Neurolipidomics

Neurolipidomics is a subfield of lipidomics and neuroscience that studies the composition, metabolism, and function of lipids in the nervous system. It aims to characterize lipid species in brain tissue, cerebrospinal fluid, and other CNS-relevant samples, and to understand how lipid networks influence neural development, signaling, and pathology.

Core methods combine mass spectrometry–based lipidomics with separation techniques, including LC-MS/MS and shotgun lipidomics, as well as imaging mass spectrometry approaches such as MALDI-MSI for spatially resolved lipid profiling. These analyses are supported by bioinformatics, lipid databases, and pathway analysis to identify lipid species, quantify changes, and interpret their biological context. Spatially resolved and single-cell approaches are increasingly used to capture regional and cellular heterogeneity in the brain.

Applications of neurolipidomics include elucidating the roles of glycerophospholipids, sphingolipids, cholesterol derivatives, and ether lipids in membrane structure, vesicle trafficking, myelination, and synaptic function. The field contributes to understanding aging and neurological diseases, such as Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and traumatic brain injury, where lipid alterations may serve as biomarkers or therapeutic targets.

Challenges include the brain’s lipid complexity and heterogeneity, isomeric species, sample preservation, and cross-platform reproducibility. Advances in imaging, spatial and single-cell lipidomics, and standardized data workflows are expected to improve biological interpretation and support translational applications in diagnosis and treatment.