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14 pages, 247 KiB  
Review
Challenges and Revisions in Diagnostic Criteria: Advancing Early Detection of Prion Diseases
by Mika Inada Shimamura and Katsuya Satoh
Int. J. Mol. Sci. 2025, 26(5), 2037; https://doi.org/10.3390/ijms26052037 - 26 Feb 2025
Viewed by 85
Abstract
Prion diseases are fatal neurological disorders characterized by abnormal protein accumulation in the brain, leading to neurodegeneration, dementia, and ataxia. Sporadic Creutzfeldt–Jakob disease (sCJD), the most common form, accounts for 80–90% of cases and progresses rapidly, with most patients surviving <6 months to [...] Read more.
Prion diseases are fatal neurological disorders characterized by abnormal protein accumulation in the brain, leading to neurodegeneration, dementia, and ataxia. Sporadic Creutzfeldt–Jakob disease (sCJD), the most common form, accounts for 80–90% of cases and progresses rapidly, with most patients surviving <6 months to a year after symptom onset, indicating the importance of early diagnosis. The disease is classified into six subtypes based on PRNP gene polymorphisms, with differences in protein degradation patterns contributing to the diversity of clinical symptoms. However, diagnosis remains challenging because of the variability in clinical presentation and disease duration. Traditional diagnostic criteria established by the World Health Organization (WHO) rely on clinical findings, electroencephalogram, and cerebrospinal fluid tests, such as the 14-3-3 protein assay. However, these criteria require pathological confirmation, often delaying diagnosis. The recently proposed Hermann’s criteria represent a significant advancement by incorporating newer biomarkers, including magnetic resonance imaging, real-time quaking-induced conversion assay, tau protein, and neurofilament light chain. These criteria improve diagnostic sensitivity and specificity but have a slightly higher risk of false positives. This review compares the effectiveness of these biomarkers with the WHO criteria and highlights the importance of early diagnosis for improving patient care. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
33 pages, 32288 KiB  
Article
Decreasing β-Catenin Leads to Altered Endothelial Morphology, Increased Barrier Permeability and Cognitive Impairment During Chronic Methamphetamine Exposure
by Hai Qiu, Manting Zhang, Chuanxiang Chen, Huijun Wang and Xia Yue
Int. J. Mol. Sci. 2025, 26(4), 1514; https://doi.org/10.3390/ijms26041514 - 11 Feb 2025
Viewed by 289
Abstract
Cognitive impairment induced by chronic methamphetamine (METH) exposure exhibits similarities to neurodegenerative disorders and is associated with blood–brain barrier (BBB) dysfunction. However, the potential involvement of β-catenin in maintaining BBB integrity during METH exposure remains unexplored. In this study, Y-maze and novel object [...] Read more.
Cognitive impairment induced by chronic methamphetamine (METH) exposure exhibits similarities to neurodegenerative disorders and is associated with blood–brain barrier (BBB) dysfunction. However, the potential involvement of β-catenin in maintaining BBB integrity during METH exposure remains unexplored. In this study, Y-maze and novel object recognition tests were conducted to assess cognitive impairment in mice exposed chronically to methamphetamine for 2 and 4 weeks. Gd-DTPA and Evans blue leakage tests revealed disruption of the BBB in the hippocampus, while chronic METH exposure for 2 and 4 weeks significantly decreased β-catenin levels along with its transcriptionally regulated protein, claudin5. Additionally, various neural injury-related proteins, such as APP, Aβ1–42, p-tau (Thr181) and p-tau (Ser396), as well as neuroinflammation-related proteins, such as IL-6, IL-1β, and TNF-α, exhibited increased levels following chronic METH exposure. Furthermore, plasma analysis indicated elevated levels of p-Tau (total), neurofilament light chain, and GFAP. In vitro experiments demonstrated that exposure to METH resulted in dose-dependent and time-dependent reductions in cellular activity and connectivity of bEnd.3 and hcmec/D3 cells. Furthermore, β-catenin exhibited decreased levels and altered subcellular localization, transitioning from the cell membrane to the cytoplasm and nucleus upon METH exposure. Overexpression of β-catenin was found to alleviate endothelial toxicity and attenuate junctional weakening induced by METH. The aforementioned findings underscore the crucial involvement of β-catenin in endothelial cells during chronic METH exposure-induced disruption of the BBB, thereby presenting a potential novel target for addressing METH-associated cerebrovascular dysfunction and cognitive impairment. Full article
