Abstract WP293: Plasma proteomic signatures associated with ischemic stroke etiologies

BACKGROUND: Identifying acute ischemic stroke (AIS) etiology guides targeted therapy implementatoin to prevent recurrent stroke. We derive plasma protein signatures of non-cryptogenic AIS etiologies and apply them to cryptogenic strokes to predict etiologies. METHODS: We studied adults at Yale-New Haven Hospital with an AIS from 2015-2020 and stored plasma samples. Proteins were measured with a SomaScan 11K Assay. Etiology was adjudicated by > 2 board-certified vascular neurologists. ANOVA tests identified proteins significantly different among the 4 non-cryptogenic etiologies (large artery atherosclerosis (LAA), cardioembolism (CE), small vessel disease (SVD), and other rare, determined etiologies (ODE)). Proteins with fold change > 1.2 and p-value < 0.05 were selected without multiple testing adjustment in this exploration. We built logistic regression models to classify 4-level and binary etiologies versus not with: A) age, B) age, sex, C) age, sex, hypertension, D) proteins, and E) age, sex, hypertension, proteins selected by stepwise selection for each outcome. We computed 95% confidence intervals for binary models with 2,000 bootstrap replicates. The PheWeb 2019 database was used to link predictive proteins with phenotypes. We applied the 4-level model to cryptogenic strokes to predict non-cryptogenic etiologies. RESULTS: We included 64 patients (median age 69 years IQR 58-76, 42.2% female, last known well to sample collection time: median 27 hours IQR 22-68, LAA n=15; CE n=23; SVD n=6; ODE n=7; cryptogenic n=13). Of 11,083 proteins, there were 40 differentially expressed proteins among 4 etiologies ( Figure 1 ). Three proteins (lithostathine-1-beta, transcription factor SOX-21, creatine kinase M- and B-types) classified 4-level etiologies: areas under the curve (AUC) Model A: 0.69, B: 0.70, C: 0.76, D: 0.84, E: 0.88; Table ). AUCs for each etiology were: 0.88 LAA (95% CI 0.78-0.97), 0.89 CE (0.80-0.98), 0.98 SVD (0.94-1.0), and 0.97 ODE (0.94-1.00). Identified proteins are linked with malignancy, varicella zoster, inflammation, hematologic conditions, and atrial fibrillation ( Figure 2) . In the cryptogenic stroke cohort, 7 patients had highest predicted probabilities for LAA (range: 0.55-0.83) and 6 for CE (0.47-0.85). CONCLUSION: We derived plasma proteomic signatures of non-cryptogenic etiologies with biologic plausibility and applied them to predict etiologies in cryptogenic AIS. Further studies are needed to evaluate their generalizability.