Metabolomic breath landscape analysis unravels lipid biomarker candidates in patients with genetic and idiopathic Parkinson’s disease
Madiha Malik, Norbert Brüggemann, Tatiana Usnich, Max Borsche, Tobias Demetrowitsch, Björn-Hergen Laabs, Karin Schwarz, Peter Bauer, Katja Lohmann, Christine Klein, Thomas Kunze

TL;DR
This study uses breath analysis to identify lipid biomarkers in Parkinson's disease patients, offering a non-invasive way to detect the condition.
Contribution
The study introduces a novel untargeted metabolomics approach using exhaled breath to identify lipid biomarkers in Parkinson's disease.
Findings
Breath analysis identified seven significant metabolites in PD patients, including fatty acid intermediates.
Five of these metabolites were also found in unaffected carriers of PD-related genetic variants.
Breath profiling can distinguish PD patients from healthy controls with high accuracy.
Abstract
Parkinson’s disease (PD) is the fastest growing neurodegenerative disorder. The current lack of efficient early diagnostic tools necessitates novel approaches to biomarker discovery. We propose an untargeted metabolomics approach using non-invasive exhaled breath analysis. Breath samples, collected from 73 PD patients, encompassing both genetic (LRRK2: n = 12, GBA1: n = 35, PRKN: n = 6) and idiopathic PD (n = 20), 4 unaffected LRRK2 pathogenic variant carriers, and 90 controls underwent extreme-resolution FT-ICR-MS analysis. Findings were compared with metabolomics data from blood plasma. Biostatistical analyses identified discernible metabolic patterns in both biofluids, enabling differentiation of PD patients from healthy controls (OOB error < 1%). Metabolomic breath profiling of PD patients yielded 7 significant metabolites putatively identified as tricosanoic acid, docosanamide,…
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Taxonomy
TopicsAdvanced Chemical Sensor Technologies · Metabolomics and Mass Spectrometry Studies · Biochemical Analysis and Sensing Techniques
