Advance in Disease Modeling and Biomarker of Neurodegenerative Disease

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

Deadline for manuscript submissions: closed (20 December 2023) | Viewed by 2618

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Guest Editor
Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheba, Israel
Interests: bipolar disorder and its treatment; the possible involvement of mitochondrial dysfunction in the etiology of neuropsychiatric diseases; mechanisms of mood stabilization; interaction among neuroinflammation, brain mitochondrial function and brain autophagy
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Special Issue Information

Dear Colleagues,

We are organizing a Special Issue entitled “Advances in Modeling and Biomarkers of Neurodegenerative Diseases” to appear in the MDPI journal Cells. We cordially invite you to contribute an original paper or a review manuscript to this Special Issue. The potential contributions will, obviously, undergo a thorough peer review process. With your contribution, we will be able to compile an up-to-date seminal and comprehensive collection which will also be considered to appear as a SI reprints book. Please find the keywords for this Special Issue and its complementary information.

Ageing is the primary risk factor for most neurodegenerative diseases., e.g., one in ten individuals aged ≥65 years has Alzheimer’s disease (AD), and its prevalence continues to increase with increasing age. Given that the populations of many of the richest countries in the world have life expectancies of over 80 years and that continue to increase, the prevalence of neurodegenerative diseases is also increasing. Since the availability of effective treatments for these diseases is scarce, if any, and since these diseases tend to progress in an irreversible manner and are associated with large socioeconomic and personal costs, the emergent need to uncover predisposition biomarkers in order to develop early interventions to prevent the occurrence of pathologies, or, at least, to slow their development, is obvious. The aim of this Special Issue is to assemble original data and reviews illustrating the plethora of models of neurodegenerative disorders and their potential biomarkers that together typify dichotomic behavioral and neurochemical characteristics of health and disease. We hope that contributions from expert groups will result in a compendium supporting researchers (and drug-developing companies) with a continuous interest in neurodegeneration and its treatment, as well as newcomers to this very important field.

With kind regards,
Dr. Galila Agam
Guest Editor

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Keywords

  • neurodegenerative diseases
  • Alzheimer’s
  • Huntington’s
  • Parkinson’s
  • amyotrophic lateral sclerosis (ALS)
  • Friedreich ataxia
  • Lewy body disease
  • spinal muscular atrophy
  • disease models
  • mutants
  • behavior
  • disease biomarkers
  • bioinformatics

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Published Papers (1 paper)

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Research

19 pages, 14635 KiB  
Article
A Diagnostic Gene-Expression Signature in Fibroblasts of Amyotrophic Lateral Sclerosis
by Giovanna Morello, Valentina La Cognata, Maria Guarnaccia, Vincenzo La Bella, Francesca Luisa Conforti and Sebastiano Cavallaro
Cells 2023, 12(14), 1884; https://doi.org/10.3390/cells12141884 - 18 Jul 2023
Cited by 3 | Viewed by 2251
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal, progressive neurodegenerative disease with limited treatment options. Diagnosis can be difficult due to the heterogeneity and non-specific nature of the initial symptoms, resulting in delays that compromise prompt access to effective therapeutic strategies. Transcriptome profiling of [...] Read more.
Amyotrophic lateral sclerosis (ALS) is a fatal, progressive neurodegenerative disease with limited treatment options. Diagnosis can be difficult due to the heterogeneity and non-specific nature of the initial symptoms, resulting in delays that compromise prompt access to effective therapeutic strategies. Transcriptome profiling of patient-derived peripheral cells represents a valuable benchmark in overcoming such challenges, providing the opportunity to identify molecular diagnostic signatures. In this study, we characterized transcriptome changes in skin fibroblasts of sporadic ALS patients (sALS) and controls and evaluated their utility as a molecular classifier for ALS diagnosis. Our analysis identified 277 differentially expressed transcripts predominantly involved in transcriptional regulation, synaptic transmission, and the inflammatory response. A support vector machine classifier based on this 277-gene signature was developed to discriminate patients with sALS from controls, showing significant predictive power in both the discovery dataset and in six independent publicly available gene expression datasets obtained from different sALS tissue/cell samples. Taken together, our findings support the utility of transcriptional signatures in peripheral cells as valuable biomarkers for the diagnosis of ALS. Full article
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