Treffer: Inflammation-related biomarkers and berberine therapy in post-stroke depression: evidence from bioinformatics, machine learning, and experimental validation.

Title:
Inflammation-related biomarkers and berberine therapy in post-stroke depression: evidence from bioinformatics, machine learning, and experimental validation.
Authors:
Liu W; Graduate School of Hebei North University, Zhangjiakou, Hebei, China.; Department of Curative Diseases, Langfang Hospital of Traditional Chinese Medicine, Langfang, Hebei, China., Wei R; Graduate School of Hebei North University, Zhangjiakou, Hebei, China.; Department of Curative Diseases, Langfang Hospital of Traditional Chinese Medicine, Langfang, Hebei, China., Xu J; Graduate School of Hebei North University, Zhangjiakou, Hebei, China.; Jingxing County Hospital, Shijiazhuang, Hebei, China., Liu Z; Department of Curative Diseases, Langfang Hospital of Traditional Chinese Medicine, Langfang, Hebei, China.; Cangzhou Hospital of Integrated Traditional Chinese and Western Medicine, Cangzhou, Hebei, China., Li Y; Graduate School of Hebei North University, Zhangjiakou, Hebei, China.; Department of Curative Diseases, Langfang Hospital of Traditional Chinese Medicine, Langfang, Hebei, China.
Source:
Frontiers in neuroscience [Front Neurosci] 2025 Oct 14; Vol. 19, pp. 1684297. Date of Electronic Publication: 2025 Oct 14 (Print Publication: 2025).
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101478481 Publication Model: eCollection Cited Medium: Print ISSN: 1662-4548 (Print) Linking ISSN: 1662453X NLM ISO Abbreviation: Front Neurosci Subsets: PubMed not MEDLINE
Imprint Name(s):
Original Publication: Lausanne : Frontiers Research Foundation
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Contributed Indexing:
Keywords: bioinformatics; inflammation; machine learning; post-stroke depression; traditional Chinese medicine
Entry Date(s):
Date Created: 20251030 Date Completed: 20251030 Latest Revision: 20251101
Update Code:
20251101
PubMed Central ID:
PMC12558837
DOI:
10.3389/fnins.2025.1684297
PMID:
41164411
Database:
MEDLINE

Weitere Informationen

Objective: Post-stroke depression (PSD), a common neuropsychiatric complication, significantly hinders stroke recovery and quality of life. Given the established role of inflammation in the pathogenesis of PSD, this study aimed to identify key inflammation-related genes and pathways using bioinformatics and machine learning and further evaluate the protective effects of traditional Chinese medicine (TCM) monomer compounds.
Methods: PSD-related datasets (GSE16561, GSE98793) were obtained from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified using the limma package, followed by functional enrichment analysis with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Three machine learning algorithms-random forest, support vector machine-recursive feature elimination (SVM-RFE), and least absolute shrinkage and selection operator (LASSO)-were applied to screen inflammation-related hub genes. Immune cell infiltration was analyzed using single-sample gene set enrichment analysis (ssGSEA). Candidate TCM compounds were explored via the Coremine Medical database. A PSD rat model was established to validate hub gene expression and to assess the efficacy of berberine (BBR).
Results: Analysis identified 35 inflammation-related DEGs (IDEGs) significantly enriched in immunological processes, including malaria pathogenesis, NETosis, innate immune deficiencies, Rap1 signaling, and IL-17 cascades. The integration of machine learning pinpointed TLR2 and CYP1B1 as core hub genes, demonstrating robust diagnostic performance in external validation. Molecular docking suggested a strong binding affinity between the TCM compound BBR and TLR2/CYP1B1 proteins. PSD rats exhibited prolonged immobility in forced swim/tail suspension tests and decreased sucrose preference versus controls, alongside neuronal damage, edema, and inflammatory infiltration (HE staining). BBR treatment reversed these behavioral deficits and pathological changes. Western blot analysis confirmed elevated TLR2 and CYP1B1 expression in PSD rats, significantly downregulated by BBR. Enzyme-linked immunosorbent assay (ELISA) showed increased serum IL-1β, IL-6, and TNF- α levels in PSD, which BBR effectively reduced.
Conclusion: This study identifies TLR2 and CYP1B1 as core inflammation-related genes in PSD. BBR demonstrates therapeutic efficacy as an active monomer compound against PSD, likely mediated through downregulating TLR2 and CYP1B1 expression, consequently diminishing the concentrations of pro-inflammatory mediators (IL-1β, IL-6, TNF- α ) that mediate cerebroprotective actions.
(Copyright © 2025 Liu, Wei, Xu, Liu and Li.)

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.