High glycemic variability is associated with a reduced T cell cytokine response to influenza A virus

Abstract

Diabetes mellitus significantly increases the risk of severe respiratory virus disease like influenza and COVID-19. Early evidence suggests that this susceptibility to respiratory viral disease is driven by glycemic variability, rather than average blood glucose levels. Here, we use blood samples and constant glucose monitoring (CGM) data obtained from people living with type 1 diabetes (T1D) to determine the effects of glycemic variability on the ex vivo T cell response to influenza virus. We show that high glycemic variability in participants living with T1D is associated with a reduced proportion of CD8⁺CD107a^-IFNγ^-MIP1β^-TNF⁺ T cells in response to stimulation with influenza virus and an influenza virus peptide pool. Thus, this study provides evidence that glycemic variability affects the ex vivo T cell response to respiratory viruses. These data suggest that monitoring glycemic variability may have important implications in understanding the antiviral immune response in people with diabetes.

Keywords: Endocrinology; Human metabolism.

Graphical abstract

Figure 1

Higher time recorded with hypoglycaemic levels were observed in participants with high glycemic variability (GV) (A) Representative CGM data for individuals with low glycemic variability and high glycemic variability. (B) The difference in time glucose levels spent above and below the glycemic healthy range (3.9 mmol/L to 10.0 mmol/L) were analyzed between both groups. Statistical significance was assessed using a Mann-Whitney test or Student’s t test. p < 0.05 ∗; p < 0.001 ∗∗∗ Bars and error bars represent means (±SEM).

Figure 2

Participants with higher glycemic variability (GV) exhibit an altered T cell profile and proportion of TNFα+ cells in response to influenza virus stimulation PBMC from participants were stained for CD4 and CD8. CD4⁺, CD4⁻CD8⁻, and CD8⁺ positive T cells (A) were stained for CD27, CD45RA, and CD95 to further define T cell subsets (B). To study T cell function, Boolean gating analysis was used. PBMC were stimulated with HKx31 (MOI10) (C), influenza virus peptide pool (D), Dynabeads (E), and PMA/I (F) for 18 h. PBMC were then stained for CD107a, IFNγ, MIP-1β, and TNF. Statistical significance was assessed using a Mann-Whitney test or Student’s t test. Bars and error bars represent means (±SEM). Gating was performed as previously described. ∗: p < 0.05.