Potential of microRNAs as diagnostic markers for distinguishing malaria severity in samples from an Indian cohort

Cerebral malaria (CM) is a subcategory of severe malaria (SM) and a major cause of death in Plasmodium falciparum infections, driven by the sequestration of infected red blood cells in the microvasculature of host vital organs. Identifying early biomarkers of CM is crucial for timely intervention. This study assessed the potential of microRNAs, produced upon organ injury, as biomarkers of CM. Plasma levels of six microRNAs were quantified in patients with CM (n = 43), severe non-CM (SNCM; n = 50), uncomplicated malaria (UM; n = 79), asymptomatic malaria (AM; n = 80), and non-malarial febrile illnesses (nMFI; n = 69) using TaqMan-RT-qPCR. Plasma levels of hsa-miR-21-5p, hsa-miR-150-5p, and hsa-miR-3158-3p correlated with SM (p < 0.0005) and CM patients (p < 0.0005), as determined by the Mann–Whitney U test and logistic regression models, with a study power of > 80%. A random forest machine learning (ML) model predicted CM patients on admission using a combination of three microRNA levels, achieving 83% sensitivity, 100% specificity, and 92% balanced accuracy. The combined use of hsa-miR-21-5p, hsa-miR-150-5p, and hsa-miR-3158-3p microRNAs may offer a powerful, non-invasive approach for early CM diagnosis, potentially improving clinical outcomes and patient survival.