Untargeted Lipidomic Reveals Potential Biomarkers in Plasma Samples for the Discrimination of Patients Affected by Parkinson's Disease.

Nowadays, the diagnosis of Parkinson's disease (PD) remains essentially clinical, based on the subjective observations of clinicians. In addition, misdiagnosis with other neuro disorders, such as Alzheimer's (AD), can occur. Herein, an untargeted lipidomic analysis of 75 plasma samples was performed to identify lipid species capable of discriminating between these two neuro groups. Therefore, PLS-DA and OPLS-DA analysis revealed significant differences in patient profiles in the sphingolipid and glycerophospholipid categories. As a result, a putative lipid biomarker panel was developed, which included HexCer (40:1; O2) and PC (O-32:0), with an area under the receiver operating characteristic curve (AUC) > 80, respectively. This panel was effective in discriminating between diseased and healthy subjects, but most importantly, it could discriminate between two neurodegenerative disorders that can present similar symptoms, namely PD and AD. Together, these findings suggest that the dysregulated metabolism of lipids plays a critical role in AD and PD pathology and may represent a valuable clinical tool for their diagnosis. Thus, further targeted studies are encouraged to better understand the underlying mechanisms of PD and confirm the diagnostic potency of the identified lipid metabolites.