Advanced Research in Proteinopathies

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cell Biology and Pathology".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 2044

Special Issue Editors


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Guest Editor
LENS-European Laboratory for Non-Linear Spectroscopy, Sesto Fiorentino, Italy
Interests: neurodegeneration; drug investigation; protein aggregation; translational research
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Guest Editor
Department of Biomedical, Experimental and Clinical Sciences "Mario Serio", University of Florence, Viale Morgagni 50, 50134 Florence, Italy
Interests: amyloid aggregation; autophagy; natural polyphenols; neurodegenerative diseases
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Special Issue Information

Dear Colleagues,

Proteinopathies are a family of diseases characterized by the accumulation of specific proteins within neurons or in the brain parenchyma that lead to synaptic dysfunction and neuronal loss. Examples for proteinopathies are Alzheimer’s disease, Parkinson’s disease, Lewy body disease, amyotrophic lateral sclerosis and fronto-temporal lobar degeneration. Typically, in a disease condition, the unstructured proteins change their conformation leading to small oligomers that eventually aggregate into higher-order structures. Prion disease is an exception within the family of proteinopathies, as the aggregated prion protein is highly infectious and can self-aggregate and propagate.

Over the years, the structural and morphological features of several protein aggregate species have been investigated, as well as the cellular events that lead to neuronal dysfunction. Moreover, a number of potential therapeutic strategies have been explored, including small molecules, antibodies and natural compounds, some of them showing promising outcomes.

This Special Issue welcomes the submission of original research papers and reviews on the most advanced developments in the above-mentioned topics, with special attention on possible therapeutic approaches targeting misfolded proteins.

Dr. Claudia Capitini
Dr. Manuela Leri
Guest Editors

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Keywords

  • protein misfolding
  • oligomers
  • amyloid fibrils
  • amorphous aggregates
  • prion
  • neurodegeneration
  • aggregation kinetics
  • neurotoxicity
  • drug discovery

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Published Papers (1 paper)

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16 pages, 1778 KiB  
Article
SIMOA Diagnostics on Alzheimer’s Disease and Frontotemporal Dementia
by Athanasia Chatziefstathiou, Sezgi Canaslan, Eirini Kanata, Kostas Vekrellis, Vasilios C. Constantinides, George P. Paraskevas, Elisabeth Kapaki, Matthias Schmitz, Inga Zerr, Konstantinos Xanthopoulos, Theodoros Sklaviadis and Dimitra Dafou
Biomedicines 2024, 12(6), 1253; https://doi.org/10.3390/biomedicines12061253 - 4 Jun 2024
Viewed by 1554
Abstract
Background: Accurate diagnosis of Alzheimer’s disease (AD) and frontotemporal dementia (FTD) represents a health issue due to the absence of disease traits. We assessed the performance of a SIMOA panel in cerebrospinal fluid (CSF) from 43 AD and 33 FTD patients with 60 [...] Read more.
Background: Accurate diagnosis of Alzheimer’s disease (AD) and frontotemporal dementia (FTD) represents a health issue due to the absence of disease traits. We assessed the performance of a SIMOA panel in cerebrospinal fluid (CSF) from 43 AD and 33 FTD patients with 60 matching Control subjects in combination with demographic–clinical characteristics. Methods: 136 subjects (AD: n = 43, FTD: n = 33, Controls: n = 60) participated. Single-molecule array (SIMOA), glial fibrillary acidic protein (GFAP), neurofilament light (NfL), TAU, and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) in CSF were analyzed with a multiplex neuro 4plex kit. Receiver operating characteristic (ROC) curve analysis compared area under the curve (AUC), while the principal of the sparse partial least squares discriminant analysis (sPLS-DA) was used with the intent to strengthen the identification of confident disease clusters. Results: CSF exhibited increased levels of all SIMOA biomarkers in AD compared to Controls (AUCs: 0.71, 0.86, 0.92, and 0.94, respectively). Similar patterns were observed in FTD with NfL, TAU, and UCH-L1 (AUCs: 0.85, 0.72, and 0.91). sPLS-DA revealed two components explaining 19% and 9% of dataset variation. Conclusions: CSF data provide high diagnostic accuracy among AD, FTD, and Control discrimination. Subgroups of demographic–clinical characteristics and biomarker concentration highlighted the potential of combining different kinds of data for successful and more efficient cohort clustering. Full article
(This article belongs to the Special Issue Advanced Research in Proteinopathies)
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