Brain-wide transcriptome-based metabolic alterations in Parkinson's disease: human inter-region and human-experimental model correlations

Odongo, Regan; Bellur, Orhan; Abdik, Ecehan; Çakır, Tunahan

doi:10.1039/d2mo00343k

Mol. Omics

2023

DOI: 10.1039/d2mo00343k

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Brain-wide transcriptome-based metabolic alterations in Parkinson's disease: human inter-region and human-experimental model correlations

Regan Odongo

Orhan Bellur

Ecehan Abdik

et al.

Abstract: Alterations in brain metabolism are closely associated with the molecular hallmarks of Parkinson’s disease (PD). A clear understanding of the main metabolic perturbations in PD is therefore important. Here, we...

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2024

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Transcriptome-based biomarker prediction for Parkinson’s disease using genome-scale metabolic modeling

Abdik,

Çakır

2024

Sci Rep

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Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. Identification of PD biomarkers is crucial for early diagnosis and to develop target-based therapeutic agents. Integrative analysis of genome-scale metabolic models (GEMs) and omics data provides a computational approach for the prediction of metabolite biomarkers. Here, we applied the TIMBR (Transcriptionally Inferred Metabolic Biomarker Response) algorithm and two modified versions of TIMBR to investigate potential metabolite biomarkers for PD. To this end, we mapped thirteen post-mortem PD transcriptome datasets from the substantia nigra region onto Human-GEM. We considered a metabolite as a candidate biomarker if its production was predicted to be more efficient by a TIMBR-family algorithm in control or PD case for the majority of the datasets. Different metrics based on well-known PD-related metabolite alterations, PD-associated pathways, and a list of 25 high-confidence PD metabolite biomarkers compiled from the literature were used to compare the prediction performance of the three algorithms tested. The modified algorithm with the highest prediction power based on the metrics was called TAMBOOR, TrAnscriptome-based Metabolite Biomarkers by On–Off Reactions, which was introduced for the first time in this study. TAMBOOR performed better in terms of capturing well-known pathway alterations and metabolite secretion changes in PD. Therefore, our tool has a strong potential to be used for the prediction of novel diagnostic biomarkers for human diseases.

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Transcriptome-based biomarker prediction for Parkinson’s disease using genome-scale metabolic modeling

Abdik,

Çakır

2024

Sci Rep

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Brain-wide transcriptome-based metabolic alterations in Parkinson's disease: human inter-region and human-experimental model correlations

Abstract: Alterations in brain metabolism are closely associated with the molecular hallmarks of Parkinson’s disease (PD). A clear understanding of the main metabolic perturbations in PD is therefore important. Here, we...

Cited by 1 publication

References 73 publications

Transcriptome-based biomarker prediction for Parkinson’s disease using genome-scale metabolic modeling

Transcriptome-based biomarker prediction for Parkinson’s disease using genome-scale metabolic modeling

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