Recent Advances and Applications of Metabolomics to Investigate Neurodegenerative Diseases

Ibáñez, Clara; Cifuentes, Alejandro; Simó, Carolina

doi:10.1016/bs.irn.2015.05.015

Cited by 25 publications

(11 citation statements)

References 105 publications

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“…Differences between metabolic profiles of individuals or groups of healthy or diseased persons can be the result of differences in genetic background, epigenetic modifications, lifestyle, stress, pathogen exposure, diet, medication, gut flora, and so on. The first metabolomic studies in neurodegenerative diseases, including PD and Alzheimer’s disease (AD) have been reviewed by various authors [ 43 , 44 , 45 , 46 ].…”

Section: Metabolomics In Pdmentioning

confidence: 99%

Biomarker Research in Parkinson’s Disease Using Metabolite Profiling

et al. 2017

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Biomarker research in Parkinson’s disease (PD) has long been dominated by measuring dopamine metabolites or alpha-synuclein in cerebrospinal fluid. However, these markers do not allow early detection, precise prognosis or monitoring of disease progression. Moreover, PD is now considered a multifactorial disease, which requires a more precise diagnosis and personalized medication to obtain optimal outcome. In recent years, advanced metabolite profiling of body fluids like serum/plasma, CSF or urine, known as “metabolomics”, has become a powerful and promising tool to identify novel biomarkers or “metabolic fingerprints” characteristic for PD at various stages of disease. In this review, we discuss metabolite profiling in clinical and experimental PD. We briefly review the use of different analytical platforms and methodologies and discuss the obtained results, the involved metabolic pathways, the potential as a biomarker and the significance of understanding the pathophysiology of PD. Many of the studies report alterations in alanine, branched-chain amino acids and fatty acid metabolism, all pointing to mitochondrial dysfunction in PD. Aromatic amino acids (phenylalanine, tyrosine, tryptophan) and purine metabolism (uric acid) are also altered in most metabolite profiling studies in PD.

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Section: Metabolomics In Pdmentioning

confidence: 99%

Biomarker Research in Parkinson’s Disease Using Metabolite Profiling

et al. 2017

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“…However, for direct investigation of body fluids in the earliest stages of neurological diseases, the biomarker field has employed “omics” technologies. These allow unbiased analysis of large ranges of DNA, RNA, proteins or metabolites, and thus allow identification of biomarker leads as well as novel hypotheses through multimodal pathway analysis [ 45 – 48 ]. The currently most powerful proteomics technologies are based on mass spectrometry methods.…”

Section: Gaps In the Current Biomarker Development Processmentioning

confidence: 99%

White paper by the Society for CSF Analysis and Clinical Neurochemistry: Overcoming barriers in biomarker development and clinical translation

et al. 2018

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Body fluid biomarkers have great potential for different clinical purposes, including diagnosis, prognosis, patient stratification and treatment effect monitoring. This is exemplified by current use of several excellent biomarkers, such as the Alzheimer’s disease cerebrospinal fluid (CSF) biomarkers, anti-neuromyelitis optica antibodies and blood neurofilament light. We still, however, have a strong need for additional biomarkers and several gaps in their development and implementation should be filled. Examples of such gaps are i) limited knowledge of the causes of neurological diseases, and thus hypotheses about the best biomarkers to detect subclinical stages of these diseases; ii) the limited success translating discoveries obtained by e.g. initial mass spectrometry proteomic low-throughput studies into immunoassays for widespread clinical implementation; iii) lack of interaction among all stakeholders to optimise and adapt study designs throughout the biomarker development process to medical needs, which may change during the long period needed for biomarker development.The Society for CSF Analysis and Clinical Neurochemistry (established in 2015) has been founded as a concerted follow-up of large standardisation projects, including BIOMARKAPD and SOPHIA, and the BioMS-consortium.The main aims of the CSF society are to exchange high level international scientific experience, to facilitate the incorporation of CSF diagnostics into clinical practice and to give advice on inclusion of CSF analysis into clinical guidelines. The society has a broad scope, as its vision is that the gaps in development and implementation of biomarkers are shared among almost all neurological diseases and thus they can benefit from the activities of the society.

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“…It offers great potential for the diagnosis and prognosis of neurodegenerative diseases by capturing snapshots of the complex and multifactorial biochemical pathways that may be altered in AD [3]. Recent studies have showed that metabolomics can be used to measure alterations in biochemical pathways related to AD [4][5][6][7]. However, one of the key challenges in these metabolomics studies is the inability to ensure whether the relationships between circulating metabolites and AD are causal.…”

Section: Introductionmentioning

confidence: 99%

Investigating Causal Relations Between Circulating Metabolites and Alzheimer’s Diseases: a Mendelian Randomization Study

Huang

Zhang

Kuo

et al. 2021

Preprint

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BackgroundMetabolomics is a promising approach that can be used to understand pathophysiological pathways of Alzheimer disease (AD). However, the relationships between metabolism and AD are poorly understood. The aim of this study is to investigate the causal association between circulating metabolites and risk of AD by combining metabolomics with genomics through two-sample Mendelian randomization (MR) approach. MethodGenetic associations with 123 circulating metabolic traits were utilized as exposures. A large summary statistics data from International Genomics of Alzheimer’s Project was used in primary analysis, including 21,982 AD cases and 41,944 controls. Validation was further performed using family history of AD data from UK Biobank (27,696 cases of maternal AD, 14,338 cases of paternal AD and 272,244 controls). We utilized the inverse-variance weighted method as primary analysis and four additional MR methods (MR-Egger, weighted median, weighted mode, and MR pleiotropy residual sum and outlier) for sensitivity analyses. ResultsWe found one-fold increased risk of developing AD per standard deviation increase in the levels of circulating ApoB (odd ratio (OR)=3.18; 95% confidence interval (CI): 1.52–6.66, P=0.0022) and glycoprotein acetyls (OR=1.21; 95% CI: 1.05–1.39, P=0.0093), serum total cholesterol (OR=2.73; 95% CI: 1.41-5.30, P=0.0030), and low-density lipoprotein (LDL) cholesterol (OR=2.34; 95% CI: 1.53-3.57, P=0.0001). Whereas glutamine (OR=0.81; 95% CI: 0.71-0.92, P=0.0011) were significantly associated with lower risk of AD. We also detected causal effects of several different composition of LDL fractions on increased AD risk, which has been verified in validation. However, we found no association between circulating high-density lipoprotein cholesterol and AD. ConclusionsOur findings provided robust evidence supporting causal effects of circulating glycoprotein acetyls, ApoB, LDL cholesterol, and serum total cholesterol on higher risk of AD, whereas glutamine showed the protective effect. Further research is required to decipher the biological pathways underpinning associations.

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Recent Advances and Applications of Metabolomics to Investigate Neurodegenerative Diseases

Cited by 25 publications

References 105 publications

Biomarker Research in Parkinson’s Disease Using Metabolite Profiling

Biomarker Research in Parkinson’s Disease Using Metabolite Profiling

White paper by the Society for CSF Analysis and Clinical Neurochemistry: Overcoming barriers in biomarker development and clinical translation

Investigating Causal Relations Between Circulating Metabolites and Alzheimer’s Diseases: a Mendelian Randomization Study

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