(This article belongs to the Section Molecular Biology)
Show Figures

Figure 1

Figure 1
<p>The Y-maze behavioral results of mice after 2 and 4 weeks of exposure to chronic METH. (<b>A</b>) Y-maze trace trajectories and heatmap profiling at 2 weeks post-exposure. (<b>B</b>) The spontaneous alternation behavior scores of mice in Y-maze at 2 weeks post-exposure. (<b>C</b>) Y-maze trace trajectories and heatmap profiling at 4 weeks post-exposure. (<b>D</b>) The spontaneous alternation behavior scores of mice in Y-maze at 4 weeks post-exposure. The statistical significance is shown as ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 2
<p>The NOR results of mice after 4 weeks of exposure to chronic METH. (<b>A</b>) Representative pictures of mice movement trajectories in the testing stage of the 4-week NOR test (The light blue rectangles represent novel objects, the red ones represent old ones, and the dark blue ones indicate the central area.). (<b>B</b>) Reference index of mice in NOR at 4 weeks post-exposure. (<b>C</b>) Discrimination index of mice in NOR at 4 weeks post-exposure. (<b>D</b>) The total time to explore novel and familiar object. (<b>E</b>) The exploration frequence of novel and familiar object. (<b>F</b>) The average time spent in exploration on novel and familiar objects. The statistical significance is shown as ns <span class="html-italic">p</span> &gt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 3
<p>Western blot analysis of neural injury-related proteins in hippocampal tissue. (<b>A</b>,<b>B</b>) Protein expression profiles in mice exposed to chronic methamphetamine (METH) for 2 weeks. (<b>C</b>,<b>D</b>) Protein expression profiles in mice exposed to chronic METH for 4 weeks. Statistical comparisons were performed between saline-treated and METH-treated groups at each time point: Saline_2w (<span class="html-italic">n</span> = 6) vs. METH_2w (<span class="html-italic">n</span> = 7) and Saline_4w (<span class="html-italic">n</span> = 6) vs. METH_4w (<span class="html-italic">n</span> = 7). Data are expressed as mean ± SEM. Statistical significance was assessed using unpaired two-tailed Student’ s t-tests or Mann–Whitney U tests (for non-normally distributed data). The statistical significance is shown as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Elisa for p-Tau, NEFL(Nfl), and GFAP in serum of mice administered METH for 2 or 4 weeks. (<b>A</b>) Elisa for p-Tau in serum of mice post-administered METH. (<b>B</b>) Elisa for Nfl in serum of mice post-administered METH. (<b>C</b>) Elisa for GFAP in serum of mice post-administered METH. Data are expressed as mean ± SEM. Statistical significance was assessed using one-way ANOVA and Tukey HSD test (for multiple comparison test). The statistical significance is shown as ns <span class="html-italic">p</span> &gt; 0.05, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 5
<p>IHC for β-amyloid 1-42 and GFAP in hippocampus of mice administered METH for 2 or 4 weeks. (<b>A</b>,<b>B</b>) IHC results and statistics of β-amyloid 1-42 of 2-week-treatment mice. Scale bars (from left to right): 200, 25, 25, 25 μm and microscope’s magnification (from left to right): 100×, 400×, 400×, 400×. (<b>C</b>–<b>E</b>) IHC results and statistics of GFAP of 2-week-treatment mice. Scale bars (from left to right): 200, 50, 25 μm and microscope’s magnification (from left to right): 100×, 200×, 400×. The image of the selected region has been magnified by a factor of two. Picture of threshold shows Sholl analysis of astrocytes to indicate the complexity of cell structure. GFAP<sup>+</sup> occupied area and the end-point voxels were used for statistics. The statistical significance is shown as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Chronic