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Altered granulopoiesis aggravates stroke in the elderly [bulk RNA-seq]

ABSTRACT: Ischemic stroke is one of the leading causes of disability and mortality worldwide, recognizing aging as a prominent risk factor and determinant of dismal outcome. Aging is known to lead to overall frailty due to multifactorial changes, but pathogenic mechanisms underlying poor outcome remain unclear. Here we show that deterioration in elderly stroke is preceded by neutrophil accumulation and clogging in the ischemic brain microcirculation leading to a worse no-reflow phenomenon. With high-dimensional single-cell profiling over time of the brain's, blood's, and bone marrow's immune response, we could delineate after stroke four main neutrophil clusters in the blood whose quantitative and temporal dynamic of release is deranged in the bone marrow of the old. In the elderly, stroke triggers an early surge in the blood of the CD62Llo neutrophil subset characterized by a signature of bone marrow proximity, senescence, and oxidative stress. Functionally, transfer of this neutrophil subset displaying prominent thrombogenic features in young stroke mice leads to increased clogging of the ischemic brain microcirculation, worse no-reflow and outcome. Interrogating the blood leukocyte landscape of a large human stroke cohort with extensive single-cell proteome analyses, we confirmed that older stroke patients display a similar precocious accumulation of blood CD62Llo neutrophil subset, worse reperfusion and outcome. Our results demonstrate how age-related alterations in the process of neutrophil differentiation and release from the bone marrow have a relevant pathogenic role in the major cerebrovascular disorder affecting the world population, that unleash emergency granulopoiesis.

ORGANISM(S): Mus musculus

PROVIDER: GSE174438 | GEO | 2023/05/16

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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Altered granulopoiesis aggravates stroke in the elderly [bulk RNA-seq]

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