Three plasma metabolites in elderly patients differentiate mild cognitive impairment and Alzheimer’s disease: a pilot study

Costa, Alana C.; Joaquim, Helena Passarelli Giroud; Forlenza, Orestes Vicente; Gattaz, Wagner F.; Talib, Leda Leme

doi:10.1007/s00406-019-01034-9

Cited by 10 publications

(14 citation statements)

References 39 publications

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“…Recently, more metabolomic research has been applied to the search for AD biomarkers, with promising results [ 70 ]; the goal is to establish prognostic indicators and better elucidate some of the biological mechanisms that underlie disease progression. This information could, in turn, result in future treatments that minimize neuronal damage.…”

Section: Metabolites In Specific Neurological Diseasesmentioning

confidence: 99%

“…Although still preliminary, this type of study is very promising because it may improve early AD diagnosis accuracy, leading to better chances of implementing disease-modifying therapies in the future [ 63 ]. In this way, a recent study proposed that it is possible to distinguish AD patients, MCI patients, and healthy individuals by the differences in metabolites in plasma to perform a targeted quantitative and qualitative controlled assay [ 70 ]. They detected lower plasma levels of acylcarnitine, phosphatidylcholine (PC), and sphingomyelin in AD and MCI patients compared with healthy individuals.…”

Section: Metabolites In Specific Neurological Diseasesmentioning

confidence: 99%

“…They detected lower plasma levels of acylcarnitine, phosphatidylcholine (PC), and sphingomyelin in AD and MCI patients compared with healthy individuals. In addition, AD and MCI patients showed differences in lysophospholipid concentrations, with higher levels in AD patients and lower levels in MCI patients [ 70 ]. Furthermore, the authors proposed dodecanedioylcarnitine, dodecanoylcarnitine, and one phosphatidylcholine with a long chain and no unsaturation (PCaaC26:0) as three potential metabolites that might distinguish among AD patients, MCI patients, and healthy people.…”

Section: Metabolites In Specific Neurological Diseasesmentioning

confidence: 99%

“…Furthermore, the authors proposed dodecanedioylcarnitine, dodecanoylcarnitine, and one phosphatidylcholine with a long chain and no unsaturation (PCaaC26:0) as three potential metabolites that might distinguish among AD patients, MCI patients, and healthy people. This phenomenon may be associated with a dysregulated cascade of acetyl-CoA production and release, interfering with neuron integrity [ 70 ].…”

Section: Metabolites In Specific Neurological Diseasesmentioning

confidence: 99%

“…Many studies have already demonstrated the importance of some phospholipids such as lysophosphatidylethanolamine and sphingomyelin to assess the degree of neuronal damage and changes in the myelin sheath potential predictors of the stage of diseases such as AD, PD, and MuS [ 70 , 109 , 111 ]. In addition, it is also possible to observe the involvement of harmful oxidative processes, with the potential to affect membranes, as has already been proposed for Lysophosphatidic acid C18: 2 in patients with AD [ 71 ].…”

Section: Metabolites In Specific Neurological Diseasesmentioning

confidence: 99%

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Circulating Metabolites as Potential Biomarkers for Neurological Disorders—Metabolites in Neurological Disorders

et al. 2020

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There are, still, limitations to predicting the occurrence and prognosis of neurological disorders. Biomarkers are molecules that can change in different conditions, a feature that makes them potential tools to improve the diagnosis of disease, establish a prognosis, and monitor treatments. Metabolites can be used as biomarkers, and are small molecules derived from the metabolic process found in different biological media, such as tissue samples, cells, or biofluids. They can be identified using various strategies, targeted or untargeted experiments, and by different techniques, such as high-performance liquid chromatography, mass spectrometry, or nuclear magnetic resonance. In this review, we aim to discuss the current knowledge about metabolites as biomarkers for neurological disorders. We will present recent developments that show the need and the feasibility of identifying such biomarkers in different neurological disorders, as well as discuss relevant research findings in the field of metabolomics that are helping to unravel the mechanisms underlying neurological disorders. Although several relevant results have been reported in metabolomic studies in patients with neurological diseases, there is still a long way to go for the clinical use of metabolites as potential biomarkers in these disorders, and more research in the field is needed.

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Section: Metabolites In Specific Neurological Diseasesmentioning

confidence: 99%

Section: Metabolites In Specific Neurological Diseasesmentioning

confidence: 99%

Section: Metabolites In Specific Neurological Diseasesmentioning

confidence: 99%

Section: Metabolites In Specific Neurological Diseasesmentioning

confidence: 99%

Section: Metabolites In Specific Neurological Diseasesmentioning

confidence: 99%

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Circulating Metabolites as Potential Biomarkers for Neurological Disorders—Metabolites in Neurological Disorders

et al. 2020

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Integrative metabolomics‐genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease

Horgusluoglu

Neff

Song

et al. 2021

Alzheimer's & Dementia

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Metabolites, the biochemical products of the cellular process, can be used to measure alterations in biochemical pathways related to the pathogenesis of Alzheimer's disease (AD). However, the relationships between systemic abnormalities in metabolism and the pathogenesis of AD are poorly understood. In this study, we aim to identify ADspecific metabolomic changes and their potential upstream genetic and transcriptional regulators through an integrative systems biology framework for analyzing genetic, transcriptomic, metabolomic, and proteomic data in AD. Metabolite co-expression network analysis of the blood metabolomic data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) shows short-chain acylcarnitines/amino acids andThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia

Winchester,

Harshfield,

Shi

et al. 2023

Alzheimer's & Dementia

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With the increase in large multimodal cohorts and high‐throughput technologies, the potential for discovering novel biomarkers is no longer limited by data set size. Artificial intelligence (AI) and machine learning approaches have been developed to detect novel biomarkers and interactions in complex data sets. We discuss exemplar uses and evaluate current applications and limitations of AI to discover novel biomarkers. Remaining challenges include a lack of diversity in the data sets available, the sheer complexity of investigating interactions, the invasiveness and cost of some biomarkers, and poor reporting in some studies. Overcoming these challenges will involve collecting data from underrepresented populations, developing more powerful AI approaches, validating the use of noninvasive biomarkers, and adhering to reporting guidelines. By harnessing rich multimodal data through AI approaches and international collaborative innovation, we are well positioned to identify clinically useful biomarkers that are accurate, generalizable, unbiased, and acceptable in clinical practice.Highlights Artificial intelligence and machine learning approaches may accelerate dementia biomarker discovery. Remaining challenges include data set suitability due to size and bias in cohort selection. Multimodal data, diverse data sets, improved machine learning approaches, real‐world validation, and interdisciplinary collaboration are required.

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Three plasma metabolites in elderly patients differentiate mild cognitive impairment and Alzheimer’s disease: a pilot study

Cited by 10 publications

References 39 publications

Circulating Metabolites as Potential Biomarkers for Neurological Disorders—Metabolites in Neurological Disorders

Circulating Metabolites as Potential Biomarkers for Neurological Disorders—Metabolites in Neurological Disorders

Integrative metabolomics‐genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease

Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia

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