Profiles of lacunar and nonlacunar stroke

Abstract

Objective Determining which small deep infarcts (SDI) are of lacunar, arterial or cardioembolic etiology is challenging, but important in order to deliver optimal stroke prevention therapy. We sought to distinguish lacunar from non-lacunar causes of SDI using a gene expression profile. Methods A total of 184 ischemic strokes were analyzed. Lacunar stroke was defined as a lacunar syndrome with infarction <15mm in a region supplied by penetrating arteries. RNA from blood was processed on whole genome microarrays. Genes differentially expressed between lacunar (n=30) and non-lacunar strokes (n=86) were identified (false discovery rate ≤0.05, fold change>|1.5|) and used to develop a prediction model. The model was evaluated by cross-validation and in a second test cohort (n=36). The etiology of SDI of unclear cause (SDI≥15mm or SDI with potential embolic source) (n=32) was predicted using the derived model. Results A 41 gene profile discriminated lacunar from non-lacunar stroke with greater than 90% sensitivity and specificity. Of the 32 SDI of unclear cause, 15 were predicted to be lacunar and 17 were predicted to be non-lacunar. The identified profile represents differences in immune response between lacunar and non-lacunar stroke. Interpretation Profiles of differentially expressed genes can distinguish lacunar from non-lacunar stroke. SDIs of unclear cause were frequently predicted to be of non-lacunar etiology, suggesting comprehensive workup of SDI is important to identify potential cardioembolic and arterial causes. Further study is required to evaluate the gene profile in an independent cohort and determine the clinical and treatment implications of SDI of predicted non-lacunar etiology.

Blood transcriptome changes after stroke in an African American population

“…As such the application of gene expression analysis, using unbiased application of mathematical cluster analysis to identify stroke subtypes offers promise. Studies of microarrays and NGS show the diagnostic potential of such an approach 5, 6, 7, 8, 10, 23, 24, 25. Using molecular technology, preliminary diagnostic discrimination following stroke is over 90% accurate, with similar high sensitivity and specificity.…”

Potential blood biomarkers for stroke

“…The analysis of regulatory RNA such as miRNA, which regulates protein-coding gene pathways by blocking mRNA translation, or DNA expression, have been related to different disorders such as cancer or CVDs [109,110] . In the case of stroke, there have been several successful studies in animal models and humans in which altered profi les of RNA expression have been found [111][112][113] , and these results are promising with regard to the possible use of blood miRNAs as biomarkers for brain injuries [114] .…”

Expression profile based gene clusters for ischemic stroke detection

“…Results from Oh et al[21] were published after this study commenced. In several other microarray studies the utility of gene expression was investigated: for the evaluation of the risk of hemorrhagic transformation[23], defining stroke etiology[24-26] and in studying gender related gene expression changes in stroke patients[27,28]. …”