Objective: We propose an untargeted metabolomics approach using exhaled breath analysis to (1) characterize the non-volatile metabolomic breath signature of Parkinson’s disease (PD) patients with and without pathogenic variants in PD-linked genes, (2) compare these metabolomic patterns with those of healthy controls and (3) examine metabolomic changes in unaffected individuals carrying pathogenic variants. The goal is to identify potential PD biomarkers.

Background: PD, the fastest-growing neurodegenerative disorder, presents significant challenges in early diagnosis due to the lack of efficient diagnostic tools, highlighting the critical necessity for novel approaches in biomarker discovery. Human breath, as an alternative biomaterial, offers a promising noninvasive strategy for exploring new biomarkers.

Method: Breath samples were collected using a filter-based device and prepared according to established protocols [1]. We included 73 PD patients, with genetic variants (LRRK2: n=12, GBA1: n=35, PRKN: n=6) and idiopathic PD (n=20), 4 unaffected LRRK2-carriers, and 90 randomly selected sex-matched controls without a PD diagnosis. The metabolomics approach utilized extreme resolution FT-ICR-MS combined with biostatistical analyses. Findings were compared with metabolomics data from simultaneously collected blood plasma.

Results: Characterizing the non-volatile breathome of PD patients yielded over 1000 biochemically versatile metabolites. Multivariate analyses and random forest classification accurately differentiated PD patients and controls in both biofluids (OOB error <1%). Metabolomic breath profiling of PD patients and controls via ROC analysis yielded 10 significant hits putatively identified as tetracosanoic acid_, tricosanoic acid, HMVA, docosanamide, eicosanoic acid, nonadecanoic acid, homophytanic acid, MG, stearic acid and palmitic acid in PD patients, irrespective of the genetic status [figure1]. Most of these structures are intermediates in fatty acid metabolism, introducing new hits for breath analysis in PD. Seven of these metabolites were also found in unaffected carriers of pathogenic variants in the LRRK2 gene when compared to controls.

Conclusion: Breath analysis effectively distinguishes between PD patients and healthy controls and nominates metabolites that could serve as noninvasive biomarkers for PD, potentially including its presymptomatic stage.

Top 10 significant metabolites in exhaled breath

References: 1. Malik M, Demetrowitsch T, Schwarz K, Kunze T. New perspectives on ‘Breathomics’: metabolomic profiling of non-volatile organic compounds in exhaled breath using DI-FT-ICR-MS. Commun Biol. 2024 Mar 2;7(1):258. doi: 10.1038/s42003-024-05943-x. PMID: 38431745.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/metabolomic-breath-landscape-analysis-unravels-lipid-biomarker-candidates-in-patients-with-monogenic-and-idiopathic-parkinsons-disease/