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Potential of microRNAs as diagnostic markers for distinguishing malaria severity in samples from an Indian cohort
Aditi Gupta1, Kushagri Arora1,2, Sneha Bhandari3
1Department of Biotechnology, Institute of Applied Sciences & Humanities, GLA University, Mathura, Uttar Pradesh, 281406, India.
Background:
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.
Methods:
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.
Results:
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.
Conclusions:
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.
Insights
Early diagnosis of cerebral malaria (CM) is possible using a combination of three microRNAs (miRNAs). These biomarkers show potential for improving patient outcomes in severe malaria cases.
Area of Science:
- Biomarkers
- Molecular Diagnostics
- Infectious Diseases
Background:
- Cerebral malaria (CM) is a severe complication of Plasmodium falciparum infection, often fatal due to infected red blood cell sequestration.
- Early identification of CM biomarkers is critical for timely therapeutic intervention.
- MicroRNAs (miRNAs) released during organ injury are investigated as potential CM biomarkers.
Purpose of the Study:
- To assess the diagnostic potential of specific plasma microRNAs in patients with varying malaria severities.
- To evaluate the utility of microRNAs as non-invasive biomarkers for early cerebral malaria detection.
Main Methods:
- Quantified plasma levels of six microRNAs using TaqMan-RT-qPCR in patient groups: CM, severe non-CM (SNCM), uncomplicated malaria (UM), asymptomatic malaria (AM), and non-malarial febrile illnesses (nMFI).
- Employed Mann-Whitney U tests, logistic regression, and random forest machine learning (ML) for data analysis and CM prediction.
Main Results:
- Plasma levels of hsa-miR-21-5p, hsa-miR-150-5p, and hsa-miR-3158-3p significantly correlated with severe malaria (SM) and CM.
- A machine learning model combining these three miRNAs accurately predicted CM patients upon admission with 83% sensitivity, 100% specificity, and 92% balanced accuracy.
Conclusions:
- The combination of hsa-miR-21-5p, hsa-miR-150-5p, and hsa-miR-3158-3p represents a promising non-invasive biomarker panel for early CM diagnosis.
- This miRNA signature may significantly improve clinical management and enhance patient survival rates in cerebral malaria.
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