Discovery and Validation of Biomarkers of Parkinson's Disease Using xC-MS

Abstract

Parkinson's Disease (PD) is a neurodegenerative disorder, increasing in prevalence. With no robust, chemical diagnostic test, diagnosis relies on hallmark motor and other symptoms to present. These manifestations occur after a long prodromal stage, during which neuronal cell damage is occurring. Joy Milne, a woman with hyperosmia, helped our research team to discover a scent associated with the disease. Anecdotally, this scent is present in early stages of disease. Working with Joy it was found to be strongest in areas rich in sebaceous glands and where sebum accumulates, namely the neckline and mid back. The work following employs different mass spectrometry based analytical platforms (Gas Chromatography - Mass Spectrometry and Liquid Chromatography - Mass Spectrometry) to study metabolite profiles of sebum. For this thesis, and accompanying experiments, we recruited c. 2,000 participants to provide sebum samples, collected by non-invasive swabbing. This thesis contains work that builds on preliminary studies demonstrating the hypothesis that PD has an associated scent that is detectable by changes in sebum. The overarching aim is to characterise sebum and consider its capabilities as a diagnostic biofluid for Parkinson's Disease. The work is arranged in the following chapters: Chapter One: Introduces the field of mass spectrometry based metabolomics and prior work in skin-based analysis. It describes the background to sebum, sebaceous glands, the skin and how these have previously been used to explore disease. Chapter Two: This concerns the design of the studies within the thesis. It describes how we chose and recruited participants from 31 collecting sites. It also provides background methodology as to how large scale -omics experiments are planned and optimised. Chapter Three: Research article that validates different volatile signatures in sebum from people with Parkinson's compared to control (C), using headspace gas chromatography-mass spectrometry. This work exhibited an increased classification rate between PD and control cohorts from our previous experiment. Chapter Four: Research article employing headspace GC-MS to analyse sebum samples from people displaying a prodromal symptom of PD. The volatile profiles of these are compared with PD and C, and putative identifications assigned to features of interest provide possible prodromal and progressive markers of disease. Chapter Five: Research article on the stability of sebum with respect to storage time and storage temperature. Both the volatile compounds and an extracted sebum sample are analysed by xC-MS platforms to investigate the effect of time and temperature on the composition of sebum, and whether alterations seen have ramifications on the viability of sebum to be a diagnostic biofluid of PD. Chapter Six: Research article, which compares sebum and serum samples from identical participants using different chromatographic techniques. Multivariate analysis investigates the ability of biofluids to classify PD from C as well as classification of longitudinal samples taken at time points to probe progressive markers. Further, features of interest are used as a target panel in samples from different sites to investigate the discriminatory power of these metabolites. Chapter Seven: Conclusions of the thesis and plans for future work.

Date of Award	1 Aug 2023
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Richard Grencis (Supervisor), Perdita Barran (Supervisor) & Drupad Trivedi (Supervisor)