Host-parasite biochemical reprogramming in malaria: clinical biochemistry, pathogenesis, and biomarker implications
Host-parasite biochemical reprogramming in malaria
DOI:
https://doi.org/10.54117/9jhp8e58Keywords:
Plasmodium falciparum, Severe malaria, Clinical biochemistry, Biochemical markers, Host–parasite interaction, Oxidative stress, Metabolic reprogramming, Metabolomics, Proteomics, Multi-omics, Artificial intelligence, Biomarker discovery, Prognostic biomarkersAbstract
Severe malaria specifically cause plasmodium falciparum infection is the leading cause of morbidity and mortality in endemic region like Nigeria. The severe malaria disease is characterized by excessive alterations in several clinical biochemical parameters that demonstrate the Pathophysiology process behind the alterations. This review summarizes the integrated analysis of the mechanism underling the major biochemical changes associated with plasmodium falciparum infection, including hemolysis-induced anemia (both intravascular and extravascular), hepatic injury and dysfunction, renal injury and impairment, metabolic abnormalities, electrolyte imbalance and hypoglycemia. These alterations are the byproducts of complex interaction between plasmodium falciparum and its human host arising from erythrocyte destruction, microvascular sequestration, tissue hypoxia and unregulated immune response.
The review also highlighted in detail the observed biochemical derangement in severe malaria infection is amplified by oxidative stress and inflammatory cytokines which further contribute to multiple organ dysfunctions. Furthermore, routine biochemical markers such as serum lactate, bilirubin, creatinine and liver enzymes are analyzed for their clinical relevance in severity assessment, prognosis and therapeutic monitoring. Discovery of novel biomarkers with improved sensitivity for early detection of severity and risk stratification from recent finding in metabolomics and proteomic profiling were also analyzed in this review.
Current scientific progress stress the need to integrate conventional clinical biochemistry analysis with genomics, proteomics, and artificial intelligence-based predictive models to enhance diagnostic precision and enable personalized disease management. Collectively, this approach represents a major avenue for future research with significant potential to transform clinical diagnosis, improved prognostic accuracy and targeted therapeutic intervention in severe malaria.
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