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Recent studies have revealed the systematic altering of gene expression in human peripheral blood during the early stages of ischemic stroke, which suggests a new potential approach for the rapid diagnosis or prediction of stroke onset. Nevertheless, due to the difficulties of collecting human samples during proper disease stages, related studies are rather restricted. Many studies have instead been performed on manipulated animal models for investigating the regulation patterns of biomarkers during different stroke stages. An important inquiry is how well the findings of animal models can be replicated in human cases. Here, a method is proposed based on PageRank scores of miRNA-mRNA interaction network to select ischemic stroke biomarkers derived from rat brain samples, and biomarkers are validated with two human peripheral blood gene expression datasets. Hierarchical clustering results revealed that the achieved biomarkers clearly separate the blood gene expression of stroke patients and healthy people. Literature searches and functional analyses further validated the biological significance of these biomarkers. Compared to the traditional methods, such as differential expression, the proposed approach is more stable and accurate in detecting cross-species biomarkers with biological relevance, thereby suggesting an efficient approach of re-using gene biomarkers obtained from animal-model studies for human diseases.

Obtaining Human Ischemic Stroke Gene Expression Biomarkers from Animal Models: A Cross-species Validation Study