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.

Inclusion Criteria:

1. Age 18 years or above
2. Admission with atrial fibrillation or clinic visit for atrial fibrillation
3. Receive routine anticoagulant therapy;
4. Signing the consent form

Exclusion Criteria:

1. Pregnant women;
2. Lactating women;
3. Severe mitral stenosis;
4. Severe impairment of liver function;
5. Severe renal insufficiency;
6. Thyroid dysfunction requiring treatment;
7. Have a history of severe bleeding within five years, such as intracerebral hemorrhage and gastrointestinal bleeding.

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.