METH exposure leads to BBB leakage. (<b>A</b>,<b>B</b>) MRI detection of contrast agent Gd-DTPA leakage in 4 w treatment mice (<span class="html-italic">n</span> = 3) (The yellow area represents the representative hippocampal brain regions.) and related statistics (L means left brain, R means right brain; NAc-nucleus accumbens; CPu-corpus striatum; Hip-hippocampus; VTA-ventral tegmental area; <span class="html-italic">n</span><sub>saline</sub> = 3, <span class="html-italic">n</span><sub>METH</sub> = 3), the statistical significance is shown as * <span class="html-italic">p</span> &lt; 0.05 beside the brain regions. (<b>C</b>,<b>D</b>) Evans blue leakage or remaining fluorescence detection results and fluorescence intensity quantitative statistics of mice with 2 weeks of METH exposure. The saline group of the same period was set to 1 for standardization and comparison (2 weeks: <span class="html-italic">n</span><sub>saline</sub> = 5, <span class="html-italic">n</span><sub>METH</sub> = 5). (<b>E</b>,<b>F</b>) Evans blue leakage or remaining fluorescence detection results and fluorescence intensity quantitative statistics of mice with 4 weeks of METH exposure. The saline group of the same period was set to 1 for standardization and comparison (4 weeks: <span class="html-italic">n</span><sub>saline</sub> = 6, <span class="html-italic">n</span><sub>METH</sub> = 7). For C and E, the complete hippocampal image was generated by stitching together scanned images acquired at 200× magnification, while the partial images were captured at 400× magnification. The statistical significance is shown as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Chronic METH exposure leads to claudin5 and β-catenin reduction, and other cell junction proteins changing. (<b>A</b>) Western blot analyses of cell-junction-associated protein in the hippocampi of mice treated for 2 weeks (<span class="html-italic">n</span><sub>saline</sub> = 6, <span class="html-italic">n</span><sub>METH</sub> = 7). (<b>B</b>) Immunofluorescence staining of claudin5 and CD31 in the hippocampi of mice exposed to METH for 2 weeks. (<b>C</b>) Immunofluorescence co-localization analysis of claudin5 and CD31 of mice exposed to METH for 2 weeks. (<b>D</b>) Statistics of colocalization coefficient R (<span class="html-italic">n</span><sub>saline</sub> = 6, <span class="html-italic">n</span><sub>METH</sub> = 7) and immunofluorescence intensity (<span class="html-italic">n</span><sub>saline</sub> = 6, <span class="html-italic">n</span><sub>METH</sub> = 7) of claudin5 for mice exposed to METH for 2 weeks. (<b>E</b>) Western blot analyses of cell-junction-associated protein in the hippocampi of mice treated for 4 weeks (<span class="html-italic">n</span><sub>saline</sub> = 6, <span class="html-italic">n</span><sub>METH</sub> = 7). (<b>F</b>) Immunofluorescence staining of claudin5 and CD31 in the hippocampi of mice exposed to METH for 4 weeks. (<b>G</b>) Immunofluorescence co-localization analysis of claudin5 and CD31 of mice exposed to METH for 4 weeks. (<b>H</b>) Statistics of colocalization coefficient R (<span class="html-italic">n</span><sub>saline</sub> = 11, <span class="html-italic">n</span><sub>METH</sub> = 12) and immunofluorescence intensity (<span class="html-italic">n</span><sub>saline</sub> = 11, <span class="html-italic">n</span><sub>METH</sub> = 12) of claudin5 for mice exposed to METH for 4 weeks. Scale bars in each group: 200 μm for upper, and 50 μm for lower. The statistical significance is shown as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 8
<p>The increase of METH concentration cause endothelial cell injury, permeability increase, decreased β-catenin and changes in other cell junction proteins. (<b>A</b>) bEnd.3 (left) and hcmec/D3 (right) cell viability was measured by CCK8 after 24 h treatment with different METH concentration gradients. Kruskal–Wallis test was used to compare between different concentrations of METH vs. control. (<b>B</b>) The modeling and detection of 70 kDa FITC-dextran permeability test for monolayer endothelial barrier in the small chamber of a transwell (above). In a bEnd.3 monolayer endothelial barrier (lower left), the total permeation amount of FITC changed