Abstract
Background:
Influenza viruses with pandemic potential and possible burden of post-viral sequelae are a global concern. To prepare for future pandemics and the development of improved vaccines, it is vital to identify the immunological changes underlying influenza disease severity.
Methods:
We combined unsupervised high-dimensional single-cell mass cytometry with gene expression analyses, plasma CXCL13 measurements, and antigen-specific immune cell assays to characterize the immune profiles of hospitalized patients with severe and moderate seasonal influenza disease during active infection and at 6-month follow-up. We used age-matched healthy donors as controls.
Results:
Severe disease was associated with a distinct immune profile, including lower frequencies of ICOS+ mucosal-associated invariant T (MAIT) cells, and CXCR5+ memory B and CD4+CXCR5+CD95+ICOS+ and CD8+CXCR3+CD95+PD-1+TIGIT+ memory T cells, as well as lower CD4 gene expression. Higher frequencies of CD16+CD161+ NK cells, CD169+ monocytes, CD123+/- dendritic cells, and CD38high plasma cells and high CXCL13 plasma levels were also associated with severe disease. Alterations in immune cell subpopulations persisted at convalescence for the severely ill patients only.
Conclusions:
Our results indicated a reduction in regulatory MAIT cells and memory T and B cells and an increase in the inhibitory subpopulations of monocytes and NK cells in severe influenza that persisted at convalescence. These immune cell alterations were associated with higher age and the presence of several underlying conditions that may contribute to frailty. This study illustrates the power and sensitivity of high-dimensional single-cell analyses in identifying potential cellular biomarkers for disease severity after influenza infection.