Gut microbiota composition is associated with SARS-CoV-2 vaccine immunogenicity and adverse events

Abstract

Objective: The gut microbiota plays a key role in modulating host immune response. We conducted a prospective, observational study to examine gut microbiota composition in association with immune responses and adverse events in adults who have received the inactivated vaccine (CoronaVac; Sinovac) or the mRNA vaccine (BNT162b2; BioNTech; Comirnaty).

Design: We performed shotgun metagenomic sequencing in stool samples of 138 COVID-19 vaccinees (37 CoronaVac and 101 BNT162b2 vaccinees) collected at baseline and 1 month after second dose of vaccination. Immune markers were measured by SARS-CoV-2 surrogate virus neutralisation test and spike receptor-binding domain IgG ELISA.

Results: We found a significantly lower immune response in recipients of CoronaVac than BNT162b2 vaccines (p<0.05). Bifidobacterium adolescentis was persistently higher in subjects with high neutralising antibodies to CoronaVac vaccine (p=0.023) and their baseline gut microbiome was enriched in pathways related to carbohydrate metabolism (linear discriminant analysis (LDA) scores >2 and p<0.05). Neutralising antibodies in BNT162b2 vaccinees showed a positive correlation with the total abundance of bacteria with flagella and fimbriae including Roseburia faecis (p=0.028). The abundance of Prevotella copri and two Megamonas species were enriched in individuals with fewer adverse events following either of the vaccines indicating that these bacteria may play an anti-inflammatory role in host immune response (LDA scores>3 and p<0.05).

Conclusion: Our study has identified specific gut microbiota markers in association with improved immune response and reduced adverse events following COVID-19 vaccines. Microbiota-targeted interventions have the potential to complement effectiveness of COVID-19 vaccines.

Keywords: COVID-19; enteric bacterial microflora; immune response.

Figure 1

Study design and changes in beta diversity, alpha diversity and bacterial species from baseline to 1 month after second dose of vaccination. (A) Study design. (B) Beta diversity was significantly different between baseline and 1 month after completion of vaccination (CoronaVac baseline, n=37; BNT162b2 baseline, n=101; CoronaVac 1 month, n=36; BNT162b2 1 month, n=98). P values were given by PERMANOVA and Wilcoxon rank-sum test (two sided), and adjusted for FDR, respectively. (C) Alpha diversity decreased significantly from baseline to 1 month after completion of vaccination for CoronaVac (n=36) and BNT162b2 (n=98). P values were given by paired Wilcoxon rank-sum test (two sided). (D) Differentially abundant species between baseline and 1 month after completion of vaccination for CoronaVac (n=36) and BNT162b2 (n=98). Differentially abundant species were detected using paired Wilcoxon rank-sum test (FDR corrected p<0.05). Elements on boxplots: centre line, median; box limits, upper and lower quartiles; whiskers, 1.5×IQR; points, outliers. FDR, false discovery rate; NMDS, non-metric multi-dimensional scaling; PERMANOVA, permutational multivariate analysis of variance.

Figure 2

Baseline gut bacterial species and functions associated with high and low responders to vaccines at 1 month after second dose of vaccination. (A) Baseline bacterial species and pathways associated with high responders among CoronaVac vaccinees (n=37) (sVNT of 10-fold diluted plasma >60%). Differential baseline gut bacterial species and pathways were detected by LEfSe. Pairwise correlations between selected bacterial species and pathways markers with FDR corrected p<0.05 were shown. (B) Baseline bacterial species and pathways for highest-tier responders among BNT162b2 vaccinees (n=101) (the first quartile (Q1) of sVNT of 200-fold diluted plasma). sVNT-10: sVNT level of 10-fold diluted plasma; sVNT-200: sVNT level of 200-fold diluted plasma. Differential baseline gut bacterial species and pathways were detected by LEfSe. Pairwise correlations between selected bacterial species and pathways markers with FDR corrected p<0.05 were shown. Full names of differentially abundant pathways between high/low responders in (A, B) are described in online supplemental table S7C), AUROC (95% CI) values of models based on individual biomarkers and a combined model based on all biomarkers for high responders (n=16) vs low responders (n=21) among CoronaVac vaccinees. (D) AUROC (95% CI) values of models based on individual biomarkers and a combined model based on all biomarkers for the highest-tier responders (n=25) vs others (n=76) among BNT162b2 vaccines. each AUROC was presented as an orange dot with a bar showing the 95% CI. AUROC, area under the receiver operating characteristic curve; FDR, false discovery rate; LEfSe, linear discriminant analysis effect size; sVNT, surrogate virus neutralisation test.

Figure 3

Association of baseline gut bacterial motility and fimbrial gene abundance with neutralising antibody response to CoronaVac and BNT162b2 vaccines at 1 month after second dose of vaccination. (A) Association of baseline gut bacterial motility (based on bacterial relative abundance and bacterial motility phenotype, the Methods section) with neutralising antibody response at 1 month after second dose of vaccination. (B) Association of flagellum-dependent cell motility (GO:0071973) of baseline gut microbiome with neutralising antibody response at 1 month after second dose of vaccination. (C) Association of fimbrial gene abundance (GO:0009289) of baseline gut microbiome with neutralising antibody response at 1 month after second dose of vaccination. CoronaVac (n=37): high-responders, n=16; low responders, n=21. BNT162b2 (n=101) highest tier, n=25; others, n=76. sVNT-10: sVNT level of 10-fold diluted plasma; sVNT-200: sVNT level of 200-fold diluted plasma. Correlation between motility/fimbrial gene abundance and sVNT data was examined using Spearman’s correlation test. Regression lines with 95% CI (grey area) were shown on scatter plots. Comparison between high versus low responder groups/highest tier versus others was made using Wilcoxon’s rank-sum test (two-sided). Elements on boxplots: centre line, median; box limits, upper and lower quartiles; whiskers, 1.5×IQR; points, outliers. sVNT, surrogate virus neutralisation test.

Figure 4

Weight status modifies the assocaitions between baseline gut bacterial species and immune response in CoronaVac vaccinees at 1 month after second dose of vaccination. Immune response and ORs to be high responders separated by baseline bacterial abundance within weight strata (A) by Bifidobacterium adolescentis abundance. (B) By Butyricimonas virosa abundance (C) by Adlercreutzia equolifaciens abundance. (D) by Asaccharobacter celatus abundance. sVNT-10: sVNT of 10-fold diluted plasma. Sample size per group was indicated on the figure. Comparisons between subgroups were done using Dunn’s test (one sided) with FDR correction. Model 1: crude model. Model 2: adjusted for age. Reference group: NW with high bacterial abundance. Elements on boxplots: centre line, median; box limits, upper and lower quartiles; whiskers, 1.5×IQR; points, outliers. Each OR was presented as an orange dot with a bar showing the 95% CI. NW, normal weight; FDR, false discovery rate; OWOB, overweight or obese; sVNT, surrogate virus neutralisation test.