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Cells
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Metabolomics and Epigenetics of Neurodegenerative Disease
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Metabolomics and Epigenetics of Neurodegenerative Disease

A special issue of Cells (ISSN 2073-4409). This special issue belongs to the section "Cells of the Nervous System".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 19706

Special Issue Editors

Dr. Stewart Graham

E-Mail Website
Guest Editor
Oakland University William Beaumont School of Medicine, Rochester, MI, USA
Interests: metabolomics; Alzheimer's disease; Parkinson's disease; neurodegenerative disease; etiopathophysiology; NMR spectroscopy; mass spectrometry; chemometrics; biomarkers
Special Issues, Collections and Topics in MDPI journals
Dr. Sangeetha Vishweswaraiah

E-Mail Website
Guest Editor
Oakland University William Beaumont School of Medicine, Rochester, MI, USA
Interests: epigenetics; genetics; GWAS; RNA-Seq; systems biology

Special Issue Information

Dear Colleagues,

“Neurodegenerative disease” is a term which collectively describes a group of diverse disorders characterized by hallmark pathologies such as progressive degeneration of the structure and function of the central and peripheral nervous systems.  One of the major treatment hurdles associated with these group of diseases is that the majority of neurodegeneration has already occurred by the time an accurate, clinical diagnosis can be made.  As such, and while expanding our understanding of both the etiology and pathophysiology of these heterogenous diseases, metabolomics and epigenetics are being increasingly used to develop predictive/diagnostic/prognostic biomarkers to help identify those people at greatest risk of developing one of these diseases earlier.  This Special Issue will include articles related to Alzheimer’s disease and related dementias, Parkinson’s disease, Huntington’s disease, Motor neuron disease, Prion diseases and other related manifestations of neurodegenerative disease. Accepted manuscripts will focus on the etiopathophysiology of the neurodegenerative disease, specific biomarkers and therapeutic developments, to name but a few potential areas of interest.  Literature reviews are also encouraged summarizing current efforts in the neurodegenerative disease research space employing metabolomics, epigenetics or a combination of both.

Dr. Stewart Graham
Dr. Sangeetha Vishweswaraiah
Guest Editors

Manuscript Submission Information

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Keywords

  • neurodegenerative disease
  • metabolomics
  • epigenetics
  • biomarkers
  • etiopathophysiology
  • ADRD
  • Parkinson’s disease
  • Huntington’s disease

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Published Papers (4 papers)

