Cerebrospinal Fluid Metabolome in Parkinson’s Disease and Multiple System Atrophy

Abstract

Parkinson’s disease (PD) and multiple system atrophy (MSA) belong to the neurodegenerative group of synucleinopathies; differential diagnosis between PD and MSA is difficult, especially at early stages, owing to their clinical and biological similarities. Thus, there is a pressing need to identify metabolic biomarkers for these diseases. The metabolic profile of the cerebrospinal fluid (CSF) is reported to be altered in PD and MSA; however, the altered metabolites remain unclear. We created a single network with altered metabolites in PD and MSA based on the literature and assessed biological functions, including metabolic disorders of the nervous system, inflammation, concentration of ATP, and neurological disorder, through bioinformatics methods. Our in-silico prediction-based metabolic networks are consistent with Parkinsonism events. Although metabolomics approaches provide a more quantitative understanding of biochemical events underlying the symptoms of PD and MSA, limitations persist in covering molecules related to neurodegenerative disease pathways. Thus, omics data, such as proteomics and microRNA, help understand the altered metabolomes mechanism. In particular, integrated omics and machine learning approaches will be helpful to elucidate the pathological mechanisms of PD and MSA. This review discusses the altered metabolites between PD and MSA in the CSF and omics approaches to discover diagnostic biomarkers.

Quantitative proteomics and phosphoproteomics of urinary extracellular vesicles define putative diagnostic biosignatures for Parkinson’s disease

“…Through microarray analysis on substantia nigra tissue, heat shock protein HSPA1A and HSPA1B were found to be upregulated in PD, indicating that this may be a common response to attenuate the adverse effects of misfolded protein 112 . ECM1 was also shown to be upregulated in the CSF samples of PD patients 113 . Interestingly, one of the most common genetic risk factors for PD is having a mutated GBA gene 114 .…”

The differential diagnosis value of radiomics-based machine learning in Parkinson’s disease: a systematic review and meta-analysis

“… di Biase et al (2020) review reported an accuracy of over 0.83 for PD diagnosis using ML based on gait feature testing. Kwon et al (2022) review demonstrated that the integration of clinically relevant biomarkers such as metabolomics, proteomics, and microRNA omics data from cerebrospinal fluid can serve as a powerful method for identifying PD and MSA. The aforementioned research results demonstrate that diagnostic models based on different variables have good performance in PD diagnosis.…”

Perspective Strategies for Interventions in Parkinsonism: Remedying the Neglected Role of TPPP

“…In the context of the exploration of candidate biomarkers for MSA, disregarding its close relationship with PD does not seem justifiable. Several recent studies have shown that SYN might be a potential diagnostic biomarker for PD in CSF though the results are inconsistent [57][58][59]. The results of a meta-analysis investigating the diagnostic and differential diagnosis efficacy of CSF SYN in PD have shown that its median concentration is significantly lower in PD compared to controls, but significantly higher in PD as compared to MSA [60,61].…”