Abstract
Progression of Parkinson’s disease (PD) is highly variable, indicating that differences between slow and rapid progression forms could provide valuable information for improved early detection and management. Unfortunately, this represents a complex problem due to the heterogeneous nature of humans in regards to demographic characteristics, genetics, diet, environmental exposures and health behaviors. In this pilot study, we employed high resolution mass spectrometry-based metabolic profiling to investigate the metabolic signatures of slow versus rapidly progressing PD present in human serum. Archival serum samples from PD patients obtained within 3 years of disease onset were analyzed via dual chromatography-high resolution mass spectrometry, with data extraction by xMSanalyzer and used to predict rapid or slow motor progression of these patients during follow-up. Statistical analyses, such as false discovery rate analysis and partial least squares discriminant analysis, yielded a list of statistically significant metabolic features and further investigation revealed potential biomarkers. In particular, N8-acetyl spermidine was found to be significantly elevated in the rapid progressors compared to both control subjects and slow progressors. Our exploratory data indicate that a fast motor progression disease phenotype can be distinguished early in disease using high resolution mass spectrometry-based metabolic profiling and that altered polyamine metabolism may be a predictive marker of rapidly progressing PD.
Highlights
Parkinson’s disease (PD) is a complex, multisystem disorder of unknown etiology that presents a broad array of symptoms and pathological features affecting organs throughout the body [1]
PD patients were divided into two motor progression subgroups determined by the average annual increase in Unified Parkinson’s Disease Rating Scale (UPDRS) motor score
A five-point per year change in the motor UPDRS has been reported for early, untreated PD patients in placebo arms of clinical trials [22] and is considered a clinically relevant change when assessing improvement due to treatment [23]; our “rapid” progressors on average experienced an annual rate in motor symptom decline of 5.95 points, while the slow progressors mean change in symptoms was only 1.45 points
Summary
Parkinson’s disease (PD) is a complex, multisystem disorder of unknown etiology that presents a broad array of symptoms and pathological features affecting organs throughout the body [1]. The heterogeneity of PD symptoms suggests that different disease subgroups exist and that these subgroups may possess distinct etiological processes [4] Due to this heterogeneous nature, the quest for reliable biomarkers that can predict disease onset, progression and/or outcome is ongoing. Biochemical biomarkers that reflect PD pathogenesis are greatly needed due to the fact that degeneration of the dopamine producing neurons is an irreversible process; biomarkers may aid in early detection and more effective disease management. These biomarkers need to be detectible in accessible samples, such as blood, saliva and cerebral spinal fluid [5]. In an effort to discover viable biomarkers, researchers have begun to employ ‘omics’ approaches in combination with bioinformatics and biostatistical methods to aid in the discovery of these very important biomarkers present in complex biological samples
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