Stroke Proteomics: From Discovery to Diagnostic and Therapeutic Applications

Abstract

Stroke remains a leading cause of death and disability, with limited therapeutic options and suboptimal tools for diagnosis and prognosis. High throughput technologies such as proteomics generate large volumes of experimental data at once, thus providing an advanced opportunity to improve the status quo by facilitating identification of novel therapeutic targets and molecular biomarkers. Proteomics studies in animals are largely designed to decipher molecular pathways and targets altered in brain tissue after stroke, whereas studies in human patients primarily focus on biomarker discovery in biofluids and, more recently, in thrombi and extracellular vesicles. Here, we offer a comprehensive review of stroke proteomics studies conducted in both animal and human specimen and present our view on limitations, challenges, and future perspectives in the field. In addition, as a unique resource for the scientific community, we provide extensive lists of all proteins identified in proteomic studies as altered by stroke and perform postanalysis of animal data to reveal stroke-related cellular processes and pathways.

Keywords: biomarkers; diagnosis; prognosis; proteomic; stroke; therapy.

Figure 1.

Schematic diagram summarizing sample sources, proteomics methods and applications of stroke proteomics studies executed in animal models and patients. AP, affinity purification; CSF, cerebrospinal fluid; ECF, extracellular fluid; EVs, extracellular vesicles; ICH, intracerebral hemorrhage; MS, mass spectrometry; SAH, subarachnoid hemorrhage. Image was partly created with BioRender.com.

Figure 2.

Heatmaps showing (A) (B) KEGG and Reactome pathways and (C) GO terms significantly enriched among DEPs in animal brain tissue after IS and HS. Datasets were derived from the following studies: Ischemia^{–,–,–,,,,–,,,}, ICH^,–,. Only DEPs that were identified in at least 2 proteomics studies were considered for analysis (Table S3, n=293 for ischemia and n=47 for ICH). Functional enrichment analysis was performed using g:Profiler. Benjamini-Hochberg FDR-corrected P values were plotted on a Log₁₀ scale. P values were considered significant for (A) (B) P<10⁻⁵ and (C) ischemia: GO-MF P<10⁻¹², GO-BP P<10⁻¹³, GO-CC P<10⁻²⁰; ICH: GO-MF P<10⁻⁷, GO-BP P<10⁻⁵, GO-CC P<10⁻⁹. FDR, false discovery rate.

Figure 3.

Heatmap comparing GO terms significantly enriched among post-stroke DEPs in animal brain tissue vulnerable to and protected from focal IS (MCAO). Datasets used for analysis were from the following studies: Vulnerable^{–,–,–,,,,,,,}, protected^,,,,,,. Enrichment analysis and data plotting were performed as in Figure 2. P values were considered significant for GO-MF P<10⁻⁸, GO-BP P<10⁻¹⁰, GO-CC P<10⁻⁸; n=98 for vulnerable UP, n=135 for vulnerable DOWN; n=8 for protected UP, n=7 for protected DOWN). FDR, false discovery rate; MCAO, middle cerebral artery occlusion.

Figure 4.

Venn Diagrams illustrating common DEPs after MCAO in animal brain tissue and CSF. (A) 20 DEPs in blue were upregulated in both tissue and CSF. They largely constitute “classic” plasma proteins. (B) 22 DEPs shaded in brown were decreased in tissue, while increased in CSF. They are mainly intracellular proteins. There is no overlap of proteins downregulated in CSF with any proteins detected in tissue. All DEPs used for this analysis are listed in Table S3. CSF, cerebrospinal fluid.