Prediction of Bleeding Risk After Anticoagulant Therapy for Atrial Fibrillation Based on Proteomics and Metabolomics

Objectives: Atrial fibrillation (AF) is the most common arrhythmia. Anticoagulation with warfarin or new oral anticoagulants in patients with AF can significantly reduce thromboembolic events. However, due to the lack of bleeding risk predictors of oral anticoagulants, the bleeding risk of patients with AF cannot be accurately evaluated. The purpose of this study is to screen biomarkers that can predict bleeding in patients with AF through proteomics and metabolomics, and construct the protein metabolic network pathway of anticoagulant bleeding in patients with AF. Design: AF patients treated with oral anticoagulants were enrolled in this study. Blood samples were centrifuged and the supernatant was stored in the refrigerator at - 80 ℃. All patients were followed up for one year to determine whether bleeding occurred after oral anticoagulants. Proteomic data were obtained by LC-MS/MS Analysis-DIA platform. Metabolomic data were obtained by UPLC-QTOF/MS platform. All of the omics data were used to compare proteins/enzymes with metabolic pathways. Quantitative changes of individual metabolites and proteins were calculated and graphed using the KEGG mapping tools.