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[Preprint]. 2020 Jun 26:2020.06.06.20123414.
doi: 10.1101/2020.06.06.20123414.

Sex differences in immune responses to SARS-CoV-2 that underlie disease outcomes

Affiliations

Sex differences in immune responses to SARS-CoV-2 that underlie disease outcomes

Takehiro Takahashi et al. medRxiv. .

Update in

  • Sex differences in immune responses that underlie COVID-19 disease outcomes.
    Takahashi T, Ellingson MK, Wong P, Israelow B, Lucas C, Klein J, Silva J, Mao T, Oh JE, Tokuyama M, Lu P, Venkataraman A, Park A, Liu F, Meir A, Sun J, Wang EY, Casanovas-Massana A, Wyllie AL, Vogels CBF, Earnest R, Lapidus S, Ott IM, Moore AJ; Yale IMPACT Research Team; Shaw A, Fournier JB, Odio CD, Farhadian S, Dela Cruz C, Grubaugh ND, Schulz WL, Ring AM, Ko AI, Omer SB, Iwasaki A. Takahashi T, et al. Nature. 2020 Dec;588(7837):315-320. doi: 10.1038/s41586-020-2700-3. Epub 2020 Aug 26. Nature. 2020. PMID: 32846427 Free PMC article.

Abstract

A growing body of evidence indicates sex differences in the clinical outcomes of coronavirus disease 2019 (COVID-19)1-4. However, whether immune responses against SARS-CoV-2 differ between sexes, and whether such differences explain male susceptibility to COVID-19, is currently unknown. In this study, we examined sex differences in viral loads, SARS-CoV-2-specific antibody titers, plasma cytokines, as well as blood cell phenotyping in COVID-19 patients. By focusing our analysis on patients with mild to moderate disease who had not received immunomodulatory medications, our results revealed that male patients had higher plasma levels of innate immune cytokines and chemokines including IL-8, IL-18, and CCL5, along with more robust induction of non-classical monocytes. In contrast, female patients mounted significantly more robust T cell activation than male patients during SARS-CoV-2 infection, which was sustained in old age. Importantly, we found that a poor T cell response negatively correlated with patients' age and was predictive of worse disease outcome in male patients, but not in female patients. Conversely, higher innate immune cytokines in female patients associated with worse disease progression, but not in male patients. These findings reveal a possible explanation underlying observed sex biases in COVID-19, and provide important basis for the development of sex-based approach to the treatment and care of men and women with COVID-19.

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Conflict of interest statement

