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Comparative transcriptomic analysis of circulating endothelial cells in sickle cell stroke

ABSTRACT: Ischemic Stroke (IS) is one of the most impairing complications of sickle cell anemia (SCA), responsible for 20% of mortality in patients. Rheological alterations, adhesive properties of sickle reticulocytes, leukocyte adhesion, inflammation and endothelial dysfunction are related to the vasculopathy observed prior to ischemic events. The role of the vascular endothelium in this complex cascade of mechanisms is emphasized, as well as in the process of ischemia-induced repair and neovascularization. The aim of the present study was to perform a comparative transcriptomic analysis of endothelial colony-forming cells (ECFCs) from SCA patients with and without IS. Next, to gain further insights of the biological relevance of differentially expressed genes (DEGs), functional enrichment analysis, protein-protein interaction network (PPI) construction and in silico prediction of regulatory factors were performed. Among the 2,469 DEGs, genes related to cell proliferation (AKT1, E2F1, CDCA5, EGFL7), migration (AKT1, HRAS), angiogenesis (AKT1, EGFL7) and defense response pathways (HRAS, IRF3, TGFB1), important endothelial cell molecular mechanisms in post ischemia repair were identified. Despite the severity of IS in SCA, widely accepted molecular targets are still lacking, especially related to stroke outcome. Thus, these exploratory results may contribute to a better understanding of the role of endothelial cells in SCA ischemic stroke recovery, and promote new insights to further studies on therapeutic strategies for this severe complication.

ORGANISM(S): Homo sapiens

PROVIDER: GSE248760 | GEO | 2024/04/08

REPOSITORIES: GEO

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Project description:Stroke remains a major leading cause of death and disability worldwide. Despite continuous advances, the identification of key molecular signatures of ischemic stroke within the hyper-acute phase of the disease is still of primary interest for a real translational research on stroke diagnosis, prognosis and treatment. High-throughput - omics technologies are enabling large-scale studies on stroke pathology at different molecular levels. Data integration resulting from these -omics approaches is becoming crucial to unravel the interactions among all different molecular elements and highly contribute to interpret all findings in a complex biological context. Here, we have used advanced data integration methods for multi-level joint analysis of transcriptomics and proteomics datasets depicted from the mouse brain 2h after cerebral ischemia. By modeling network-like correlation structures, we identified a set of differentially expressed genes and proteins by ischemia with a relevant association in stroke pathology. The ischemia-induced deregulation of 10 of these inter-correlated elements was successfully verified in a new cohort of ischemic mice, and changes in their expression pattern were also evaluated at a later time-point after cerebral ischemia. Of those, CLDN20, GADD45G, RGS2, BAG5 and CTNND2 were highlighted and evaluated as potential blood biomarkers of cerebral ischemia in blood samples from ischemic and sham-control mice and from ischemic strokes and other patients presenting stroke-mimicking conditions. Our findings indicated that CTNND2 and GADD45G levels in blood within the first hours after ischemic stroke might be potentially useful to discriminate ischemic strokes from mimics and to predict patients’ poor outcome after stroke, respectively. In summary, we have here used for the first time an integrative approach to elucidate by means of biostatistical tools key elements of the initial stages of the stroke pathophysiology, highlighting new outstanding proteins that might be further considered as blood biomarkers of ischemic stroke.

Project description:Stroke remains a major leading cause of death and disability worldwide. Despite continuous advances, the identification of key molecular signatures of ischemic stroke within the hyper-acute phase of the disease is still of primary interest for a real translational research on stroke diagnosis, prognosis and treatment. High-throughput -omics technologies are enabling large-scale studies on stroke pathology at different molecular levels. Data integration resulting from these -omics approaches is becoming crucial to unravel the interactions among all different molecular elements and highly contribute to interpret all findings in a complex biological context. Here, we have used advanced data integration methods for multi-level joint analysis of transcriptomics and proteomics datasets depicted from the mouse brain 2h after cerebral ischemia. By modeling net-like correlation structures, we identified a set of differentially expressed genes and proteins with a relevant association in stroke pathology. The ischemia-induced deregulation of 10 of these inter-correlated elements was successfully verified in a new cohort of ischemic mice and changes in their expression pattern were also evaluated at a later time-point after cerebral ischemia. Of those, CLDN20, GADD45G, RGS2, BAG5 and CTNND2 were highlighted as potential candidates as blood biomarkers of cerebral ischemia and hence they were evaluated in blood samples from ischemic and sham-control mice and in ischemic strokes and patients presenting stroke-mimicking conditions. Our findings indicated that CTNND2 and GADD45G levels in blood within the first hours after ischemic stroke might be potentially useful to discriminate ischemic strokes from mimics and to predict patients’ poor outcome after stroke, respectively. In summary, we have here used for the first time an integrative approach that enabled us to elucidate by means of biostatistical tools key elements of the initial stages of the stroke pathophysiology and highlight new outstanding proteins that might be further considered as blood biomarkers of ischemic stroke.

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Comparative transcriptomic analysis of circulating endothelial cells in sickle cell stroke

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