News Release

Unconventional T cell subset enriched in airways of some patients with severe COVID-19

Peer-Reviewed Publication

American Association for the Advancement of Science (AAAS)

Unconventional T cells called mucosa-associated invariant T (MAIT) cells are recruited to the airways and strongly activated in some patients with severe COVID-19, a new study has found, suggesting the cells' possible involvement in the development of disease. These findings corroborate other recent studies that highlight potential associations between strong MAIT cell activation and severe COVID-19 outcomes. MAIT cells, representing 1% to 10% of T cells in the blood, can readily home into specific tissues and are particularly abundant in the liver and lungs. Emerging evidence has shown these primarily antibacterial cells can also act as quick-acting sensors of viral infection as well, leading Tiphaine Parrot and colleagues to investigate the MAIT cell population in the context of SARS-CoV-2. They analyzed blood samples taken from 24 hospitalized COVID-19 patients with moderate and severe disease, as well as 23 patients recovering from mild disease and 22 in recovery after severe disease. They discovered MAIT cells declined significantly in the blood and swarmed the airways of patients with COVID-19, compared with controls. By contrast, MAIT cell levels normalized in the blood of patients in recovery. Together, these patterns are consistent with the concept that MAIT cells home into tissues during disease and later return into the blood when disease is resolved. Furthermore, gene expression analyses revealed that MAIT cell expression of certain inflammatory proteins in the airways - including IL-17A, CD69, and CXCR3 - was associated with poor clinical outcome. Four out of 24 patients studied here who died at hospital had significantly higher CD69 expression by MAIT cells than patients who survived. The authors note several limitations of their study that must be resolved with further work, including that the cohorts studied here do not reflect the full complexity of COVID-19.

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