4.6 Review

Metabolomic Footprint of Disrupted Energetics and Amino Acid Metabolism in Neurodegenerative Diseases: Perspectives for Early Diagnosis and Monitoring of Therapy

Journal

METABOLITES
Volume 13, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/metabo13030369

Keywords

biomarker; neurodegeneration; energy metabolism; Alzheimer's disease; Parkinson's disease; Huntington's disease

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The prevalence of neurodegenerative diseases (NDs) is increasing due to demographic changes. This review explores the alterations in brain metabolism in Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD). Based on the findings, potential metabolic indicators or predictors of the diseases are proposed. Challenges and future directions of metabolomics studies in NDs are discussed. The integration of metabolomics with other omic techniques may be necessary to achieve clinically applicable results.
The prevalence of neurodegenerative diseases (NDs) is increasing due to the aging population and improved longevity. They are characterized by a range of pathological hallmarks, including protein aggregation, mitochondrial dysfunction, and oxidative stress. The aim of this review is to summarize the alterations in brain energy and amino acid metabolism in Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD). Based on our findings, we proposed a group of selected metabolites related to disturbed energy or mitochondrial metabolism as potential indicators or predictors of disease. We also discussed the hidden challenges of metabolomics studies in NDs and proposed future directions in this field. We concluded that biochemical parameters of brain energy metabolism disruption (obtained with metabolomics) may have potential application as a diagnostic tool for the diagnosis, prediction, and monitoring of the effectiveness of therapies for NDs. However, more studies are needed to determine the sensitivity of the proposed candidates. We suggested that the most valuable biomarkers for NDs studies could be groups of metabolites combined with other neuroimaging or molecular techniques. To attain clinically applicable results, the integration of metabolomics with other omic techniques might be required.

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