DECODING THE TRANSCRIPTOME: GENE EXPRESSION PROFILES IN ACUTE ISCHEMIC STROKE PATIENTS

Introduction: Acute ischemic stroke (AIS) is a complex vascular disorder characterized by sudden focal neurological symptoms lasting at least 24 hours, representing a significant source of long-term disability in Western populations. The urgent restoration of cerebral blood flow is typically achieved through a combination of intravenous rt-PA treatment and mechanical thrombectomy (MT), offering access to cerebral thrombi (CT) for investigation. Recent advancements in omics technologies have enabled comprehensive investigations into clot composition and stroke mechanisms, enhancing predictive capabilities. AIS is classified into five subtypes based on the TOAST classification system: cardioembolic (CE), large-vessel atherosclerotic (LAA), lacunar (SVO), cryptogenic, and other causes. Determining the etiologic classification is essential for establishing prognosis, outcome, and event management factors, thus enabling the development of personalized medicine in which prevention and treatment strategies are increasingly individualized. Aim: The primary thrust of this investigation is to delve into the intricate genetic landscape of ischemic stroke through the application of cutting-edge transcriptomic approaches. Our specific focus centers on the meticulous exploration of molecular signatures within thrombotic tissue and peripheral venous blood (PB) that are uniquely associated with distinct stroke subtypes. Through this systematic inquiry, we aim to unveil the intricate interplay between gene expression patterns and the nuanced phenotypic differences that characterize the spectrum of ischemic stroke subtypes. Methods: We conducted gene expression profiling on a cohort of 92 AIS patients. CT samples obtained during MT were preserved in RNA later, while PB in tubes containing a reagent that protects RNA from degradation and minimizes ex vivo changes in gene expression. RNA extraction was performed using the PAX gene blood miRNA kit, and global gene expression profiling was accomplished using Affymetrix technology with the GeneChip Human Transcriptome Array 2.0 platform, allowing the analysis of 44,699 genes, >285,000 full-length transcripts coverage, combined with Affymetrix Transcriptome Analysis Console (TAC) Software, followed by a Gene Ontology (GO) and Reactome enrichment analysis to identify biological processes and pathways affected by different stroke etiologies. Results: The initial observation from our analysis, reinforced by the Cibersort analysis, spotlights a robust activation of the immune response in the aftermath of the ischemic event. The results of the analysis reveal consistency and uniformity in the quantity of different types of immune cells present in the samples, suggesting a similar immune cell composition in both CT and PB. Specifically, a predominance of neutrophils, the type of white blood cell that plays a crucial role in the body's immune response, emerged in both types of analyzed material, constituting 33% and 66% of the total, respectively. Analysis of CT data unveiled significant differences (p-value<0.05 and FoldChange=2 as threshold) in gene expression profiles when comparing strokes of LAA origin with CE and cryptogenic strokes. Notably, LAA strokes exhibited overexpression of 301 genes compared to CE strokes, with differential expression of 209 genes compared to cryptogenic strokes. The next step was to conduct a GO and REACTOME enrichment analysis, so as to identify, respectively, the biological processes and pathways that are impacted by the condition being examined. Among them, biological processes such as neutrophil degranulation, regulation of cytokine production, and processes involved in damage response appear to be significantly enriched. Specifically, genes such as S100A12 (logFC=3.826 p-val.adj=0,002519), S100A9 (logFC=2.8555 p-val.adj= 0,000748), and S100A8 (logFC=3.175 p-val.adj= 0,001599), associated with inflammation and atherosclerotic plaque instability, were prominently overexpressed in LAA strokes. Additionally, genes involved in inflammation, including MMP9 (logFC=2.3845 p-val.adj= 0,002712), IL-1β (logFC=2.1035 p-val.adj= 0,004624), and VNN2 (logFC=5.1645 p-val.adj= 0,002925), showed significant upregulation. In the realm of microRNAs (miRNAs), we highlighted the substantial overexpression of miRNA-223 (logFC=3.093 p-val.adj= 0,001225) in atherosclerotic-origin strokes. This particular miRNA has a significant role in inflammatory processes and has been linked, based on existing literature, to cardiovascular diseases. Despite thorough exploration, no significant differences in gene expression were detected in comparisons beyond other subtypes in CT and PB samples. This underscores a unique molecular landscape within the identified subtypes, emphasizing the necessity for a nuanced understanding of the underlying biology. Conclusions: Transcriptome profiling has provided valuable insights into the molecular landscape of AIS. The overexpression of genes such as MMP-9, S100A12, S100A9 and S100A8 in atherosclerotic strokes underscores their association with plaque instability and adverse neurological outcomes. Dysregulation of genes such as IL-1β exacerbates ischemic injury, highlighting their crucial role in AIS pathophysiology. Transcriptome signatures hold promise in distinguishing between stroke etiologies, paving the way for personalized approaches to secondary stroke prevention.