The Use of Host Biomarkers for the Management of Invasive Fungal Disease

Invasive fungal disease (IFD) causes severe morbidity and mortality, and the number of IFD cases is increasing. Exposure to opportunistic fungal pathogens is inevitable, but not all patients with underlying diseases increasing susceptibility to IFD, develop it. IFD diagnosis currently uses fungal biomarkers and clinical risk/presentation to stratify high-risk patients and classifies them into possible, probable, and proven IFD. However, the fungal species responsible for IFD are highly diverse and present numerous diagnostic challenges, which culminates in the empirical anti-fungal treatment of patients at risk of IFD. Recent studies have focussed on host-derived biomarkers that may mediate IFD risk and can be used to predict, and even identify IFD. The identification of novel host genetic variants, host gene expression changes, and host protein expression (cytokines and chemokines) associated with increased risk of IFD has enhanced our understanding of why only some patients at risk of IFD actually develop disease. Furthermore, these host biomarkers when incorporated into predictive models alongside conventional diagnostic techniques enhance predictive and diagnostic results. Once validated in larger studies, host biomarkers associated with IFD may optimize the clinical management of populations at risk of IFD. This review will summarise the latest developments in the identification of host biomarkers for IFD, their use in predictive modelling and their potential application/usefulness for informing clinical decisions.

Automated summary

Invasive fungal disease (IFD) causes severe morbidity and mortality, and the number of IFD cases is increasing. Current IFD diagnosis relies on fungal biomarkers and clinical risk/presentation, but the diverse fungal species and diagnostic challenges lead to empirical anti-fungal treatment for high-risk patients. Recent studies have focused on host-derived biomarkers that can predict and identify IFD, enhancing diagnostic results. Once validated in larger studies, these biomarkers may optimize the clinical management of populations at risk of IFD.