Detection and Determination of Protein Network Associated with Atrial Fibrillation Phenotypes

Atrial fibrillation (AF) is associated with increased risks of stroke, cardiac failure, and mortality. Since the discrimination of AF phenotype is inadequate, accurate diagnosis remains elusive. Left atrial appendage tissue resected routinely during the maze procedure was collected from patients with paroxysmal, persistent, and longstanding persistent arrhythmia. In situ comprehensive proteomic approaches of matrix-assisted laser desorption/ ionization imaging mass spectrometry was used to differentiate and classify the spatial molecular processes in the pathology of AF phenotypes. Using unsupervised computational evaluation strategy, probabilistic latent semantic clustering, and receiver operating characteristic analysis (SCiLS Lab), the acquired peptide signatures and characteristic m/z species could be used to assign the AF phenotype. Intensity distribution of the given m/z values, which are discriminative for the considered cluster, was determined to distinguish between paroxysmal and persistent AF (mean, 4.08 ± 1.21 vs 1.59 ± 0.12, p=0.09) and persistent and long-standing persistent AF (1.59 ± 0.12 vs 6.85 ± 3.02, p=0.02). Tissue-based proteomic approach provides clinically relevant information, which may be beneficial in improving risk stratification in AF patients.