Hypertrophic cardiomyopathy (HCM) is a common inherited cardiovascular disease with heterogeneous clinical presentations, governed by multiple molecular mechanisms. Metabolic perturbations underlie most cardiovascular diseases; however, the metabolic alterations and their function in HCM are unknown. Here, we describe the metabolome and lipidome of heart and plasma samples from individuals with and without HCM. Correlation analyses showed strong association between metabolic alterations and cardiac function and prognosis of patients with HCM. Using machine learning we identified metabolite panels as potential HCM diagnostic markers or predictors of survival. Clustering based on metabolome and lipidome of heart enabled stratification of patients with HCM into three subgroups with distinct cardiac function and survival. Integration of metabolomics and proteomics data identified metabolic pathways significantly altered in patients with HCM, with the pentose phosphate pathway and oxidative stress being particularly upregulated. Thus, targeting the pentose phosphate pathway and oxidative stress may serve as potential therapeutic strategies for HCM. Wang et al. analyze the metabolome and lipidome of heart and plasma samples from patients with HCM and healthy individuals and identify panels of metabolites that can be used as diagnostic biomarkers of HCM or predictors of HCM patient survival; patients are stratified into three groups with distinct cardiac function and survival and identify metabolic pathways that are greatly affected in patients with HCM, suggesting that targeting the pentose phosphate pathway and oxidative stress may represent effective ways to treat HCM.