under different concentrations of METH (24 h treatment) and different detection time. The same statistics for hcmec/D3 are on the lower right. Two-way ANOVA was used to compare the effect of METH treatment and testing time. (<b>C</b>) Cell morphology observation of bEnd.3 treated with METH concentration gradients for 24 h. The second row of images shows the threshold images of the intercellular area at a magnification of 200×, which were used for statistics. Scale bars in 200× and 400× images are shown as 100 and 50 μm. (<b>D</b>,<b>E</b>) Western blot analyzed cell-junction-related proteins in bEnd.3 and hcmec/D3 treated with different concentrations of METH for 24 h. Using β-actin as an internal parameter, the control group was normalized to 1 and METH groups were compared with control group. The statistical significance is shown as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. All the data were derived from cell passages of at least three batches.</p>
Full article ">Figure 9
<p>METH concentration gradient treatments affected PTEN/AKT/GSK-3β signal axis in endothelial cells. (<b>A</b>) Western blot of PTEN, p-AKT, AKT, GSK-3β in bEnd.3 treated by METH concentration gradient. (<b>B</b>–<b>E</b>) Relative protein level analyses of PTEN, p-AKT, AKT, GSK-3β in bEnd.3. (<b>F</b>) Western blot of PTEN, p-AKT, AKT, GSK-3β in hcmec/D3 treated by METH concentration gradient. (<b>G</b>–<b>J</b>) Relative protein level analyses of PTEN, p-AKT, AKT, GSK-3β in hcmec/D3. All the data were derived from cell passages of at least three batches. The statistical significance is shown as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>METH treatment duration induced the decrease of β-catenin and its transfer from cytomembrane to nucleus. (<b>A</b>) The immunofluorescence staining of β-catenin in bEnd.3 after continuous treatment with 1.0 mM METH for 0~5 days (400× and 630× magnification). The threshold images show decreased cytomembrane β-catenin and increased cytoplasm β-catenin. (<b>B</b>,<b>C</b>) Cell membrane, cytoplasmic and nuclear components of bEnd.3 were separated and β-catenin expression levels of each component were detected by Western blot, and corresponding statistics. (<b>D</b>,<b>E</b>) The same detection and statistics of hcmec/D3. All the data were derived from cell passages of at least three batches. The statistical significance is shown as ns <span class="html-italic">p</span> &gt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Effects of knockdown and overexpression of β-catenin on cell activity and permeability of bEnd.3. (<b>A</b>) The knockdown and overexpression of β-catenin were detected by Western blot. (<b>B</b>,<b>C</b>) CCK8 was used to detect the cell viability of knockdown and overexpressed cell lines and the viability under treatments of 2.0 mM METH treating for 24 h and 1.5 mM METH treating for 48 h. (<b>D</b>) The detection of 70 kDa using an FITC-dextran permeability test for monolayer endothelial barrier of different cell lines and for those under 1.5 mM METH treatment for 48 h. The statistical significance is shown as ns <span class="html-italic">p</span> &gt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Effects of knockdown and overexpression of β-catenin on morphology of bEnd.3. (<b>A</b>) Morphological observation of different cell lines under 2.0 mM METH treatment for 24 h, scale bars: 500 μm for 100×, 250 μm for 200× and 400× images were enlarged twice from 200×. (<b>B</b>) Immunocytochemistry of β-catenin in different cell lines on the transwell after FITC-dextran permeability test. The upper images of each group are formed by scanning and stitching together at a magnification of 200×, while the lower images are displayed by magnifying three times within a rectangular selection area. Scale bars represent 200 μm for upper and 50 μm for lower, respectively.</p>
