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Investigation of Volatile Metabolites in Sebum as Prodromal Indicators of Parkinson’s Disease

Authors :
Caitlin Walton-Doyle
Beatrice Heim
Eleanor Sinclair
Katherine A Hollywood
Joy Milne
Evi Holzknecht
Ambra Stefani
Birgit Högl
Klaus Seppi
Monty Silverdale
Werner Poewe
Perdita Barran
Drupad K Trivedi
Publication Year :
2023
Publisher :
Cold Spring Harbor Laboratory, 2023.

Abstract

BackgroundParkinson’s Disease (PD) has been associated with a distinct odour, strongest in sebum-rich areas. Thermal Desorption – Gas Chromatography – Mass Spectrometry (TD-GC-MS) has revealed volatile signatures that distinguish individuals with Parkinson’s Disease (PD) from healthy controls. Here, we applied the same method, including subjects with isolated REM sleep behaviour disorder (iRBD) to examine the volatiles in sebum and compare this with that found in PD subjects and control participants. Participants with iRBD have a high likelihood for conversion to overt clinical synucleinopathies like PD, Dementia with Lewy Bodies (DLB) or (less commonly) Multiple System Atrophy (MSA).MethodsSubjects with clinically established PD (n=16) or iRBD (n=9) as well as healthy controls (n=9) were included. Following methods established in our laboratory, sebum was sampled from each participant using cotton gauze and the headspace from these swabs, analysed directly with TD-GC-MS1,2. Univariate and multivariate analysis was employed to probe the differences between volatile metabolites found for each phenotype. Putative identifications were assigned using spectral matching against the Golm metabolome and NIST spectral databases.FindingsWe can completely classify each phenotype using the sampled volatilome from which we built models with logistic regression analysis. The classification between PD and control improved on previously published work, from 85% to 100%. Putatively annotated molecules include alkanes, aldehydes, fatty acid methyl esters (FAMEs), and three metabolites namely purine, tropinone and oleamide. Investigation of highly ranked features revealed 18 features that showed intermediate expression in samples from iRBD participants.InterpretationTD-GC-MS can differentiate volatile metabolite signatures from sebum between PD, RDB and control samples. More than 70% of the identifiable metabolites that permit this discrimination were putatively annotated as hydrocarbons and fatty acid methyl esters (FAMEs). Our prior work indicates that these components arise from larger lipid molecules that decompose during the experiment2. Features putatively annotated as tropinone, oleamide and purine, have previously been linked with neuroprotection, sleep induction and antioxidation, respectively, are significantly different between the three groups of participants, along with FAMEs and hydrocarbons.FundingWe thank Michael J Fox Foundation (grant ref:12921) and Parkinson’s UK (grant ref: K-1504) for funding this study and Community of Analytical and Measurement Sciences (CAMS) for supporting DT’s research position. This work was supported by the BBSRC (award BB/L015048/1) for instrumentation used in this work and by a DTA to CW-D (project ref. 2113640). We also thank our recruitment centres for their enthusiasm and rigor during the recruitment process. We are very grateful to all the participants who took part in this study as well as PIs and nurses at the recruiting centres.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........fbce32cd424f1172f33f75ad72d2677f
Full Text :
https://doi.org/10.1101/2023.03.01.530578