Proteomics and Recurrence of Atrial Fibrillation: A Pilot Study Nested in the PREDIMAR Trial - Cristina Razquin; Joaquín Fernandez-Irigoyen; María Teresa Barrio-López; Begoña López; Susana Ravassa; Pablo Ramos; Rosa Macías-Ruíz; Alicia Ibañez Criado; Enrique Santamaría; Leticia Goni; Eduardo Castellanos; Jose Luis Ibañez Criado; et al. (Lifestyle Genomics)
Introduction: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia worldwide. Although catheter ablation is the most efficacious therapy, relapses occur frequently (30%) in the first year after ablation. Novel biomarkers of recurrence are needed for a better prediction of recurrence and management of AF. In this pilot study, we aimed to analyze the baseline proteome of subjects included in a case-control study to find differential proteins associated with AF recurrence. Methods: Baseline serum proteomics (354 proteins) data from 16 cases (recurrent AF) and 17 controls (non-recurrent) were obtained using MS/MS analysis. A false discovery rate was performed using a nonlinear fitting method for the selection of proteins. Logistic regression models were used to further analyze the association between differentially expressed proteins and AF recurrence. Results: Ten proteins were differentially represented in cases vs. controls. Two were upregulated in the cases compared to the controls: keratin type I cytoskeletal 17 (Fold-change [FC] = 2.14; p = 0.017) and endoplasmic bifunctional protein (FC = 1.65; p = 0.032). Eight were downregulated in the cases compared to the controls: C4bpA (FC = 0.64; p = 0.006), coagulation factor XI (FC = 0.83; p = 0.011), CLIC1 (FC = 0.62; p = 0.017), haptoglobin (FC = 0.37; p = 0.021), Ig alpha-2 chain C region (FC = 0.49; p = 0.022), C4bpB (FC = 0.73; p = 0.028), N-acetylglucosamine-1-phosphotransferase subunit gamma (FC = 0.61; p = 0.033), and platelet glycoprotein Ib alpha chain (FC = 0.84; p = 0.038). Conclusion: This pilot study identifies ten differentially expressed serum proteins associated with AF recurrence, offering potential biomarkers for improved prediction and management.