دورية أكاديمية

Comprehensive Proteomics Profiling Identifies Patients With Late Gadolinium Enhancement on Cardiac Magnetic Resonance Imaging in the Hypertrophic Cardiomyopathy Population

التفاصيل البيبلوغرافية
العنوان: Comprehensive Proteomics Profiling Identifies Patients With Late Gadolinium Enhancement on Cardiac Magnetic Resonance Imaging in the Hypertrophic Cardiomyopathy Population
المؤلفون: Bradley S. Lander, Yanling Zhao, Kohei Hasegawa, Mathew S. Maurer, Albree Tower-Rader, Michael A. Fifer, Muredach P. Reilly, Yuichi J. Shimada
المصدر: Frontiers in Cardiovascular Medicine, Vol 9 (2022)
بيانات النشر: Frontiers Media S.A., 2022.
سنة النشر: 2022
المجموعة: LCC:Diseases of the circulatory (Cardiovascular) system
مصطلحات موضوعية: hypertrophic cardiomyopathy, late gadolinium enhanced (LGE), myocardial fibrosis, proteomics, cardiac magnetic resonance (MRI), Diseases of the circulatory (Cardiovascular) system, RC666-701
الوصف: IntroductionIn hypertrophic cardiomyopathy (HCM), late gadolinium enhancement (LGE) on cardiac magnetic resonance imaging (CMR) represents myocardial fibrosis and is associated with sudden cardiac death. However, CMR requires particular expertise and is expensive and time-consuming. Therefore, it is important to specify patients with a high pre-test probability of having LGE as the utility of CMR is higher in such cases. The objective was to determine whether plasma proteomics profiling can distinguish patients with and without LGE on CMR in the HCM population.Materials and MethodsWe performed a multicenter case-control (LGE vs. no LGE) study of 147 patients with HCM. We performed plasma proteomics profiling of 4,979 proteins. Using the 17 most discriminant proteins, we performed logistic regression analysis with elastic net regularization to develop a discrimination model with data from one institution (the training set; n = 111) and tested the discriminative ability in independent samples from the other institution (the test set; n = 36). We calculated the area under the receiver-operating-characteristic curve (AUC), sensitivity, and specificity.ResultsOverall, 82 of the 147 patients (56%) had LGE on CMR. The AUC of the 17-protein model was 0.83 (95% confidence interval [CI], 0.75–0.90) in the training set and 0.71 in the independent test set for validation (95% CI, 0.54–0.88). The sensitivity of the training model was 0.72 (95% CI, 0.61–0.83) and the specificity was 0.78 (95% CI, 0.66–0.90). The sensitivity was 0.71 (95% CI, 0.49–0.92) and the specificity was 0.74 (95% CI, 0.54–0.93) in the test set. Based on the discrimination model derived from the training set, patients in the test set who had high probability of having LGE had a significantly higher odds of having LGE compared to those who had low probability (odds ratio 29.6; 95% CI, 1.6–948.5; p = 0.03).ConclusionsIn this multi-center case-control study of patients with HCM, comprehensive proteomics profiling of 4,979 proteins demonstrated a high discriminative ability to distinguish patients with and without LGE. By identifying patients with a high pretest probability of having LGE, the present study serves as the first step to establishing a panel of circulating protein biomarkers to better inform clinical decisions regarding CMR utilization.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2297-055X
Relation: https://www.frontiersin.org/articles/10.3389/fcvm.2022.839409/full; https://doaj.org/toc/2297-055X
DOI: 10.3389/fcvm.2022.839409
URL الوصول: https://doaj.org/article/1d4b77c3a8b64e2fb5174549fc803275
رقم الأكسشن: edsdoj.1d4b77c3a8b64e2fb5174549fc803275
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2297055X
DOI:10.3389/fcvm.2022.839409