Comprehensive plasma metabolomics profiling develops diagnostic biomarkers of obstructive hypertrophic cardiomyopathy - Hao Cui; Yifan Wang; Xiumeng Hua; Jing Han; Han Mo; Shun Liu; Hongmei Wang; Siyuan Huang; Yiqi Zhao; Xiao Chen; Qian Zhao; Hao Jia; et al. (Biomarker Research)
Abstract Hypertrophic cardiomyopathy (HCM) is the common cause of sudden cardiac death in young people and is characterized by cardiac hypertrophy. Non-HCM caused left ventricular hypertrophy (LVH) is more common in the population, especially in people with hypertension, obesity, and diabetes. In order to identify high-risk populations, a screening technique that can rapidly differentiate between HCM and LVH patients should be developed. Plasma metabolomics may help develop useful biomarkers for the disease diagnosis. We performed a comprehensive plasma metabolomic analysis on a total of 720 individuals, included 441 HCM patients, 160 LVH patients, and 119 normal controls (NC) (derivation cohort = 368, validation cohort = 352). Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to construct discriminant models based on metabolomics, and the result showed significant changes in plasma metabolic profiling among the HCM, LVH, and NC. The prospective diagnostic biomarkers for HCM patients have been examined using variable importance in projection, fold change, and FDR. Acylcarnitines efficiently distinguished HCM and LVH patients, with a C14:0-carnitine AUC of 0.937 shown by the reiver operator characteristic (ROC) curve analysis. The biomarkers for the diagnosis of HCM patients was verified in another independent validation cohort. This study is the largest plasma metabolomics analysis of Chinese Han patients with HCM, finding biomarkers that can be used to distinguish between HCM from LVH patients. These results highlight the great potential value of plasma metabolic profiling analysis on HCM diagnoses.