Pro‐adrenomedullin as an independent predictive biomarker for heart failure in atrial fibrillation and flutter

Abstract Aims This study aimed to investigate potential biomarkers for predicting incident heart failure (HF) in patients with atrial fibrillation and flutter (AF and AFL), utilizing proteomic data from the UK Biobank Pharma Proteomics Project (UKB‐PPP). Methods This study analysed data from AF and...

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Main Authors: Gaifeng Hu, Xiaodong Peng, Liu He, Yiwei Lai, Nian Liu, Xin Li, Caihua Sang, Jianzeng Dong, Changsheng Ma
Format: Article
Language:English
Published: Wiley 2025-06-01
Series:ESC Heart Failure
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Online Access:https://doi.org/10.1002/ehf2.15196
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Summary:Abstract Aims This study aimed to investigate potential biomarkers for predicting incident heart failure (HF) in patients with atrial fibrillation and flutter (AF and AFL), utilizing proteomic data from the UK Biobank Pharma Proteomics Project (UKB‐PPP). Methods This study analysed data from AF and AFL patients, split into discovery (n = 1050) and replication (n = 305) cohorts. Plasma biomarkers were screened using a multivariable‐adjusted Cox proportional hazards model. Kaplan–Meier survival analysis and area under the receiver operating characteristic (ROC) curve assessments were conducted to evaluate predictive performance. Results Over a follow‐up of 14.2 years, 222 cases (21.1%) of HF were documented in the discovery cohort, while 117 cases (38.4%) occurred over 13.8 years in the replication cohort. Out of 2923 proteins measured, only pro‐adrenomedullin (pro‐ADM) consistently showed a significant association with incident HF in both cohorts. In the discovery cohort, each unit increase in pro‐ADM was linked to an increased risk of HF (HR = 2.78, 95% CI 1.64–4.71, P < 0.001, FDR = 0.026), which was confirmed in the replication cohort (HR = 3.95, 95% CI 1.97–7.94, P < 0.001, FDR = 0.012). Kaplan–Meier analysis demonstrated that patients with higher pro‐ADM levels had significantly shorter time to HF onset, with median times ranging from 2306 to 3183 days across quartiles (P < 0.001). The cumulative incidence of HF ranged from 15.3% to 42.7% across quartiles of pro‐ADM (log‐rank P < 0.001). Adding pro‐ADM to a model with traditional risk factors, including NT‐proBNP, significantly improved predictive accuracy for 3‐year (AUC = 0.783; integrated discrimination improvement [IDI] = 0.010 and net reclassification index [NRI] = 0.206, both P = 0.002) and 5‐year (AUC = 0.749, IDI = 0.013, NRI = 0.179, P = 0.001) risk of HF. In sensitivity analyses, the association between pro‐ADM and incident HF remained consistent after excluding participants with self‐reported AF and AFL, with each unit increase in pro‐ADM being associated with an increased risk of HF (HR = 1.77, 95% CI 1.02–3.04, P = 0.041) and across subgroups of paroxysmal AF (HR = 2.80, 95% CI 1.11–7.07, P = 0.029) and persistent AF (HR = 4.36, 95% CI 1.41–13.43, P = 0.010). Conclusions Pro‐ADM is identified as an independent biomarker for predicting incident HF in AF and AFL patients. Its inclusion in risk prediction models enhances the ability to stratify HF risk beyond traditional biomarkers, demonstrating its potential utility in clinical practice.
ISSN:2055-5822