission.
We found that checking the levels of three tiny molecules (microRNAs) in the blood can warn doctors early if a patient is at risk of cerebral malaria. This simple test could help start treatment sooner and save lives, especially in areas with limited medical facilities. — Dr. Himanshu Gupta
How would you explain your research outcomes (Key findings) to the non-scientific community?
We discovered that three tiny molecules in blood—microRNAs—act as early ‘warning signals’ of cerebral malaria. Measuring their levels allowed us to identify patients with cerebral malaria, enabling faster treatment and saving lives without using expensive methods like MRI.
What are the potential implications of your findings for the field and society?
For the field: Establishes microRNAs as robust, non-invasive biomarkers for early cerebral malaria detection and demonstrates the value of integrating molecular diagnostics with machine learning, encouraging further biomarker-driven research.
For society: Enables earlier, more accurate diagnosis, reducing treatment delays, lowering mortality, and supporting affordable point-of-care testing in malaria-endemic regions, thereby easing the broader socio-economic burden of malaria.
What was the exciting moment during your research?
Seeing that three microRNAs could predict cerebral malaria with high specificity and sensitivity, and with over 90% accuracy, was thrilling—a clear sign that a simple blood test could one day help doctors save lives in malaria-endemic areas, especially for patients who have parasites sequestered in their vital organs.
Paper reference: Gupta, A., Arora, K., Bhandari, S. et al. Potential of microRNAs as diagnostic markers for distinguishing malaria severity in samples from an Indian cohort. BMC Infect Dis 25, 1065 (2025). https://link.springer.com/article/10.1186/s12879-025-11459-4
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