Abstract Body: Introduction: Atrial fibrillation (AFib) is a major risk factor for ischemic stroke (IS). AFib diagnosis is critical to optimize secondary prevention and reduce the recurrent stroke risk.
Objectives: We undertook an exploratory cross-platform proteomics study to discover plasma biomarkers of AFib diagnosis in patients with IS or transient ischemic attack (TIA).
Methods: We used clinical and proteomics data of stroke patients aged ≥18 years lodged within a prospective plasma repository from 2010 to 2014. We collected blood from each patient at hospital admission before administering any therapeutic intervention. Our outcome was differentially expressed levels of proteins in stroke patients with AFib compared to patients without AFib. We performed aptamer-based proteomics using the plasma 7K SomaScan assay. We identified the differentially expressed proteins using (i) ±1.5-fold change and unadjusted p-value <0.05 cut-offs, (ii) Boruta random forest-based machine learning algorithm, and (iii) 30% or more variation explained by AFib in variance partitioning analysis (VPA). We selected the top proteins that were identified using two of the three selection approaches and conducted multivariable adjusted analyses. We conducted internal validation on the same samples using the PeptiQuant Plus biomarker assessment kits (BAK-270) for targeted protein quantitation.
Results: We included 60 patients with IS/TIA (mean age 62.9 years, 50% males) classified into 11 AFib and 49 no AFib (Figure 1). SomaScan quantified 7307 protein targets including 6373 unique proteins. We identified 171 differentially expressed proteins in stroke patients with AFib compared to no AFib. After adjusting for age, sex, diabetes, and coronary artery disease in the multivariable analysis, we identified 53 top proteins independently associated with AFib in stroke patients (adjusted p<0.05) (Figure 2). In the validation phase, we quantified 216 proteins using the BAK-270 platform, of which 185 proteins were overlapping with SomaScan. Using BAK-270, we validated increased levels of IGFBP2, B2M, and COL18A1 and decreased levels of CNDP1, AHSG, and SERPINA4 in stroke patients with AFib compared to no AFib (Figure 3).
Conclusions: Our exploratory study highlights the potential of plasma proteomics as a valuable tool for discovering protein biomarkers to discriminate IS/TIA patients with AFib compared to no AFib. Further longitudinal studies with adequate sample sizes are needed to support these findings.