Conflict of interest statement All authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Comparison of viral load, anti-SARS-CoV-2 antibody titers, and plasma cytokines.
a, Comparison of viral load measured with nasopharyngeal (Np) swab and saliva. Male patients (M_Pt); Female patients (F_Pt) =14:14 for Np samples and 9:10 for saliva samples. Dotted lines indicate the detection limit of the assay (5610 copies/mL), and negatively tested data are shown on the x-axis (not detected; ND). Bar = median. b, Titers of specific IgG and IgM antibody against SARS-CoV-2 S1 protein were measured. M_H-CW:F_HCW:M_Pt:F_Pt = 12:74:13:19 for IgG and 3:18:14:19 for IgM. c, A heatmap of the plasma levels of 71 cytokines and chemokines in 44 HCW controls (M : F = 15 : 29) and 38 patients in Cohort A (M : F = 17 : 21). Representative innate immune cytokines and chemokines are shown in (d). Data = mean ± SEM for b and d. Bonferroni’s multiple comparison test was used for the comparison between M_Pt vs F_Pt, M_HCW vs F_HCW, M_HCW vs M_Pt, and F_HCW vs F_Pt. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. All p-values < 0.10 are shown. The results of the all the cytokines/chemokines including those shown here can be found in Extended Data Fig. 1 (cytokines/IFNs) and Extended Data Fig. 2 (chemokines/growth factors).
Fig. 2
Fig. 2. PBMC composition differences between male and female COVID-19 patients.
a, A heatmap for the composition of PBMC (% of live cells) in control HCWs and Cohort A patients. M_HCW : F_HCW : M_Pt : F_Pt = 6 : 44 : 17 : 22. b, Comparison on the proportion of B cells and T cells in live PBMCs are summarized. c, Representative 2D plots for CD14 and CD16 in monocytes gate (live/CD19−CD3−/CD56−CD66b−). Numbers in red indicate the percentages in the monocyte gate. d, Percentages of total Monocytes, cMono, intMono, ncMono in the total live cells are shown. e, Correlation between plasma CCL5 levels and and ncMono (% of live cells). Linear regression line and 95% confidence interval are shown for each sex. Pearson correlation coefficient (R) and p-values for each sex are shown on top of the plot. (b, d) Data are mean ± SEM. Bonferroni’s multiple comparison test was used for the comparison between M_Pt vs F_Pt, M_HCW vs F_HCW, M_HCW vs M_Pt, and F_HCW vs F_Pt. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. All p-values < 0.10 are shown in the panels.
Fig. 3
Fig. 3. Sex difference in T cell phenotype in COVID-19 patients.
a, A heatmap for T cell subsets (% of CD3-positive cells) in control HCWs and Cohort A patients. M_HCW : F_HCW : M_PT : F_PT = 6 : 44 : 17 : 22. b, Percentages of CD4 and CD8 in the CD3-positive cells are shown. c, Representative 2D plots for CD38 and HLA-DR in the CD4 and CD8 T cells are shown. d, Percentages of CD38+HLA−DR+ CD4/CD8 cells in CD3-positive cells are summarized. e, Representative 2D plots for TIM-3 and PD-1 in the CD4 and CD8 T cells are shown. Data from the same samples in c. f, Percentages of PD-1+TIM-3+ CD4/8 cells in CD3-positive cells are summarized. g, A heatmap of intracellular cytokine staining of T cells (% of CD3-positive cells). Mean ± SEM in b, d and f. Bonferroni’s multiple comparison test was used for the comparison between M_Pt vs F_Pt, M_HCW vs F_HCW, M_HCW vs M_Pt, and F_HCW vs F_Pt. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. All p-values < 0.10 are shown in the panels.
Fig. 4
Fig. 4. Differential immune phenotypes related to COVID-19 disease progression between sexes.
Patients in Cohort A are divided into stabilized group and deteriorated group, depending on the comparison between maximum clinical score after sampling and the score at the sampling (M_stablized ; M_deteriorated : F_stablized : F_aggravated= 11:6:16:6). a, The differences in the patients’ age, BMI, nasopharyngeal/saliva virus RNA copies, and anti-S1-IgG antibody are compared. For virus concentration panels, dotted lines indicate the detection limit, and median values are indicated for each group. b, Cytokine/chemokine comparison between stabilized and deteriorated group. c, Proportions of activated (CD38+HLA−DR+) and terminally differentiated (PD-1+TIM-3+) CD4/CD8 T cells, and IFNγ+CD8 T cells in CD3-positive T cells are shown. d, Pearson correlation heatmaps of the indicated parameters are shown for each sex. For viral load levels and cytokine/chemokine levels, log-transformed values were used for the calculation of the correlations. The size and color of the circles indicate the correlation coefficient (R), and only statistically significant correlations (p < 0.05) are shown. Clinical deterioration from the first time point is scored by Cmax- C1. e, Correlation between age and CD38+HLA−DR+ CD8 T cells (left) and IFNγ+CD8 T cells (right, both in % of CD3 T cells). Linear regression lines and 95% confidence intervals are shown. Pearson correlation coefficient (R) and p-values for each correlation and for each sex are shown on top of each plot. Data are mean ± SEM and unpaired t-test was used to compare the differences between stabilized group and deteriorated group about each sex in a, b, c. For the age panel in a and correlation plots for age and T cells (e), data points for individuals ≥ 90-year-old are plotted as 90-year-old. *P < 0.05, **P < 0.01. All p-values < 0.10 are shown in the panels.

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