Integrated metagenomic and metabolomic analysis identifies severity-specific inflammatory and metabolic signatures in post-stroke depression.

Overview

1. Wenzhou Joint Training Base, Zhejiang Chinese Medical University, Wenzhou, China
2. Department of Rehabilitation Medicine, The Second People's Hospital of Lishui, Lishui, China
3. Department of Rehabilitation Medicine, Wenzhou TCM Hospital of Zhejiang Chinese Medical University, Wenzhou, China

Abstract

Post-stroke depression (PSD) is a common complication that significantly impacts patient prognosis. This study aimed to systematically characterize the associations among gut microbial ecology, metabolic profiles, and inflammatory responses across different severities of PSD. We conducted metagenomic sequencing, non-targeted metabolomics, and serum cytokine analysis (IL-1β, IL-6, IL-10, IL-18, TNF-α, IFN-γ, and CRP) in 91 patients with varying degrees of PSD and non-PSD controls. Bioinformatics analyzes were employed to construct multi-omics association networks and machine learning models. Results indicated that PSD patients exhibited significantly increased gut microbiota alpha-diversity, suggesting dysbiosis. Mild depression was characterized by compensatory neural signaling activation, whereas the moderate depression group exhibited abnormalities in tryptophan/indole metabolism, oxidative stress-related metabolic imbalances, and functional decompensation. Further analyzes suggested that Alistipes, Blautia_A, Evtepia gabavorous, and Lachnospira were associated with inflammatory features, GABA-related metabolic alterations, aromatic amino acid/indole metabolism, and lipid-amino acid metabolism, respectively. Under a more rigorous 10-fold cross-validation framework, the performance of different multi-omics combination models showed heterogeneity; however, some combinations still demonstrated superior discriminatory ability compared to single-omics approaches. This study provides multi-omics clues suggesting associations between different PSD severity levels and features such as increased Alistipes abundance, reduced antioxidant capacity, and altered tryptophan metabolism. It provides candidate biomarker combinations that may be useful for PSD stratification and suggests that the gut microbiome may represent a potential target for future PSD intervention. In summary, PSD may be associated with dynamic alterations along the “gut–brain-inflammation-metabolism” axis. These findings provide integrated evidence for microbial, metabolic, and inflammatory abnormalities across different PSD severity levels, but still require validation in larger samples, longitudinal cohorts, and mechanistic studies.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

Datasets cited

• zenodo:19388744, at Zenodo; found in “Data availability statement”
• zenodo:19394192, at Zenodo; found in “Data availability statement”

Data availability statement

The fecal and serum untargeted metabolomics datasets generated in this study have been deposited in Zenodo under embargo and are available via the following DOI(s): https://doi.org/10.5281/zenodo.19394192(fecal); https://doi.org/10.5281/zenodo.19388744(serum).

The metagenomic raw sequence data generated in this study have been deposited in the Genome Sequence Archive (GSA) at the National Genomics Data Center, China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences, under accession number CRA040936 that are publicly accessible at https://ngdc.cncb.ac.cn/gsa The files will be made publicly accessible upon publication of this article.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 3, 28 September 2026

• Funding: added Zhejiang University; Wenzhou Municipal Science and Technology Bureau

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 8 authors, 6 keywords, 16 MeSH terms, 46 references.

Cite

This paper

Chen, W., Pan, Y., Chen, M., Zhou, S., Liu, X., Sun, M., Yang, Z., & Zhi, Y. (2026). Integrated metagenomic and metabolomic analysis identifies severity-specific inflammatory and metabolic signatures in post-stroke depression. Gut microbes, 18(1), 2726620. https://doi.org/10.1080/19490976.2026.2726620

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