Sphingolipids in mitochondria-from function to disease

Sphingolipids are not only structural components of cellular membranes but also play vital roles in cell signaling and modulation of cellular processes. Within mitochondria, sphingolipids exert diverse effects on mitochondrial dynamics, energy metabolism, oxidative stress, and cell death pathways. In this review, we summarize literature addressing the crucial role of sphingolipids in mitochondria, highlighting their impact on mitochondrial dynamics, cellular bioenergetics, and important cell processes including apoptosis and mitophagy.

Sphingolipids in the Heart: From Cradle to Grave

Cardiovascular diseases are the leading cause of mortality worldwide and this has largely been driven by the increase in metabolic disease in recent decades. Metabolic disease alters metabolism, distribution, and profiles of sphingolipids in multiple organs and tissues; as such, sphingolipid metabolism and signaling have been vigorously studied as contributors to metabolic pathophysiology in various pathological outcomes of obesity, including cardiovascular disease. Much experimental evidence suggests that targeting sphingolipid metabolism may be advantageous in the context of cardiometabolic disease. The heart, however, is a structurally and functionally complex organ where bioactive sphingolipids have been shown not only to mediate pathological processes, but also to contribute to essential functions in cardiogenesis and cardiac function. Additionally, some sphingolipids are protective in the context of ischemia/reperfusion injury. In addition to mechanistic contributions, untargeted lipidomics approaches used in recent years have identified some specific circulating sphingolipids as novel biomarkers in the context of cardiovascular disease. In this review, we summarize recent literature on both deleterious and beneficial contributions of sphingolipids to cardiogenesis and myocardial function as well as recent identification of novel sphingolipid biomarkers for cardiovascular disease risk prediction and diagnosis.