T-cell responses as a correlate of COVID-19 vaccination. A pilot study in Health Care Workers.

Martinez-Gallo, M.; Esperalba-Ezquerra, J.; Pujol-Borrell, R.; Sanda, V.; Arrese-Munoz, I.; Fernandez-Naval, C.; Anton-Pagarolas, A.; Cardona, V.; Labrador-Horrillo, M.; Pumarola-Sune, T.; Hernandez-Gonzalez, M.

Background: Clinical trials on the different vaccines to SARS-CoV-2 have demonstrated protection efficacy, but it is urgent to assess the levels of protection generated with real-world data, especially in individuals professionally exposed. Measuring T-cell responses may complement antibody tests currently in use as correlates of protection but there are not validated T-cell responses applicable to large number of samples. Objective: To assess the feasibility of using T-cell responses to SARS-CoV-2 S peptides by commercially available whole blood interferon-gamma release assays (IGRA) as a correlate of protection. Patients: Twenty health care workers before and after vaccination. Methods: Antibody test to SARS-CoV-2 N and S proteins in parallel with one IGRA assay and two detection techniques than can be automated. Results: IGRA test detected T-cell responses in naturally exposed and vaccinated HCW already after first vaccination dose. the correlation by the two detection methods, CLIA and ELISA, very high (R>0.9) and sensitivity and specificity ranged between 100 and 86% and 100-73% respectively. Even though there was a very high concordance between antibody and the IGRA assay in the ability to detect immune response to SARS-CoV-2 there was a relatively low quantitative correlation. In the small group primed by natural infection, one vaccine dose was sufficient to reach immune response plateau. IGRA was positive in one Ig (S) antibody negative vaccinated immunosuppressed HCW illustrating another advantage of the IGRA test. Conclusion: Whole blood IGRA tests amenable to automation, as the one here reported, constitute a promising additional tool for measuring the state of the immune response to SARS-CoV-2; they are applicable to large number of samples and may become valuable correlates of protection to COVID-19, particularly for vulnerable groups at risk of being re-exposed to infection, as are health care workers.