Molecular Biomarkers in Malaria: Linking Plasmodium Gene Variants to Early Diagnostic and Prognostic Tools

Malaria Plasmodium Molecular biomarkers early diagnosis

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November 24, 2025

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Malaria is a significant health issue of the world especially in tropical and subtropical areas where both Plasmodium falciparum and Plasmodium vivax infections are associated with serious morbidity and mortality. Discovery of molecular biomarkers with parasite gene variants has become an interesting strategy that can enhance early diagnosis, prognosis, and management of the disease. Plasmodium-based molecular biomarkers, including circumsporozoite protein (CSP), merozoite surface proteins (MSP-1, MSP -2), and apical membrane antigen-1 (AMA-1) are becoming more commonly utilized to determine the stage of infection and species. The parasite virulence, drug resistance, and host immune responses have been associated with gene polymorphisms and the expression profiles of these biomarkers, and could be monitored more accurately. The recent improvements of both genomic and proteomic technologies have made the identification of new biomarkers, such as circulating parasite DNA, RNA transcripts, and protein signatures, possible, making the diagnostic tests more sensitive. In addition, the deletion of molecular biomarkers like pfhrp2 and pfhrp3 has also been identified to be very important in the failure of rapid diagnostic tests (RDTs), and therefore genetic surveillance in localities where these problems are endemic is necessary. The introduction of these molecular tools into clinical practice offers a platform on which customized response to malaria treatment and control can be made. Knowledge about genetic diversity of Plasmodium species and how it relates to the severity of the disease may eventually result in devising more precise diagnosis measures, specific treatment, and successful vaccine candidates. Therefore, molecular biomarkers are fundamental ingredients in combating malaria between basic research and clinical implementation to predict and treat the disease more effectively.