Association between T cell exhaustion and the recurrence of atrial fibrillation after cryoballoon ablation
Rong Suo1,2, Shiyu Qi1, Wenhua Song1
1Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Background:
Atrial fibrillation (AF) recurrence remains a challenge after Cryoballoon ablation (CBA). To date, few studies have investigated the impact of immunosenescence, particularly exhausted T cells, on AF recurrence after CBA. This study aims to investigate the association between exhausted T cells and AF recurrence after CBA, and to develop a novel model for the prediction of AF recurrence.
Methods:
Clinical data of patients undergoing CBA treatment for AF at Tianjin Medical University Second Hospital from March to November 2022 were collected, and AF recurrence was followed up. Flow cytometry was employed to evaluate the levels of inhibitory receptors (IR) on exhausted T cells, including killer cell lectin-like receptor G1 (KLRG1), programmed death-1 (PD-1), T cell immunoglobulin and mucin domain-containing molecule 3 (Tim-3), lymphocyte activation gene 3 (LAG-3), CD27, and CD57. Variables selected through Lasso regression analyses were incorporated into a multivariable Cox proportional hazards model to validate and identify independent risk factors for AF recurrence, building two predictive models. The efficacy of the two models was assessed using Receiver Operating Characteristic (ROC) curves, calibration curves, and Decision Curve Analysis (DCA).
Results:
Cox multivariate regression analysis revealed that KLRG1 of CD8+ T central memory cell (Tcm), PD-1 of CD8+ naive T cell (Tnaive), mean corpuscular volume (MCV), γ-Glutamyl Transferase (γ-GGT), glucose, and mitral valve maximum blood flow velocity (MV Vmax) were significant predictors. Two models were developed based on Cox multivariate regression analysis. Model 1 includes MCV, γ-GGT, glucose, and MV Vmax, while Model 2 includes all risk factors: MCV, γ-GGT, glucose, MV Vmax, KLRG1 of CD8+ Tcm, and PD-1 of CD8+ Tnaive. Validation of both models revealed that Model 2 showed better predictive performance, and a nomogram was created to present the results visually.
Conclusion:
The KLRG1 of CD8+ Tcm and PD-1 of CD8+ Tnaive are novel independent risk factors for AF recurrence after CBA and play a significant role in the early recurrence of AF. We constructed a new predictive nomogram incorporating KLRG1 of CD8+ Tcm and PD-1 of CD8+ Tnaive as key variables, which can enhance the predictive value for AF recurrence in patients after CBA surgery.
