IPAFLU: A prospective study assessing the incidence of invasive pulmonary aspergillosis (IPA) and identifying host and microbial risk factors predisposing to IPA among critically ill patients with severe influenza

Each year, influenza causes ~30,000 U.S. deaths, the majority of which stem from influenza pneumonia or secondary bacterial or fungal pneumonia. Aspergillus fumigatus is the leading cause of post-influenza fungal pneumonia. A retrospective study of ICU patients with influenza in Europe showed that 14% of patients without typical risks for invasive fungal infection developed invasive pulmonary aspergillosis (IPA). The mortality rate of IPA associated with severe influenza was very high (45% vs. 20% for those without IPA). IPA among patients with influenza has also been recognized increasingly in the US, but the incidence is not known. Since IPA is often diagnosed by specific diagnostic testing, it is possible that post-influenza cases are under-diagnosed in the US. Therefore, it is important to compare the incidence of IPA complicating influenza in both continents using a systematic prospective approach. Progression to IPA is likely a multifactorial process involving viral, bacterial and host factors. In this project, we will use a systems biology approach to develop models that predict the severity and outcomes of IPA complicating influenza. The specific aims are: (1) To determine the incidence of IPA in patients with influenza via a multicenter, prospective, observational study involving ICU wards in Europe and the US. (2) To identify host factors predisposing to IPA in patients with influenza. We will determine: associations between immune signatures in serum/BAL and IPA; identify genetic host variants associated with IPA; determine metabolic phenotypes underlying host−fungus interactions and perform a functional immunological assay to identify defects in fungal specific host immune responses. (3) To identify microbial factors predisposing to IPA in patients with influenza. We will investigate the effects of influenza on the microbiome composition of the BAL, and associations between BAL microbiome and IPA; determine the associations between gut-microbiome and IPA; determine the associations between influenza genomes and IPA. Finally, we will use predictive models to identify signatures for susceptibility to IPA, taking together data from Aims 1, 2 and 3.