4.8 Article

Monocyte, neutrophil, and whole blood transcriptome dynamics following ischemic stroke

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BMC MEDICINE
卷 21, 期 1, 页码 -

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BMC
DOI: 10.1186/s12916-023-02766-1

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Ischemic stroke; Gene expression; Blood; Monocytes; Neutrophils; Transcriptomics; RNA-seq; WGCNA; Hub genes; Pathway analyses; Time course

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After ischemic stroke, peripheral leukocytes infiltrate the damaged region and modulate the response to injury. Peripheral blood cells display distinctive gene expression signatures post-stroke, reflecting changes in immune responses to stroke. Analyzing the temporal dynamics of gene expression after stroke can improve our understanding of immune and clotting responses at the molecular and cellular level, and may assist with time-targeted, cell-specific therapy.
BackgroundAfter ischemic stroke (IS), peripheral leukocytes infiltrate the damaged region and modulate the response to injury. Peripheral blood cells display distinctive gene expression signatures post-IS and these transcriptional programs reflect changes in immune responses to IS. Dissecting the temporal dynamics of gene expression after IS improves our understanding of immune and clotting responses at the molecular and cellular level that are involved in acute brain injury and may assist with time-targeted, cell-specific therapy.MethodsThe transcriptomic profiles from peripheral monocytes, neutrophils, and whole blood from 38 ischemic stroke patients and 18 controls were analyzed with RNA-seq as a function of time and etiology after stroke. Differential expression analyses were performed at 0-24 h, 24-48 h, and >48 h following stroke.ResultsUnique patterns of temporal gene expression and pathways were distinguished for monocytes, neutrophils, and whole blood with enrichment of interleukin signaling pathways for different time points and stroke etiologies. Compared to control subjects, gene expression was generally upregulated in neutrophils and generally downregulated in monocytes over all times for cardioembolic, large vessel, and small vessel strokes. Self-organizing maps identified gene clusters with similar trajectories of gene expression over time for different stroke causes and sample types. Weighted Gene Co-expression Network Analyses identified modules of co-expressed genes that significantly varied with time after stroke and included hub genes of immunoglobulin genes in whole blood.ConclusionsAltogether, the identified genes and pathways are critical for understanding how the immune and clotting systems change over time after stroke. This study identifies potential time- and cell-specific biomarkers and treatment targets.

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