Introduction: Hypertrophic cardiomyopathy (HCM) is the most common genetic cardiomyopathy. It is sometimes challenging to distinguish HCM from other cardiomyopathies that cause left ventricular hypertrophy (LVH) such as hypertensive LVH, transthyretin cardiac amyloidosis (ATTR-CA), and aortic stenosis (AS). We aimed to identify a set of plasma protein biomarkers that distinguishes HCM from the other cardiomyopathies with LVH. Methods: In this multi-center case-control study, we conducted plasma proteomics profiling of 4,979 proteins in cases with HCM (n=879) and controls with hypertensive LVH (n=331), ATTR-CA (n=169), and AS (n=36). We identified clinical parameters that were significantly (univariable P&lt;0.05) different between HCM and hypertensive LVH. We then specified proteins that were significantly (multivariable P&lt;0.001) upregulated or downregulated in HCM compared to hypertensive LVH by performing multivariable logistic regression analysis on each protein adjusting for the identified clinical parameters (comparison #1). We performed the same analysis between HCM and ATTR-CA (comparison #2) as well as between HCM and AS (comparison #3). We identified proteins that were upregulated in HCM in all 3 comparisons. We also specified proteins downregulated in HCM throughout all 3 comparisons. Finally, using these proteins, we constructed a logistic regression model to distinguish HCM from all 3 control groups combined, and calculated an area under the receiver-operating-characteristics curve (AUROC). Results: Eight clinical parameters listed in Image 1 were significantly different between HCM and the controls and adjusted for in the multivariable logistic regression analyses. In the comparison between HCM and hypertensive LVH, 444 proteins were upregulated and 267 downregulated with multivariable P&lt;0.001 ( Image 1 ). There were 226 upregulated and 170 downregulated proteins comparing HCM with ATTR-CA, and 57 upregulated and 74 downregulated proteins when comparing HCM with AS ( Image 1 ). Among these proteins, 4 were upregulated in all 3 comparisons with multivariable P&lt;0.001 and 5 were downregulated ( Image 2 ). The logistic regression model with these 9 proteins had AUROC of 0.86 (95% confidence interval 0.84-0.88, Image 3 ). Conclusions: This study serves as the first to apply comprehensive proteomics profiling to identify circulating biomarkers that distinguish HCM from other cardiomyopathies with LVH independently from potential confounders.

Abstract 4121733: Comprehensive Plasma Proteomics Profiling Identifies Circulating Biomarkers to Distinguish Hypertrophic Cardiomyopathy from Other Cardiomyopathies with Left Ventricular Hypertrophy