Exploring post-stroke depression: Exosomal proteomics reveals underlying mechanisms and potential plasma biomarkers

As the most common psychiatric complication following stroke, post-stroke depression (PSD) lacks effective biomarkers for diagnosis. This study aims to identify potential biomarkers for PSD through proteomics analysis of plasma exosomes.

Patients with acute ischemic stroke were grouped according to the Hamilton Depression Rating Scale (HAMD). Exosomes were isolated and purified from plasma samples using size exclusion filtration combined with ultracentrifugation. Differentially expressed proteins (DEPs) were screened and subjected to functional analysis and identification using direct data-independent acquisition (direct-DIA) proteomics and bioinformatics approaches.

A total of 111 significantly differentially expressed proteins were identified between the two groups, including 44 upregulated and 67 downregulated. GO and KEGG enrichment analyses revealed that the upregulated proteins were significantly enriched in the complement and coagulation cascades. Protein-protein interaction network analysis further identified PLG, HRG, and CPB2 as core network nodes. ROC curve analysis demonstrated favorable predictive efficacy for the combined detection of these three proteins, and their expression levels were positively correlated with HAM-D scores. These findings were validated by ELISA in an independent cohort.

These results suggest that the complement and coagulation pathways may be involved in the pathophysiological process of post-stroke depression (PSD), in which key proteins such as PLG, HRG, and CPB2 are likely to play important roles.