Targeted fatty acid metabolomics to discover Parkinson's disease associated metabolic alteration

The pathogenesis of Parkinson's disease (PD) remains to be elucidated, and the metabolomics analysis has the potential to identify metabolic profiles that are involved in PD pathogenesis. Here we applied a target metabolomics approach to measure the plasma levels of 158 fatty acid metabolites in a discovery cohort including 42 PD patients and 54 health volunteers, and found two upregulated (arachidonic acid and 13-hydroxy-octadecatrienoic acid) and eleven down-regulated (docosahexaenoic acid, lyso-platelet-activating factor, 12-hydroxy-eicosatetraenoic acid, dihydroxy-eicosatrienoic acids, dihidroxy-octadecenoic acids, 17,18-dihydroxy-eicosatetraenoic acid, and hydroperoxy-octadecadienoic acids) metabolites as primary candidate marker of PD. A support vector machine algorithm with primary candidate marker was used in an independent validation cohort to identify PD. Arachidonic acid and 13-hydroxy-octadecatrienoic acid were evaluated as an effective tool in that area under the receiver operating characteristic curve reached 0.995 and 0.912 in the validation set for diagnosing PD from healthy volunteers. Besides, the sensitivity and specificity of arachidonic acid as diagnostic factor of PD in validation set were 100% and 94.10%. Similarly, the sensitivity and specificity of 13-hydroxy-octadecatrienoic acid were 100% and 82.40% for identifying PD. This target fatty acid metabolomics demonstrated a series of plasma fatty acid metabolite as PD candidate marker with high efficiency and provided insights into the understanding of PD metabolic regulation.