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Research

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16 pages, 3395 KiB  
Article
Alterations of Sphingolipid and Phospholipid Pathways and Ornithine Level in the Plasma as Biomarkers of Parkinson’s Disease
by Kuo-Hsuan Chang, Mei-Ling Cheng, Hsiang-Yu Tang, Cheng-Yu Huang, Hsiu-Chuan Wu and Chiung-Mei Chen
Cells 2022, 11(3), 395; https://doi.org/10.3390/cells11030395 - 24 Jan 2022
Cited by 19 | Viewed by 3677
Abstract
The biomarkers of Parkinson’s disease (PD) remain to be investigated. This work aimed to identify blood biomarkers for PD using targeted metabolomics analysis. We quantified the plasma levels of 255 metabolites in 92 PD patients and 60 healthy controls (HC). PD patients were [...] Read more.
The biomarkers of Parkinson’s disease (PD) remain to be investigated. This work aimed to identify blood biomarkers for PD using targeted metabolomics analysis. We quantified the plasma levels of 255 metabolites in 92 PD patients and 60 healthy controls (HC). PD patients were sub-grouped into early (Hoehn–Yahr stage ≤ 2, n = 72) and advanced (Hoehn–Yahr stage > 2, n = 20) stages. Fifty-nine phospholipids, 3 fatty acids, 3 amino acids, and 7 biogenic amines, demonstrated significant alterations in PD patients. Six of them, dihydro sphingomyelin (SM) 24:0, 22:0, 20:0, phosphatidylethanolamine-plasmalogen (PEp) 38:6, and phosphatidylcholine 38:5 and 36:6, demonstrated lowest levels in PD patients in the advanced stage, followed by those in the early stage and HC. By contrast, the level of ornithine was highest in PD patients at the advanced stage, followed by those at the early stage and HC. These biomarker candidates demonstrated significant correlations with scores of motor disability, cognitive dysfunction, depression, and quality of daily life. The support vector machine algorithm using α-synuclein, dihydro SM 24:0, and PEp 38:6 demonstrated good ability to separate PD from HC (AUC: 0.820). This metabolomic analysis demonstrates new plasma biomarker candidates for PD and supports their role in participating PD pathogenesis and monitoring disease progression. Full article
(This article belongs to the Special Issue Metabolomics and Epigenetics of Neurodegenerative Disease)
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15 pages, 1389 KiB  
Article
Plasma Metabolomics of Intermediate and Neovascular Age-Related Macular Degeneration Patients
by Sabrina L. Mitchell, Chunyu Ma, William K. Scott, Anita Agarwal, Margaret A. Pericak-Vance, Jonathan L. Haines, Dean P. Jones, Karan Uppal and Milam A. Brantley, Jr.
Cells 2021, 10(11), 3141; https://doi.org/10.3390/cells10113141 - 12 Nov 2021
Cited by 13 | Viewed by 2942
Abstract
To characterize metabolites and metabolic pathways altered in intermediate and neovascular age-related macular degeneration (IAMD and NVAMD), high resolution untargeted metabolomics was performed via liquid chromatography-mass spectrometry on plasma samples obtained from 91 IAMD patients, 100 NVAMD patients, and 195 controls. Plasma metabolite [...] Read more.
To characterize metabolites and metabolic pathways altered in intermediate and neovascular age-related macular degeneration (IAMD and NVAMD), high resolution untargeted metabolomics was performed via liquid chromatography-mass spectrometry on plasma samples obtained from 91 IAMD patients, 100 NVAMD patients, and 195 controls. Plasma metabolite levels were compared between: AMD patients and controls, IAMD patients and controls, and NVAMD and IAMD patients. Partial least-squares discriminant analysis and linear regression were used to identify discriminatory metabolites. Pathway analysis was performed to determine metabolic pathways altered in AMD. Among the comparisons, we identified 435 unique discriminatory metabolic features. Using computational methods and tandem mass spectrometry, we identified 11 metabolic features whose molecular identities had been previously verified and confirmed the molecular identities of three additional discriminatory features. Included among the discriminatory metabolites were acylcarnitines, phospholipids, amino acids, and steroid metabolites. Pathway analysis revealed that lipid, amino acid, and vitamin metabolism pathways were altered in NVAMD, IAMD, or AMD in general, including the carnitine shuttle pathway which was significantly altered in all comparisons. Finally, few discriminatory features were identified between IAMD patients and controls, suggesting that plasma metabolic profiles of IAMD patients are more similar to controls than to NVAMD patients. Full article
(This article belongs to the Special Issue Metabolomics and Epigenetics of Neurodegenerative Disease)
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15 pages, 1901 KiB  
Article
Lipid Profiling of Alzheimer’s Disease Brain Highlights Enrichment in Glycerol(phospho)lipid, and Sphingolipid Metabolism
by Sumeyya Akyol, Zafer Ugur, Ali Yilmaz, Ilyas Ustun, Santosh Kapil Kumar Gorti, Kyungjoon Oh, Bernadette McGuinness, Peter Passmore, Patrick G. Kehoe, Michael E. Maddens, Brian D. Green and Stewart F. Graham
Cells 2021, 10(10), 2591; https://doi.org/10.3390/cells10102591 - 29 Sep 2021
Cited by 51 | Viewed by 5711
Abstract
Alzheimer’s disease (AD) is reported to be closely linked with abnormal lipid metabolism. To gain a more comprehensive understanding of what causes AD and its subsequent development, we profiled the lipidome of postmortem (PM) human brains (neocortex) of people with a range of [...] Read more.
Alzheimer’s disease (AD) is reported to be closely linked with abnormal lipid metabolism. To gain a more comprehensive understanding of what causes AD and its subsequent development, we profiled the lipidome of postmortem (PM) human brains (neocortex) of people with a range of AD pathology (Braak 0–6). Using high-resolution mass spectrometry, we employed a semi-targeted, fully quantitative lipidomics profiling method (Lipidyzer) to compare the biochemical profiles of brain tissues from persons with mild AD (n = 15) and severe AD (AD; n = 16), and compared them with age-matched, cognitively normal controls (n = 16). Univariate analysis revealed that the concentrations of 420 lipid metabolites significantly (p < 0.05; q < 0.05) differed between AD and controls. A total of 49 lipid metabolites differed between mild AD and controls, and 439 differed between severe AD and mild AD. Interestingly, 13 different subclasses of lipids were significantly perturbed, including neutral lipids, glycerolipids, glycerophospholipids, and sphingolipids. Diacylglycerol (DAG) (14:0/14:0), triacylglycerol (TAG) (58:10/FA20:5), and TAG (48:4/FA18:3) were the most notably altered lipids when AD and control brains were compared (p < 0.05). When we compare mild AD and control brains, phosphatidylethanolamine (PE) (p-18:0/18:1), phosphatidylserine (PS) (18:1/18:2), and PS (14:0/22:6) differed the most (p < 0.05). PE (p-18:0/18:1), DAG (14:0/14:0), and PS (18:1/20:4) were identified as the most significantly perturbed lipids when AD and mild AD brains were compared (p < 0.05). Our analysis provides the most extensive lipid profiling yet undertaken in AD brain tissue and reveals the cumulative perturbation of several lipid pathways with progressive disease pathology. Lipidomics has considerable potential for studying AD etiology and identifying early diagnostic biomarkers. Full article
(This article belongs to the Special Issue Metabolomics and Epigenetics of Neurodegenerative Disease)
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Review

