PLoS Neglected Tropical Diseases (Mar 2024)

Harnessing Schistosoma-associated metabolite changes in the human host to identify biomarkers of infection and morbidity: Where are we and what should we do next?

  • Mireille Kameni,
  • Fungai Musaigwa,
  • Leonel Meyo Kamguia,
  • Severin Donald Kamdem,
  • Gladice Mbanya,
  • Poppy H L Lamberton,
  • Justin Komguep Nono

DOI
https://doi.org/10.1371/journal.pntd.0012009
Journal volume & issue
Vol. 18, no. 3
p. e0012009

Abstract

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Schistosomiasis is the second most widespread parasitic disease affecting humans. A key component of today's infection control measures is the diagnosis and monitoring of infection, informing individual- and community-level treatment. However, newly acquired infections and/or low parasite burden are still difficult to diagnose reliably. Furthermore, even though the pathological consequence of schistosome egg sequestration in host tissues is well described, the evidence linking egg burden to morbidity is increasingly challenged, making it inadequate for pathology monitoring. In the last decades, omics-based instruments and methods have been developed, adjusted, and applied in parasitic research. In particular, the profiling of the most reliable determinants of phenotypes, metabolites by metabolomics, emerged as a powerful boost in the understanding of basic interactions within the human host during infection. As such, the fine detection of host metabolites produced upon exposure to parasites such as Schistosoma spp. and the ensuing progression of the disease are believed to enable the identification of Schistosoma spp. potential biomarkers of infection and associated pathology. However, attempts to provide such a comprehensive understanding of the alterations of the human metabolome during schistosomiasis are rare, limited in their design when performed, and mostly inconclusive. In this review, we aimed to briefly summarize the most robust advances in knowledge on the changes in host metabolic profile during Schistosoma infections and provide recommendations for approaches to optimize the identification of metabolomic signatures of human schistosomiasis.