Identification of metabolites reproducibly associated with Parkinson’s Disease via meta-analysis and computational modelling

Fleming, Ronan M. T.; Luo, Xi; Liu, Yanjun; Balck, Alexander; Klein, Christine

doi:10.21203/rs.3.rs-3209421/v1

Cited by 2 publications

References 153 publications

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Omics data integration suggests a potential idiopathic Parkinson’s disease signature

Zagare,

Preciat,

Nickels

et al. 2023

Commun Biol

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The vast majority of Parkinson’s disease cases are idiopathic. Unclear etiology and multifactorial nature complicate the comprehension of disease pathogenesis. Identification of early transcriptomic and metabolic alterations consistent across different idiopathic Parkinson’s disease (IPD) patients might reveal the potential basis of increased dopaminergic neuron vulnerability and primary disease mechanisms. In this study, we combine systems biology and data integration approaches to identify differences in transcriptomic and metabolic signatures between IPD patient and healthy individual-derived midbrain neural precursor cells. Characterization of gene expression and metabolic modeling reveal pyruvate, several amino acid and lipid metabolism as the most dysregulated metabolic pathways in IPD neural precursors. Furthermore, we show that IPD neural precursors endure mitochondrial metabolism impairment and a reduced total NAD pool. Accordingly, we show that treatment with NAD precursors increases ATP yield hence demonstrating a potential to rescue early IPD-associated metabolic changes.

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Omics data integration suggests a potential idiopathic Parkinson’s disease signature

Zagare,

Preciat,

Nickels

et al. 2023

Commun Biol

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The role of dopaminergic medication, lipid, and endocannabinoid pathway alterations in idiopathic andPRKN/PINK1-mediated Parkinson’s disease – a large-scale targeted metabolomics study

Balck,

Borsche,

Campbell

et al. 2024

Preprint

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Alterations in many metabolites and biochemical pathways have been described in Parkinson’s Disease (PD). However, only a small fraction of these have been replicated in independent studies. As almost every PD patient is treated with dopaminergic medication, it is challenging to discriminate between disease- and drug-related effects, especially in relation to dopamine metabolism. We conducted a large-scale metabolomic study in plasma from 140 idiopathic (IPD), 19PRKN/PINK1-linked PD patients, and 64 healthy controls to disentangle disease-related metabolite alterations from drug-related effects. We distinguished between L-Dopa and non-L-Dopa treated PD patients to uncover nuanced metabolic changes associated with different therapies. We demonstrate that L-Dopa treatment uniquely influences the metabolome, with methyldopa and methoxytyramine, both L-Dopa breakdown products, elevated in L-Dopa-treated IPD andPRKN/PINK-linked PD patients. These alterations were not seen in untreated IPD patients and those on agonist treatment only. Polyamine metabolism alterations, notably elevation of putrescine and ornithine, were partly caused by L-Dopa treatment but also found in non-L-Dopa treated PD patients. In non-L-Dopa-treated patients, endocannabinoid metabolites were lowered and associated with disease duration. We observed lipid metabolism alterations, highlighting potential crosslinks with alpha-synuclein and providing insights into pathophysiological mechanisms. AllPRKN/PINK1-linked PD patients received L-Dopa treatment. However, our data potentially support the well-established role of oxidative damage in these subtypes of PD. In conclusion, our study emphasizes the significant impact of L-Dopa treatment on the metabolome, which might be of relevance not only for metabolomics studies but also for PD biomarker research in general. Finally, our study highlights potential biomarkers and pathways crucial for the understanding disease mechanisms of PD.

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Identification of metabolites reproducibly associated with Parkinson’s Disease via meta-analysis and computational modelling

Cited by 2 publications

References 153 publications

Omics data integration suggests a potential idiopathic Parkinson’s disease signature

Omics data integration suggests a potential idiopathic Parkinson’s disease signature

The role of dopaminergic medication, lipid, and endocannabinoid pathway alterations in idiopathic andPRKN/PINK1-mediated Parkinson’s disease – a large-scale targeted metabolomics study

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