REVIEW article
Front. Immunol.
Sec. Vaccines and Molecular Therapeutics
Identification of metabolic signatures of immune response following mRNA and inactivated vaccines against COVID-19: a systematic review
Provisionally accepted
- Wroclaw Medical University, Wrocław, Poland
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Background: Metabolomic profiling offers insights into immune responses, yet a synthesis of systemic metabolic changes after COVID-19 vaccination is lacking. This review aims to characterize vaccination-induced metabolomic alterations and identify correlative biomarkers of responsiveness. Methods: Following PRISMA 2020 guidelines (PROSPERO 1181037), four databases (PubMed, Embase, Scopus, Web of Science) were searched for studies using LC-MS, GC-MS, or NMR to analyze venous blood after COVID-19 vaccination. Inclusion criteria focused on original human studies. Risk of bias was assessed using ROBINS-I and RoB 2. Results: Ten studies (n > 1,200) evaluating mRNA and inactivated vaccines were included. Vaccination consistently altered amino acid pathways, specifically glutamine, phenylalanine, and tryptophan. Early activation of the kynurenine pathway (1–2 days post-dose) emerged as a predictor of stronger antibody responses. Inactivated vaccines triggered a "Warburg-like" metabolic switch, characterized by increased glycolysis and reduced TCA intermediates. Lipidomic changes were prominent; high baseline ceramides predicted low response, while sphingomyelins and short-chain fatty acids associated with positive immunity. Most studies showed a moderate risk of bias due to post-hoc grouping and confounding factors. Conclusions: COVID-19 vaccination induces reproducible changes in amino acid, energy, and lipid metabolism. Kynurenine activity, baseline amino acids, and sphingolipid signatures are potential predictors of vaccine efficacy, supporting personalized immunization strategies.
Keywords: biomarkers, COVID-19 vaccine, immune response, Kynurenine, Metabolomics
Received: 08 Jan 2026; Accepted: 09 Feb 2026.
Copyright: © 2026 Wasilewski and Serrafi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Andrzej Wasilewski
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