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Liu M, Zhang Y, Ye Z, He P, Zhou C, Yang S, Zhang Y, Gan X, Qin X. Enhanced prediction of atrial fibrillation risk using proteomic markers: a comparative analysis with clinical and polygenic risk scores. Heart 2024:heartjnl-2024-324274. [PMID: 39237126 DOI: 10.1136/heartjnl-2024-324274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 08/21/2024] [Indexed: 09/07/2024] Open
Abstract
BACKGROUND Proteomic biomarkers have shown promise in predicting various cardiovascular conditions, but their utility in assessing the risk of atrial fibrillation (AF) remains unclear. This study aimed to develop and validate a protein-based risk score for predicting incident AF and to compare its predictive performance with traditional clinical risk factors and polygenic risk scores in a large cohort from the UK Biobank. METHODS We analysed data from 36 129 white British individuals without prior AF, assessing 2923 plasma proteins using the Olink Explore 3072 assay. The cohort was divided into a training set (70%) and a test set (30%) to develop and validate a protein risk score for AF. We compared the predictive performance of this score with the HARMS2-AF risk model and a polygenic risk score. RESULTS Over an average follow-up of 11.8 years, 2450 incident AF cases were identified. A 47-protein risk score was developed, with N-terminal prohormone of brain natriuretic peptide (NT-proBNP) being the most significant predictor. In the test set, the protein risk score (per SD increment, HR 1.94; 95% CI 1.83 to 2.05) and NT-proBNP alone (HR 1.80; 95% CI 1.70 to 1.91) demonstrated superior predictive performance (C-statistic: 0.802 and 0.785, respectively) compared with HARMS2-AF and polygenic risk scores (C-statistic: 0.751 and 0.748, respectively). CONCLUSIONS A protein-based risk score, particularly incorporating NT-proBNP, offers superior predictive value for AF risk over traditional clinical and polygenic risk scores, highlighting the potential for proteomic data in AF risk stratification.
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Affiliation(s)
- Mengyi Liu
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Yuanyuan Zhang
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Ziliang Ye
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Panpan He
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Chun Zhou
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Sisi Yang
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Yanjun Zhang
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Xiaoqin Gan
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
| | - Xianhui Qin
- Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Organ Failure Research; Guangdong Provincial Institute of Nephrology; Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, Guangdong, China
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Matthia EL, Setteducato ML, Elzeneini M, Vernace N, Salerno M, Kramer CM, Keeley EC. Circulating Biomarkers in Hypertrophic Cardiomyopathy. J Am Heart Assoc 2022; 11:e027618. [PMID: 36382968 PMCID: PMC9851432 DOI: 10.1161/jaha.122.027618] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Hypertrophic cardiomyopathy is the most common genetic heart disease. Biomarkers, molecules measurable in the blood, could inform the clinician by aiding in diagnosis, directing treatment, and predicting outcomes. We present an updated review of circulating biomarkers in hypertrophic cardiomyopathy representing key pathologic processes including wall stretch, myocardial necrosis, fibrosis, inflammation, hypertrophy, and endothelial dysfunction, in addition to their clinical significance.
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Affiliation(s)
| | | | | | | | - Michael Salerno
- Department of Medicine, Cardiovascular DivisionUniversity of VirginiaCharlottesvilleVA
| | - Christopher M. Kramer
- Department of Medicine, Cardiovascular DivisionUniversity of VirginiaCharlottesvilleVA
| | - Ellen C. Keeley
- Department of MedicineUniversity of FloridaGainesvilleFL,Division of Cardiovascular MedicineUniversity of FloridaGainesvilleFL
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Wei Z, Zhu E, Ren C, Dai J, Li J, Lai Y. Triglyceride-Glucose Index Independently Predicts New-Onset Atrial Fibrillation After Septal Myectomy for Hypertrophic Obstructive Cardiomyopathy Beyond the Traditional Risk Factors. Front Cardiovasc Med 2021; 8:692511. [PMID: 34368252 PMCID: PMC8342798 DOI: 10.3389/fcvm.2021.692511] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 07/01/2021] [Indexed: 11/13/2022] Open
Abstract
The triglyceride-glucose index is a valuable marker of insulin resistance. However, the predictive value of this index for postoperative atrial fibrillation in patients undergoing septal myectomy remains unclear. A total of 409 patients with hypertrophic obstructive cardiomyopathy who underwent septal myectomy were recruited in this study. The triglyceride-glucose index was calculated for all patients preoperatively. All patients underwent clinical data collection, blood sampling, and standard echocardiographic examinations during hospitalization. The prevalence of postoperative atrial fibrillation was approximately 15% in the present study. Multivariate logistic regression revealed that age (odds ratio [OR]: 1.053, 95% CI: 1.016-1.090, P = 0.004), hypertension (OR: 2.399, 95% CI: 1.228-4.686, P = 0.010), left atrial diameter (OR: 1.101, 95% CI: 1.050-1.155, P < 0.001), and triglyceride-glucose index (OR: 4.218, 95% CI: 2.381-7.473, P < 0.001) were independent risk factors for postoperative atrial fibrillation in patients undergoing septal myectomy. In receiver operating characteristic curve analysis, the triglyceride-glucose index could provide a moderate predictive value for postoperative atrial fibrillation after septal myectomy 0.723 (95% CI: 0.650-0.796, P < 0.001). Moreover, adding the triglyceride-glucose index to conventional risk factor model could numerically but not significantly increase our ability to predict postoperative atrial fibrillation (area under the receiver: 0.742 (0.671-0.814) vs. 0.793 (0.726-0.860), p = 0.065) after septal myectomy. In our retrospective cohort study, the triglyceride-glucose index was identified as an independent predictor of postoperative atrial fibrillation in patients undergoing septal myectomy.
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Affiliation(s)
| | | | | | | | | | - Yongqiang Lai
- Department of Cardiac Surgery, Institute of Heart, Lung and Blood Vascular Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
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