Variability in mRNA SARS-CoV-2 BNT162b2 vaccine immunogenicity is associated with differences in the gut microbiome and habitual dietary fibre intake
Bibliographic record
Abstract
ABSTRACT Objective Little is known about the interplay between gut microbiome and SARS-CoV-2 vaccine immunogenicity. In this prospective observational study, we investigated associations between the gut microbiome, habitual dietary fibre intake, and mRNA vaccine-elicited immune responses, including anti-Spike IgG, avidity, and ACE-2 competition (surrogate neutralization). Design 16S rRNA sequencing and short-chain fatty acid analyses were undertaken using stool samples collected from 48 healthy individuals at baseline and twelve-weeks after 1 st BNT162b2 SARS-CoV-2 vaccine dose. Associations between gut microbiome data and SARS-CoV-2 spike and RBD IgG levels, competitive binding antibodies, and anti-SARS-CoV-2 spike total relative fractional avidity assays were evaluated. A validated dietary fibre intake food frequency questionnaire was also used to correlate habitual dietary fibre intakes with vaccine responses. Results Our data revealed several baseline bacterial taxa, including Prevotella, Haemophilus and Veillonella (p<0.01), associated with BNT162b2 vaccine responses. Several Bacteroides spp. (p<0.01) as well as Bifidobacterium animalis , (p=0.003), amongst others, were positively associated with antibody avidity. Conversely, concentrations of isovaleric and isobutyric acid were higher in individuals with the lowest SARS-CoV-2 vaccine responses (p<0.01). Classifying participants based on habitual dietary fibre intake identified distinct avidity responses. Conclusion We showed associations between baseline gut microbiota composition and immunogenicity of BNT162b2 vaccine responses, particularly avidity maturation. We also demonstrate that branched-chain fatty acids and habitual dietary fibre intakes are associated with BNT162b2 vaccine immunogenicity. Together these findings indicate a link between gut microbiome, diet and antibody immunity to SARS-CoV-2 spike protein, suggesting interventions which modulate the gut microbiome could enhance COVID-19 vaccine responses. SIGNIFICANCE OF THIS STUDY What is already known on this subject? Strength and persistence of the SARS-CoV-2 BNT162b2 vaccine is variable between individuals. To date, only one study has demonstrated that baseline gut microbiota can predict SARS-CoV-2 vaccine response. What are the new findings? For the first time we showed that the higher concentrations of branched-chain fatty acids, isovaleric and isobutyric acids, are negatively associated with SARS-CoV-2 BNT162b2 vaccine responses. We revealed that habitual dietary fibre intake led to variability in the strength of antibody binding after the BNT162b2 vaccine. Specifically, high dietary fibre consumers displayed a significant increase in antibody avidity between in their 1 st and 2 nd dose. How this study might affect research, practice, or policy Our data suggests that therapeutic interventions which target the gut microbiome, including dietary modification, as well as pre-, pro-, and post-biotics, could enhance BNT162b2 vaccine immunogenicity, thus helping in the fight against COVID-19.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".