Comprehensive proteomics profiling identifies patients with late gadolinium enhancement on cardiac magnetic resonance imaging in the hypertrophic cardiomyopathy population. (14th October 2021)

• Record Type: Journal Article
• Authors: Lander, B S; Zhao, Y; Hasegawa, K; Maurer, M S; Fifer, M A; Reilly, M P; Shimada, Y J
• Is Part Of: European heart journal. Volume 42(2021)Supplement 1
• Publication Date: 2021-10-14
• Subjects: Hypertrophic Cardiomyopathy; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; 616.12005
• DOI: 10.1093/eurheartj/ehab724.1764
• Languages: English
• ISSNs: 0195-668X

Abstract

Abstract: Introduction: Late gadolinium enhancement (LGE) on cardiac magnetic resonance imaging (CMR) represents myocardial fibrosis. In patients with hypertrophic cardiomyopathy (HCM), LGE on CMR has been associated with an increased risk of sudden cardiac death (SCD), which can be prevented with implantable cardioverter-defibrillators. Yet, CMR is expensive, resource-intensive, and, in certain patients, contraindicated. Therefore, it is important to determine which patients with HCM have a high pre-test probability of LGE on CMR. Proteomics profiling is a recently developed technology that simultaneously measures thousands of protein concentrations in plasma with a single blood draw. To date, no studies have examined the ability of proteomics profiling to identify which patients with HCM are more likely to have LGE on CMR. Purpose: To test the hypothesis that plasma proteomics profiling can distinguish patients with and without LGE on CMR in the HCM population. Methods: We performed a multicenter case-control (i.e., LGE vs. no LGE) study of 147 patients with HCM who underwent CMR between July 2006 and October 2020. We carried out plasma proteomics profiling of 4979 proteins using the SOMAscan assay. Using the 17 most discriminant proteins, we performed logistic regression analysis with elastic net regularization to develop a discrimination model with data from 1 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, specificity, positive predictive value (PPV), and negative predictive value (NPV). Furthermore, we performed pathway analysis of proteins that were differentially regulated between patients with and without LGE with p<0.05. Results: The mean age was 57 years and 67% were male. Overall, 82 of the 147 patients (56%) had LGE on CMR. The AUC of the 17-protein model was 0.83 (95% 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; Figure). The sensitivity, specificity, PPV, and NPV are shown in the Figure. The pathway analysis revealed that multiple signaling pathways were dysregulated in patients with LGE (Table). The list included signaling pathways that have been previously associated with myocardial fibrosis (e.g., pathways related to inflammation) and previously unrecognized pathways (e.g., glycolysis, amino acid metabolism). Conclusions: In this multicenter study of 147 patients with HCM, comprehensive proteomics profiling identified a panel of 17 plasma protein biomarkers to specify patients with LGE on CMR and revealed associated signaling pathways. This 17-protein plasma protein biomarker panel would help physicians specify patients with LGE, in whom CMR is more likely to change the clinical management of HCM. Funding Acknowledgement: Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Institute of Health, USA