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

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 m...

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Autores principales: Zagare, Alise, Preciat, German, Nickels, Sarah. L., Luo, Xi, Monzel, Anna S., Gomez-Giro, Gemma, Robertson, Graham, Jaeger, Christian, Sharif, Jafar, Koseki, Haruhiko, Diederich, Nico J., Glaab, Enrico, Fleming, Ronan M. T., Schwamborn, Jens C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662437/
https://www.ncbi.nlm.nih.gov/pubmed/37985891
http://dx.doi.org/10.1038/s42003-023-05548-w
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author Zagare, Alise
Preciat, German
Nickels, Sarah. L.
Luo, Xi
Monzel, Anna S.
Gomez-Giro, Gemma
Robertson, Graham
Jaeger, Christian
Sharif, Jafar
Koseki, Haruhiko
Diederich, Nico J.
Glaab, Enrico
Fleming, Ronan M. T.
Schwamborn, Jens C.
author_facet Zagare, Alise
Preciat, German
Nickels, Sarah. L.
Luo, Xi
Monzel, Anna S.
Gomez-Giro, Gemma
Robertson, Graham
Jaeger, Christian
Sharif, Jafar
Koseki, Haruhiko
Diederich, Nico J.
Glaab, Enrico
Fleming, Ronan M. T.
Schwamborn, Jens C.
author_sort Zagare, Alise
collection PubMed
description 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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spelling pubmed-106624372023-11-20 Omics data integration suggests a potential idiopathic Parkinson’s disease signature Zagare, Alise Preciat, German Nickels, Sarah. L. Luo, Xi Monzel, Anna S. Gomez-Giro, Gemma Robertson, Graham Jaeger, Christian Sharif, Jafar Koseki, Haruhiko Diederich, Nico J. Glaab, Enrico Fleming, Ronan M. T. Schwamborn, Jens C. Commun Biol Article 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. Nature Publishing Group UK 2023-11-20 /pmc/articles/PMC10662437/ /pubmed/37985891 http://dx.doi.org/10.1038/s42003-023-05548-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Zagare, Alise
Preciat, German
Nickels, Sarah. L.
Luo, Xi
Monzel, Anna S.
Gomez-Giro, Gemma
Robertson, Graham
Jaeger, Christian
Sharif, Jafar
Koseki, Haruhiko
Diederich, Nico J.
Glaab, Enrico
Fleming, Ronan M. T.
Schwamborn, Jens C.
Omics data integration suggests a potential idiopathic Parkinson’s disease signature
title Omics data integration suggests a potential idiopathic Parkinson’s disease signature
title_full Omics data integration suggests a potential idiopathic Parkinson’s disease signature
title_fullStr Omics data integration suggests a potential idiopathic Parkinson’s disease signature
title_full_unstemmed Omics data integration suggests a potential idiopathic Parkinson’s disease signature
title_short Omics data integration suggests a potential idiopathic Parkinson’s disease signature
title_sort omics data integration suggests a potential idiopathic parkinson’s disease signature
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662437/
https://www.ncbi.nlm.nih.gov/pubmed/37985891
http://dx.doi.org/10.1038/s42003-023-05548-w
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