Severe influenza infection has no effective treatment available. One of the key barriers to developing host-directed therapy is a lack of reliable prognostic factors needed to guide such therapy. Here, we use a network analysis approach to identify host factors associated with severe influenza and fatal outcome. In influenza patients with moderate-to-severe diseases, we uncover a complex landscape of immunological pathways, with the main changes occurring in pathways related to circulating neutrophils. Patients with severe disease display excessive neutrophil extracellular traps formation, neutrophil-inflammation and delayed apoptosis, all of which have been associated with fatal outcome in animal models. Excessive neutrophil activation correlates with worsening oxygenation impairment and predicted fatal outcome (AUROC 0.817–0.898). These findings provide new evidence that neutrophil-dominated host response is associated with poor outcomes. Measuring neutrophil-related changes may improve risk stratification and patient selection, a critical first step in developing host-directed immune therapy.

Cirrhosis likely shares common pathophysiological pathways despite arising from a variety of liver diseases. A recent GWAS identified rs641738, a polymorphism in the MBOAT7 locus, as being associated with the development of alcoholic cirrhosis. Here we explore the role of this variant on liver inflammation and fibrosis in two cohorts of patients with chronic hepatitis C. In 2,051 patients, rs641738 associated with severe hepatic inflammation and increased risk of fibrosis, as well as fast fibrosis progression. At functional level, rs641738 associated with MBOAT7 transcript and protein levels in liver and blood, and with serum inflammatory, oxidative stress and macrophage activation markers. MBOAT7 was expressed in immune cell subsets, implying a role in hepatic inflammation. We conclude that the MBOAT7 rs641738 polymorphism is a novel risk variant for liver inflammation in hepatitis C, and thereby for liver fibrosis.

Host response biomarkers can accurately distinguish between influenza and bacterial infection. However, published biomarkers require the measurement of many genes, thereby making it difficult to implement them in clinical practice. This study aims to identify a single-gene biomarker with a high diagnostic accuracy equivalent to multi-gene biomarkers.In this study, we combined an integrated genomic analysis of 1071 individuals with experiments using well-established infection models.We identified a single-gene biomarker,, which had a high prediction accuracy (91%) equivalent to that obtained by multi-gene biomarkers. studies showed that was upregulated by TLR7 in plasmacytoid dendritic cells, antigen-presenting cells that responded to influenza virus rather than bacteria. studies confirmed that was expressed in influenza patients but not in bacterial infection, as demonstrated in multiple patient cohorts (n=521). In a large prospective study (n=439) of patients presented with undifferentiated respiratory illness (aetiologies included viral, bacterial and non-infectious conditions), displayed 88% diagnostic accuracy (AUC) and 90% specificity in discriminating between influenza and bacterial infections. represents a significant step forward in overcoming a translational barrier in applying genomic assay in clinical setting; its implementation may improve the diagnosis and management of respiratory infection.