Abstract

Gene expression changes in peripheral leukocytes display distinctive profiles after intracerebral hemorrhage (ICH) and ischemic stroke (IS), differentiating both conditions at the molecular level. The breadth of data produced by high-throughput transcriptomic analyses can identify groups of genes and main gene expression drivers that have meaningful functional associations with the disease. This can help prioritize the investigation of key genes for diagnosis and treatment. Thus, we performed whole transcriptome analyses on ICH and IS samples and constructed gene networks from a genome-wide perspective. RNA-seq was performed on peripheral blood (WB) and isolated monocytes (MON) and neutrophils (NEU) (n=6 ICH, n=33 IS and n=9 vascular risk factors control (VRFC) subjects). Gene expression results were used to construct separate co-expression networks for all datasets analyzed (ICH + VRFCs, and IS + VRFCs, for MON, NEU and WB) using Weighted Gene Co-expression Network Analysis. Modules of genes significantly associated with ICH in the ICH + VRFCs network, and with IS in the IS + VRFCs network, were identified. The most highly interconnected genes in each of these modules were identified, representing hub genes that are potential master regulators. Functional annotation of the modules and hubs were done using gene ontology. From the significantly associated modules for ICH and IS in all sample types analyzed, there was little overlap in genes between diagnoses (≤2% in MON, ≤21 % in NEU and ≤16% in WB), and no overlap of ICH or IS hub genes from MON and NEU. In WB, ≤2% of the hubs were common to ICH and IS. It is plausible that these potential master regulators drive diagnosis-specific gene expression profiles. ICH hubs were associated with RNA splicing and mRNA processing (MON), cell adhesion (NEU) and NF-κβ signaling (WB). IS hubs were associated with cell migration (MON), T cell chemotaxis (NEU) and transcription factor activity (WB). In addition, most hubs in IS MON were noncoding RNA. The gene networks and their respective hub genes provide novel cell-specific pathophysiological insights and could represent potential key pharmacological targets and biomarkers.

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