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20 pages, 5600 KiB  
Review
DNA Methylation and Schizophrenia: Current Literature and Future Perspective
by Thabo Magwai, Khanyiso Bright Shangase, Fredrick Otieno Oginga, Bonginkosi Chiliza, Thabisile Mpofana and Khethelo Richman Xulu
Cells 2021, 10(11), 2890; https://doi.org/10.3390/cells10112890 - 26 Oct 2021
Cited by 31 | Viewed by 6434
Abstract
Schizophrenia is a neuropsychiatric disorder characterized by dissociation of thoughts, idea, identity, and emotions. It has no central pathophysiological mechanism and precise diagnostic markers. Despite its high heritability, there are also environmental factors implicated in the development of schizophrenia. Epigenetic factors are thought [...] Read more.
Schizophrenia is a neuropsychiatric disorder characterized by dissociation of thoughts, idea, identity, and emotions. It has no central pathophysiological mechanism and precise diagnostic markers. Despite its high heritability, there are also environmental factors implicated in the development of schizophrenia. Epigenetic factors are thought to mediate the effects of environmental factors in the development of the disorder. Epigenetic modifications like DNA methylation are a risk factor for schizophrenia. Targeted gene approach studies attempted to find candidate gene methylation, but the results are contradictory. Genome-wide methylation studies are insufficient in literature and the available data do not cover different populations like the African populations. The current genome-wide studies have limitations related to the sample and methods used. Studies are required to control for these limitations. Integration of DNA methylation, gene expression, and their effects are important in the understanding of the development of schizophrenia and search for biomarkers. There are currently no precise and functional biomarkers for the disorder. Several epigenetic markers have been reported to be common in functional and peripheral tissue. This makes the peripheral tissue epigenetic changes a surrogate of functional tissue, suggesting common epigenetic alteration can be used as biomarkers of schizophrenia in peripheral tissue. Full article
(This article belongs to the Special Issue Metabolomics and Epigenetics of Neurodegenerative Disease)
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