Integrative lipidomics of brain and plasma uncovers sex-specific metabolic signatures in Parkinson's disease
Lipid dysregulation is increasingly recognized as a key feature of Parkinson's disease (PD). A central unresolved question, however, is whether lipidomic signatures identified in accessible peripheral biofluids faithfully recapitulate the pathogenic alterations within the central nervous system (CNS). This gap impedes the development of reliable biomarkers and constrains a comprehensive understanding of PD pathophysiology. To address this challenge, we employed a cross-species lipidomic approach. We modeled PD in both male and female mice by injecting human -synuclein preformed fibrils into the substantia nigra. Three months post-injection, lipidomic profiles of the midbrain and plasma were generated and compared. These findings were further validated in plasma from male and female PD patients and age-matched controls, enabling the identification of conserved alterations. We identified shared dysregulation of sphingolipids, glycerophospholipids, and fatty acids in the brains and plasma of diseased mice as well as in plasma from PD patients. Notably, lipids associated with lipid droplet biogenesis, including triacylglycerols and monoacylglycerols, were elevated in diseased mouse brains and patient plasma. These alterations coincided with a marked accumulation of lipid droplets in the mouse midbrain and were further corroborated by increased lipid droplet abundance in macrophages derived from PD patients. Interestingly, lipid droplet accumulation exhibited sex-specific patterns: male mice displayed greater microglial accumulation, whereas female mice showed enhanced neuronal deposition. Together, these findings demonstrate that peripheral lipidomic signatures reflect CNS pathology in PD, highlighting new opportunities for biomarker discovery and therapeutic intervention. Furthermore, sex-specific lipid droplet accumulation in innate immune cells and neurons implicates these pathways as mechanistic contributors to PD and underscores the necessity of sex-stratified strategies in biomarker discovery and disease modeling.