Stroke remains a leading cause of death and disability worldwide. Despite continuous advances, the identification of key molecular signatures of acute ischemic stroke is still of primary interest for a real translational research on stroke diagnosis, prognosis and treatment. Integration of data from high-throughput -omics techniques is crucial to unravel key interactions among different molecular elements in a complex biological context. Here, we used advanced data integration methods for a multi-level joint analysis of transcriptomics and proteomics datasets depicted from the mouse brain 2h after cerebral ischemia. We identified a correlation-based integrated network of genes and proteins differentially expressed acutely after stroke. Of those, CLDN20, GADD45G, RGS2, BAG5 and CTNND2 were further evaluated as blood biomarkers of cerebral ischemia in mice and human blood samples. Our findings indicated that CTNND2 and GADD45G levels in blood within the first hours after ischemic stroke might be potentially useful to discriminate ischemic strokes from stroke-mimicking conditions and to predict stroke patients’ poor outcome, respectively. Together, we used for the first time an integrative biostatistical approach to elucidate key molecules of the initial stages of stroke pathophysiology and highlight new outstanding proteins that might be further considered as blood biomarkers of ischemic stroke.