Abstract 4369563: Expression of proteins encoded by putative atrial fibrillation risk genes in human left atrial appendage differs by AF state

Abstract

Introduction: Atrial fibrillation (AF) is a common cardiac arrhythmia. Putative genes associated with AF risk have been identified through large genome wide association studies. How expression of these proteins in the left atria differs by AF state (no history of AF, history of paroxysmal AF, history of persistent AF, persistent AF, long-standing persistent AF) has not been examined. Hypothesis: We hypothesized that proteins associated with AF risk differ by AF state. Methods: Left atrial appendage (LAA) tissue was obtained from 222 Cleveland Clinic patients undergoing cardiac surgery. At surgery, 104 were in sinus rhythm (SR) (24 without a history of AF, 50 had a history of paroxysmal AF, 30 had a history of persistent AF) and 118 patients were in AF rhythm (65 with history of persistent AF, 53 long-standing persistent AF). Proteins (n=2539) were identified by mass spectrometry. Protein levels were modeled for associations with AF state using linear regression and adjusted for sex, age, and 23 inferred surrogate variables. Results: Among the quantified proteins we identified 33 encoded from putative AF risk genes. Of these, CASQ2 was increased (p<0.05) and TTN was decreased in patients with a history of AF in SR compared to patients with no history of AF (Table 1A). There were nine proteins that differed between AF rhythm and sinus rhythm, of which five (SYNPO2L, MYPN, NACA, PKP2, and CALU) were increased (Table 1B) and four (TUBA8, MYOZ1, CASQ2, and CAMK2D) were decreased. In patients diagnosed with persistent AF in AF rhythm versus those with a history of persistent AF but in SR at surgery, four were increased (SYNPO2L, MYPN, NACA, and PKP2) and two (CASQ2 and CAMK2D) were decreased (Table 1C). Expression of proteins encoded by putative AF risk genes was not different in long-standing persistent AF rhythm compared to persistent AF rhythm. Conclusions: In one of the largest proteomic datasets in human LAA, we found that key proteins encoded by genes associated with AF risk are altered in patients in AF rhythm. Expression of these proteins also differs by AF state. These studies provide insight into pathways that may be targeted for AF prevention and highlight the importance of early intervention to prevent AF progression.