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A metabolomics profiling approach was conducted to identify diagnostic biomarkers of PD from sebum, a non-invasively available biofluid. In this study, we used liquid chromatography-mass spectrometry (LC-MS) to analyse 274 samples from participants (80 drug naïve PD, 138 medicated PD and 56 well matched control subjects) and detected metabolites that could predict PD phenotype. Partial least squares-discriminant analysis (PLS-DA) models based on this sebum metabolome had correct classification rates of 70.4% and 69.7% to distinguish between drug naïve PD and medicated PD from control, respectively. Variable importance in projection (VIP) scores indicate compounds with significance belonged to sphingolipid, triacylglycerol and fatty acid/ester lipid classes. Pathway enrichment analysis showed alterations in lipid metabolism and mitochondrial dysfunction viz. the carnitine shuttle, sphingolipid metabolism and arachidonic acid metabolism. This study unveiled novel diagnostic sebum-based biomarkers for PD, and provides insight towards our current understanding of the pathogenesis of PD.

Parkinson’s disease (PD) is the second most common neurodegenerative disorder for which identification of robust biomarkers to complement clinical PD diagnosis would accelerate treatment options and help to stratify disease progression. Here we demonstrate the use of paper spray ionisation coupled with ion mobility mass spectrometry (PSI IM-MS) to determine diagnostic molecular features of PD in sebum. PSI IM-MS was performed directly from skin swabs, collected from 34 people with PD and 30 matched control subjects as a training set and a further 91 samples from 5 different collection sites as a validation set. PSI IM-MS elucidates ~ 4200 features from each individual and we report two classes of lipids (namely phosphatidylcholine and cardiolipin) that differ significantly in the sebum of people with PD. Putative metabolite annotations are obtained using tandem mass spectrometry experiments combined with accurate mass measurements. Sample preparation and PSI IM-MS analysis and diagnosis can be performed ~5 minutes per sample offering a new route to for rapid and inexpensive confirmatory diagnosis of this disease.

A metabolomics profiling approach was conducted to identify diagnostic biomarkers of PD from sebum, a non-invasively available biofluid. In this study, we used liquid chromatography-mass spectrometry (LC-MS) to analyse 274 samples from participants (80 drug naïve PD, 138 medicated PD and 56 well matched control subjects) and detected metabolites that could predict PD phenotype. Partial least squares-discriminant analysis (PLS-DA) models based on this sebum metabolome had correct classification rates of 70.4% and 69.7% to distinguish between drug naïve PD and medicated PD from control, respectively. Variable importance in projection (VIP) scores indicate compounds with significance belonged to sphingolipid, triacylglycerol and fatty acid/ester lipid classes. Pathway enrichment analysis showed alterations in lipid metabolism and mitochondrial dysfunction viz. the carnitine shuttle, sphingolipid metabolism and arachidonic acid metabolism. This study unveiled novel diagnostic sebum-based biomarkers for PD, and provides insight towards our current understanding of the pathogenesis of PD.