Project description:Stroke remains a major leading cause of death and disability worldwide. Despite continuous advances, the identification of key molecular signatures of ischemic stroke within the hyper-acute phase of the disease is still of primary interest for a real translational research on stroke diagnosis, prognosis and treatment. High-throughput -omics technologies are enabling large-scale studies on stroke pathology at different molecular levels. Data integration resulting from these -omics approaches is becoming crucial to unravel the interactions among all different molecular elements and highly contribute to interpret all findings in a complex biological context. Here, we have used advanced data integration methods for multi-level joint analysis of transcriptomics and proteomics datasets depicted from the mouse brain 2h after cerebral ischemia. By modeling net-like correlation structures, we identified a set of differentially expressed genes and proteins with a relevant association in stroke pathology. The ischemia-induced deregulation of 10 of these inter-correlated elements was successfully verified in a new cohort of ischemic mice and changes in their expression pattern were also evaluated at a later time-point after cerebral ischemia. Of those, CLDN20, GADD45G, RGS2, BAG5 and CTNND2 were highlighted as potential candidates as blood biomarkers of cerebral ischemia and hence they were evaluated in blood samples from ischemic and sham-control mice and in ischemic strokes and patients presenting stroke-mimicking conditions. 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 mimics and to predict patients’ poor outcome after stroke, respectively. In summary, we have here used for the first time an integrative approach that enabled us to elucidate by means of biostatistical tools key elements of the initial stages of the stroke pathophysiology and highlight new outstanding proteins that might be further considered as blood biomarkers of ischemic stroke.

Project description:Aim of the present study is to identify all circulating miRNAs that are modulated in patients with stroke, to select specific miRNAs to be used as disease biomarkers to improve both diagnosis and prognosis. Background. Stroke is the second-most common cause of death worldwide. The major factor limiting prognosis in patients affected by acute stroke is the very limited therapeutic window, so that most patients are not able receive the most successful treatments because of delays in diagnosis and to differentiate between ischemic and hemorrhagic etiology. Circulating levels of selected microRNAs (miRNAs) were found to be modulated both in animal experimental models and in patients with stroke, opening up new avenues for the identification of more effective and specific biomarkers to identify and risk-stratify stroke patients. Study aim. Aim of the present study is to identify all circulating miRNAs that are modulated in patients with stroke, to select specific miRNAs to be used as disease biomarkers to improve both diagnosis and prognosis. Methods. RNA was extracted from plasma samples using a commercial RNA extraction kit and quality of extracted material was assessed using a fluorometric electrophoretic assay (Agilent 4200 TapeStation, Santa Clara, CA, USA). MiRNA profiling was performed using the Affymetrix platform using GeneChip 4.0 (Thermo Fischer Scientific, Waltham, MA, USA). RT-PCR was performed using the Taqman protocol. MiRNA were chosen among those with the most relevant modulation between the groups. Results. Among the circulating miRNAs that were most down-regulated in stroke patients, we identified miR-3135b (20-fold, p<0.001), associated with vascular calcifications and heart failure; miR-1275 (18-fold, p=0.028), involved in cardiovascular atherosclerotic diseases and a sponge for circMAN2B2 in cancer; miR-4467 (13-fold, p=0.003), modulated in neurodegenerative diseases; and miR-7170 (7-fold, p<0.001). Among the circulating miRNAs that were most up-regulated in stroke patients, we identified miR-18a (35-fold, p=0.004), associated with stroke in the Framingham Cohort; the platelet-enriched miR-22-5p (24-fold, p=0.004), that is modulated in Huntington Disease; miR-199a (11-fold, p=0.012), a marker of brain microvascular injury and of stroke severity in rats, and miR-106b (10-fold, p=0.009), a regulator of neural stem-cell proliferation/differentiation whose level are modulated in patients with neurodegenerative diseases. Conclusions. Our results identified several circulating miRNAs that are down- of up-regulated in stroke patients. Among those with the most relevant differential expression, several miRNAs were identified that are known to play a role in the pathophysiology of neurovascular diseases, paving the way to a new class of smart pathophysiology-based biomarkers in stroke.

Project description:Stroke remains a major leading cause of death and disability worldwide. Despite continuous advances, the identification of key molecular signatures of ischemic stroke within the hyper-acute phase of the disease is still of primary interest for a real translational research on stroke diagnosis, prognosis and treatment. High-throughput - omics technologies are enabling large-scale studies on stroke pathology at different molecular levels. Data integration resulting from these -omics approaches is becoming crucial to unravel the interactions among all different molecular elements and highly contribute to interpret all findings in a complex biological context. Here, we have used advanced data integration methods for multi-level joint analysis of transcriptomics and proteomics datasets depicted from the mouse brain 2h after cerebral ischemia. By modeling network-like correlation structures, we identified a set of differentially expressed genes and proteins by ischemia with a relevant association in stroke pathology. The ischemia-induced deregulation of 10 of these inter-correlated elements was successfully verified in a new cohort of ischemic mice, and changes in their expression pattern were also evaluated at a later time-point after cerebral ischemia. Of those, CLDN20, GADD45G, RGS2, BAG5 and CTNND2 were highlighted and evaluated as potential blood biomarkers of cerebral ischemia in blood samples from ischemic and sham-control mice and from ischemic strokes and other patients presenting stroke-mimicking conditions. 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 mimics and to predict patients’ poor outcome after stroke, respectively. In summary, we have here used for the first time an integrative approach to elucidate by means of biostatistical tools key elements of the initial stages of the stroke pathophysiology, highlighting new outstanding proteins that might be further considered as blood biomarkers of ischemic stroke.

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