Dataset Information

MicroRNA Analysis of Human Stroke Brain Tissue Resected during Decompressive Craniectomy/Stroke-Ectomy Surgery.

ABSTRACT:

Background

Signaling pathways mediated by microRNAs (miRNAs) have been identified as one of the mechanisms that regulate stroke progression and recovery. Recent investigations using stroke patient blood and cerebrospinal fluid (CSF) demonstrated disease-specific alterations in miRNA expression. In this study, for the first time, we investigated miRNA expression signatures in freshly removed human stroke brain tissue.

Methods

Human brain samples were obtained during craniectomy and brain tissue resection in severe stroke patients with life-threatening brain swelling. The tissue samples were subjected to histopathological and immunofluorescence microscopy evaluation, next generation miRNA sequencing (NGS), and bioinformatic analysis.

Results

miRNA NGS analysis detected 34 miRNAs with significantly aberrant expression in stroke tissue, as compared to non-stroke samples. Of these miRNAs, 19 were previously identified in stroke patient blood and CSF, while dysregulation of 15 miRNAs was newly detected in this study. miRNA direct target gene analysis and bioinformatics approach demonstrated a strong association of the identified miRNAs with stroke-related biological processes and signaling pathways.

Conclusions

Dysregulated miRNAs detected in our study could be regarded as potential candidates for biomarkers and/or targets for therapeutic intervention. The results described herein further our understanding of the molecular basis of stroke and provide valuable information for the future functional studies in the experimental models of stroke.

SUBMITTER: Carlson AP

PROVIDER: S-EPMC8702168 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Purpose: Signaling pathways mediated by microRNAs (miRNAs) represent one of the mechanisms that regulate stroke progression and recovery. The goal of this study is to investigate miRNA expression signatures in freshly removed human stroke brain tissue. Methods: Human brain samples (5 stroke and 3 non-stroke samples) obtained at 48-72 hours after stroke onset during craniectomy and stroke-ectomy, were subjected to histopathological and immunofluorescence microscopy analyses. NGS sequencing was performed by Qiagen company and analyses were carried out using QIAseq miRNA Quantification workflow and RNA-seq Analysis tools within CLC Genomics Workbench (version 20.0.2). Reads were normalized for expression analysis using trimmed mean of M-values method (TMM). miRNA profiling was performed using the EdgeR in Bioconductor package. Whole transcriptome RNA-sequencing Analysis: The unmapped reads from the NGS miRNA analysis were extracted, deduplicated and mapped to the genome. Gene expressions were calculated by counting number of reads mapping to the annotated gene loci. Human miR-155 Targets RT2 Profiler PCR Array (Qiagen) was performed using 3 RNA samples per stroke and control groups. The PCR Array Data analysis was performed using an automated PCR Analysis Web Portal and GeneGlobe Data Analysis (Qiagen). Results: Human stroke brain tissue was characterized by classic ischemic changes, including significant neuronal and vascular damage, and prominent edema. The absence of monocytes and notable neutrophil infiltration indicated the early stage of leukocyte response to ischemia. miRNA NGS analysis detected 36 miRNAs with significantly aberrant expression in stroke tissue, as compared to non-stroke samples. Of these miRNAs, 19 were previously identified in stroke patient blood and CSF, while dysregulation of 16 miRNAs was newly detected in this study. Bioinformatics pathway enrichment analysis demonstrated a strong association of the identified miRNAs with stroke-related biological processes and signaling pathways Conclusions: Dysregulated miRNAs detected in our study could be regarded as potential candidates for biomarkers and/or targets for therapeutic intervention. The obtained data will serve for better understanding of the molecular basis of stroke and provide valuable information for the future functional studies in the experimental models of stroke.

Project description:BackgroundDecompressive craniectomy (DC) is a surgical intervention used following traumatic brain injury to prevent or alleviate raised intracranial pressure. However the clinical effectiveness of the intervention remains in doubt. The location of the craniectomy (unilateral or bifrontal) might be expected to change the brain deformation associated with the operation and hence the clinical outcome. As existing methods for assessing brain deformation have several limitations, we sought to develop and validate a new improved method.MethodsComputed tomography (CT) scans were taken from 27 patients who underwent DC (17 bifrontal patients and 10 unilateral patients). Pre-operative and post-operative images were processed and registered to determine the change in brain position associated with the operation. The maximum deformation in the herniated brain, the change in volume and estimates of the craniectomy area were determined from the images. Statistical comparison was made using the Pearson's correlation coefficient r and a Welch's two-tailed T-test, with statistical significance reported at the 5% level.ResultsThere was a reasonable correlation between the volume increase and the maximum brain displacement (r = 0.64), a low correlation between the volume increase and the craniectomy area (r = 0.30) and no correlation between the maximum displacement and the craniectomy area (r = -0.01). The maximum deformation was significantly lower (P = 0.023) in the bifrontal patients (mean = 22.5 mm) compared with the unilateral patients (mean = 29.8 mm). Herniation volume was significantly lower (P = 0.023) in bifrontal (mean = 50.0 ml) than unilateral patients (mean = 107.3 ml). Craniectomy area was not significantly different for the two craniectomy locations (P = 0.29).ConclusionsA method has been developed to quantify changes in brain deformation due to decompressive craniectomy from CT images and allow comparison between different craniectomy locations. Measured displacement is a reasonable way to characterise volume changes.