Author Identifier

David Broadhurst

ORCID : 0000-0003-0775-9581

Document Type

Journal Article

Publication Title

Science Signaling

Volume

14

Issue

690

Publisher

American Association for the Advancement of Science

School

School of Science / Centre for Integrative Metabolomics and Computational Biology

RAS ID

36885

Funders

Funding information : https://doi.org/10.1126/scisignal.abf8483

Comments

Cai, Y., Kim, D. J., Takahashi, T., Broadhurst, D. I., Yan, H., Ma, S., ... Iwasaki, A. (2021). Kynurenic acid may underlie sex-specific immune responses to COVID-19. Science Signaling, 14(690), article eabf8483. https://doi.org/10.1126/scisignal.abf8483

Abstract

Coronavirus disease 2019 (COVID-19) has poorer clinical outcomes in males than in females, and immune responses underlie these sex-related differences. Because immune responses are, in part, regulated by metabolites, we examined the serum metabolomes of COVID-19 patients. In male patients, kynurenic acid (KA) and a high KA–to–kynurenine (K) ratio (KA:K) positively correlated with age and with inflammatory cytokines and chemokines and negatively correlated with T cell responses. Males that clinically deteriorated had a higher KA:K than those that stabilized. KA inhibits glutamate release, and glutamate abundance was lower in patients that clinically deteriorated and correlated with immune responses. Analysis of data from the Genotype-Tissue Expression (GTEx) project revealed that the expression of the gene encoding the enzyme that produces KA, kynurenine aminotransferase, correlated with cytokine abundance and activation of immune responses in older males. This study reveals that KA has a sex-specific link to immune responses and clinical outcomes in COVID-19, suggesting a positive feedback between metabolites and immune responses in males.

DOI

10.1126/scisignal.abf8483

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Research Themes

Health

Priority Areas

Multidisciplinary biological approaches to personalised disease diagnosis, prognosis and management

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