Abstract WP143: Identification of Socially-Regulated Circulating Microrna Signatures in Stroke

Abstract

Introduction: Epidemiological and clinical studies strongly support that social isolation (SI) is associated with higher mortality after stroke. SI has been identified as a risk factor in a wide variety of diseases, including stroke. However, few studies have attempted to identify the underlying mechanisms contributing to the detrimental effect of SI. To better understand systemic and global regulation networks governed by social factors, and in an attempt to identify viable biomarkers, we profiled changes in circulating microRNA (miRNA) expression in aged stroke mice after SI. Methods: Aged C57BL/6 mice (18-20 months) of both sexes were pair-housed (PH) or socially isolated (SI) for two weeks prior to sham or a 60-minute middle cerebral artery occlusion surgery. Mice were sacrificed two weeks after surgery and blood samples were obtained for profiling of plasma miRNAs. Using whole miRNAome analysis, differentially expressed miRNAs by isolation, stroke and sex differences were comprehensively identified and compared using bioinformatics. We further used mimic and antagomiR treatments to confirm a potential role of the identified miRNAs. Results: Stroke significantly changed 8 miRNAs including miR-467d-3p ( P =0.0014), miR-376b-3p ( P =0.013) and miR-297c-5p ( P =0.016) in PH groups (sham vs. stroke). In a comparison between PH vs. SI in stroke mice, stroke SI mice showed a differential miRNA profile (11 miRNAs) including let-7 family potentially targeting Dicer protein, a key enzyme for miRNA biogenesis. Interestingly, compared to sham SI mice, stroke SI mice had a 2-fold increase in the number of altered miRNAs (21 miRNAs) including miR-129-1-3p ( P =0.0075), miR-28a-3p ( P =0.0091) and miR-204-5p ( P =0.016). Finally, we found a strong sex difference in miRNA expression in response to SI. Conclusions: We identified several key miRNAs as potential biomarkers for 1) stroke, 2) SI and 3) SI/stroke. These miRNA signatures are highly unique and create a complex gene-regulatory network that depends on the social environment. Our data provide potential biomarkers and identify several miRNAs that could lead to significant improvements in diagnosis of elderly patients at elevated risk for the detrimental effects of loneliness.