Key result
A 5-protein model distinguishes HCM from other LVH cardiomyopathies with an AUC of 0.86.
Why the study?
Distinguishing hypertrophic cardiomyopathy from other cardiomyopathies with left ventricular hypertrophy is sometimes challenging.
Does plasma proteomics profiling identify circulating biomarkers that can distinguish hypertrophic cardiomyopathy from other causes of left ventricular hypertrophy?
Case-Control (n=1,415)
Yes
Does plasma proteomics profiling identify circulating biomarkers that can distinguish hypertrophic cardiomyopathy from other causes of left ventricular hypertrophy?
A 5-protein panel identified via plasma proteomics profiling can accurately distinguish hypertrophic cardiomyopathy from other causes of left ventricular hypertrophy.
Answers are grounded in this paper and cite their sources.
May support proteomic differentiation of HCM from other LVH; leaves open prospective validation before clinical adoption.
BACKGROUND: Distinguishing hypertrophic cardiomyopathy (HCM) from other cardiomyopathies with left ventricular hypertrophy (LVH), such as hypertensive LVH, transthyretin amyloid cardiomyopathy, and aortic stenosis, is sometimes challenging. Using plasma proteomics profiling, we aimed to identify circulating biomarkers and dysregulated signaling pathways specific to HCM. METHODS: In this multicenter case-control study, plasma proteomics profiling was performed in cases with HCM and controls with hypertensive LVH, transthyretin amyloid cardiomyopathy, and aortic stenosis. Two-thirds of patients enrolled earlier in each disease group were defined as the training set and the remaining one-third as the test set. Protein concentrations in HCM were compared with those in hypertensive LVH (comparison 1), transthyretin amyloid cardiomyopathy (comparison 2), and aortic stenosis (comparison 3). Candidate proteins that meet the following 2 criteria were selected: (1) higher abundance in HCM throughout all 3 comparisons or lower abundance in HCM throughout all 3 comparisons with univariable P <0.05 and |log 2 (fold change)| >0.5 in both the training and test sets and (2) independently associated with HCM with multivariable P <0.05 after adjusting for clinical parameters significantly different between HCM and controls. Using the selected candidate proteins, a logistic regression model to distinguish HCM from controls was developed in the training set and applied to the test set. Finally, pathway analysis was performed in each comparison using proteins with different abundance. RESULTS: Overall, 4979 proteins in 1415 patients (HCM, n=879; hypertensive LVH, n=331; transthyretin amyloid cardiomyopathy, n=169; aortic stenosis, n=36) were analyzed. Of those, 5 proteins were selected as candidate proteins. The logistic regression model with these 5 proteins had an area under the receiver operating characteristic curve of 0.86 (95% CI, 0.82–0.89) in the test set. The MAPK (mitogen-activated protein kinase) and HIF-1 (hypoxia-inducible factor 1) pathways were dysregulated in HCM throughout the 3 comparisons. CONCLUSIONS: This study identified circulating biomarkers that distinguish HCM from other cardiomyopathies with LVH independently from confounders and revealed signaling pathways associated with HCM.
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Akita et al. (2024) conducted a case-control in Hypertrophic cardiomyopathy and other cardiomyopathies with left ventricular hypertrophy (n=1,415). Plasma proteomics profiling (5-protein panel) vs. Controls with hypertensive LVH, transthyretin amyloid cardiomyopathy, and aortic stenosis was evaluated on Distinguishing HCM from controls (Area under the receiver operating characteristic curve) (AUC 0.86, 95% CI 0.82-0.89). A 5-protein logistic regression model distinguished hypertrophic cardiomyopathy from other cardiomyopathies with left ventricular hypertrophy with an AUC of 0.86 (95% CI, 0.82-0.89).
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