👤 Zofia Wicik

Identifying reliable circulating biomarkers is crucial for improving the diagnosis and risk stratification of patients with ischemic stroke. In this study, we evaluated several whole-blood circulating miRNAs (miR-106b-5p, miR-16-5p, miR-15b-5p, let-7e-5p, and miR-125a-3p/-5p) to determine their diagnostic and disease severity in acute ischemic stroke (AIS). Sixty AIS patients and thirty age- and sex-matched controls were included. Whole-blood miRNAs were quantified at admission and on day 7. Statistical analyses included ROC curves, multivariate logistic regression, and SHAP-based machine learning. Bioinformatic analyses assessed predicted miRNA targets, pathway enrichment, and interaction networks. MiR-125a-3p was significantly reduced in AIS at both time points, while miR-125a-5p was elevated at admission and decreased by day 7. Both miRNAs showed moderate diagnostic value (AUC 0.675 and 0.712, respectively). Higher admission levels of miR-16-5p were strongly associated with greater neurological deficit (NIHSS) and unfavorable outcome (mRS ≥ 3). Multivariate analyses confirmed high miR-16-5p and elevated CRP as independent predictors of poor outcome. Bioinformatic analyses revealed that miR-16-5p targets were enriched in pathways relevant to ischemic injury, including hypoxia response, platelet activation, coagulation, TGF-β and BDNF signaling. A target-interaction network highlighted IL6, FN1, TGFB1, ICAM1, and TLR4 as central nodes linking miR-16-5p to ischemia-inflammatory mechanisms in AIS. Circulating miRNAs display distinct expression patterns in the acute phase of AIS. miR-16-5p emerges as a promising biomarker associated with stroke severity and unfavorable outcome, while miR-125a-3p and miR-125a-5p show potential diagnostic utility. These findings strengthen mechanistic links between platelet-derived miRNAs and ischemic stroke biology. Larger, longitudinal studies integrating functional validation are warranted to confirm their clinical value. Show less

In this study, we applied microarray, bioinformatics, and qRT-PCR techniques to identify miRNAs and their target genes in plasma obtained from acute ischemic stroke patients and matching controls. Microarray analyses were performed with 24-h acute ischemic stroke vs. healthy individuals and CV-risk factors matched control group plasma samples. Statistical analysis of gene expression was performed using TAC and R, with a focus on robust methods suitable for the small sample size, and miRNA target prediction was conducted using a previously established in-house wizbionet R package. Top non-coding regulators of ischemia (miR-18a-5p, miR-4467, miR-199a-5p and miR-3135b) and their predicted target genes (ANKRD12, HIF1A, GNAI2, GRIN1) were detected via qRT-PCR. 146 upregulated and 258 downregulated differentially expressed RNAs were detected by microarray analysis. Using the multiMiR R package for target prediction, 67 upregulated and 125 downregulated mRNAs were mapped. Functional enrichment analysis revealed that upregulated miRNAs were associated with pathways like BDNF and IL-2 signaling, while downregulated miRNAs were linked to neurodevelopmental and NGF pathways. MiR-18a-5p and miR-199a-5p were significantly elevated in stroke patients at both day 1 and day 7 compared to healthy individuals and CV-matched controls ( Our integrated miRNA/mRNA analysis identified distinct molecular signatures in acute ischemic stroke, with 146 upregulated and 258 downregulated RNAs, implicating key neuroinflammatory and neuroprotective pathways, including BDNF, IL-2, and NGF signaling. Among the validated candidates, miR-199a-5p, miR-3135b, miR-4467, and miR-18a-5p demonstrated diagnostic potential, while miR-4467, together with GNAI2 and HIF1A, showed post-stroke dynamic relevance, reflecting early transcriptomic adaptations following ischemic injury. [Image: see text] The online version contains supplementary material available at 10.1186/s12920-025-02302-5. Show less

Glucagon-like peptide-1 (GLP-1) is a hormone known for its critical functions in managing blood sugar and offering cardiovascular benefits. Our study focuses on Glucagon Like Peptide 1 Receptor (GLP1R) agonists that act beyond glycemic control in cardiovascular and metabolic health. A comprehensive bioinformatic analysis was conducted, incorporating GLP1R, Gastric Inhibitory Polypeptide Receptor (GIPR), Gastric Inhibitory Polypeptide (GIP) and glucagon receptor (GCGR) to assess the effects of GLP1R agonists on gene and metabolite interactions. Interaction network analysis revealed 130 common genes among GLP1R, GLP1R/GIPR, GLP1R/GIP, and GLP1R/GIPR/GCGR associated with diabetes-related processes, including obesity and hyperglycemia. Enriched terms related to cardiovascular diseases, such as hypertension, calcium regulation in cardiac cells, and amino acid accumulation-induced mTOR activation. We also observed enrichment in gene sets linked to longevity and less recognized terms like fatty liver disease. In GLP1R/GIP, behavior-related terms and gastric acid secretion were identified; GLP1R/GIPR/GCGR linked to fibrosarcoma, thought/speech disturbances, and adipogenesis. The metabolite-gene layer revealed enrichment in galactose metabolism, platelet homeostasis, and nitric-oxide pathways. We found that GLP1R agonists network-level associations are stronger with heart diseases than sodium-glucose co-transporter 2 inhibitors, suggesting greater therapeutic benefits. Integrating networks with metabolites highlighted key interactors and clarified GLP1R agonists' mechanisms and therapeutic potential. Show less