Florey Advanced Fellow Secures Investment to Investigate New Approaches to Diagnose Infections in the Tropics
The award of $1.4m is for a multisite study to investigate novel approaches to diagnosis of acute undifferentiated febrile illness (AUFI). AUFI is a principal presenting complaint in patients in low-resource and tropical settings for which the differential diagnosis includes important life-threatening infections including malaria, dengue and typhoid fever. Accurate rapid diagnosis is important to ensure appropriate management, but also to guide vaccine implementation and treatment algorithms in such areas.
In their approach, the team will focus on determining the potential causative agents of AUFI, by identifying distinctive patterns of the human immune and inflammatory responses to infection in gene expression profiles. Traditional detection of the disease-causing pathogen is often extremely difficult, especially for bacterial infections such as enteric (or typhoid) fever, due to the low numbers of bacteria present in clinical samples and the inaccuracy of interpreting antibody responses in settings where exposure to infection is common.
The team will search for patterns or ‘signatures’ of specific types of infection by interrogating large datasets of gene expression (transcription) data, generated from blood samples collected from patients presenting to healthcare facilities with fever without any obvious local cause. They will perform computational modelling of this data to categorize gene expression profiles and then perform a series of parallel clinical and research diagnostic assays to identify the probable causes associated with these response profiles. Additional data will be integrated into these datasets, including previously collected and publicly available gene expression datasets, data generated in Controlled Human Infection Models (CHIM) and they will leverage additional resources including samples and data collected from ongoing fever and Phase III vaccine efficacy studies and planned enteric treatment trials.
The overall aim of the Bill & Melinda Gates Foundation investment is to demonstrate that gene expression signatures can be used to accurately identify and usefully discriminate bacterial, viral and parasitic causes of AUFI in South Asia. These data will be assessed in the context of additional bedside tests (such as measurement of C-reactive protein) to develop solutions for point-of-care testing for AUFI. Such tests could significantly improve the care of sick patients in low-resource settings, reduce the inappropriate dispensing of antimicrobials (which could limit the spread of antimicrobial resistance), and guide the more precise deployment of vaccines through improved case ascertainment and definition of disease burdens.
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