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<p>Effects of knockdown and overexpression of β-catenin on β-catenin and claudin5 protein levels, and β-catenin expression levels on cytomembrane, cytoplasm and nucleus. (<b>A</b>,<b>B</b>) Western blot analysis of β-catenin and claudin5 protein levels in cells subjected to knockdown, overexpression, and METH treatment. (<b>C</b>–<b>E</b>) Western blot analysis of β-catenin expression levels on cytomembrane, cytoplasm and nucleus in cells subjected to knockdown, overexpression, and METH treatment. In the statistical comparison of data corresponding to the two endpoints of the connection, symbols * and # are used to denote significant differences. The statistical significance is shown as: ns <span class="html-italic">p</span> &gt; 0.05, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001; # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001, #### <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Establishment of chronic METH exposure model and behavioral test and sampling arrangement.</p>
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<p>Concept drawing: METH diminishes endothelial β-catenin expression and induces its relocalization, compromising the integrity of the blood–brain barrier and eliciting cognitive impairment in chronically exposed mice. (The illustration is created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.)</p>
Full article ">Scheme 1
<p>The performance of mice in the NOR test adaptation stage, training stage, and testing stage (The light blue rectangles represent novel objects, the red ones represent old ones, and the dark blue ones indicate the central area.). (<b>A</b>–<b>D</b>) Representative pictures of mice movement trajectories in the adaptation stage (open field) of the 4-week NOR test, and their statistical analysis of total distance, moving distance in central area (%), and moving time in central area (%). (<b>E</b>–<b>G</b>) Representative pictures of mice movement trajectories in the training stage, and their statistical analysis of discrimination index and preference index. (<b>H</b>,<b>I</b>) Some mice exhibited the behavior of knocking against the walls in the testing stage of the 4-week NOR test and relevant statistics (The yellow arrow points to the location of the mouse.). The statistical significance is shown as ns <span class="html-italic">p</span> &gt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Scheme 2
<p>A schematic diagram of mouse MRI-T1-WI imaging and data acquisition. The formula for calculating the signal intensity of the corresponding brain region in T1-WI imaging is as follows: (Mean<sub>25min after injection</sub> − Mean<sub>Basline</sub>)/Mean<sub>Basline</sub>. (The outlines of the brain region are depicted as the yellow dotted line in the left figures. The mean value is marked with a red underline.).</p>
Full article ">Scheme 3
<p>The increase of METH concentration causes decrease of β-catenin, ZO-1 and claudin5. (<b>A</b>) Immunofluorescence staining of β-catenin of bEnd.3 after METH concentration gradient treatment for 24 h. Images in upper row were captured at 400× magnification, while those in lower row were at 630× magnification. (<b>C</b>) Corresponding average fluorescence intensity statistics of β-catenin. (<b>B</b>) Immunofluorescence staining of ZO-1 and claudin5 of bEnd.3 after METH concentration gradient treatment for 24 h. (<b>D</b>,<b>E</b>) Corresponding average fluorescence intensity statistics of ZO-1 and claudin5. The statistical significance is shown as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Scheme 4
<p>METH treatment duration induced the decrease of β-catenin and other junction proteins. (<b>A</b>) Western blot analysis of ZO-1, CDH5, β-catenin and occludin in bEnd.3 treated by 1.5 mM METH for a 0–48 h time gradient. (<b>B</b>) Immunofluorescence staining of β-catenin in bEnd.3 after continuous treatment with 1.0 mM METH for 0~5 days (400× magnification). (<b>C</b>,<b>D</b>) Western blot analysis of β-catenin in bEnd.3 after continuous treatment with 1.0 mM METH for 0~5 days. (<b>E</b>,<b>F</b>) Western blot analysis of claudin5 in bEnd.3 after continuous treatment with 1.0 mM METH for 0~5 days. All the data were derived from cell passages of at least three batches. The statistical significance is shown as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">
15 pages, 7436 KiB  
Article
Notch-1 Immunopositivity in Brain Lesions Associated with Pharmacoresistant Epilepsy
by Dimitar Metodiev, Petia Dimova, Margarita Ruseva, Dimitar Parvanov, Rumiana Ganeva, Georgi Stamenov, Sevdalin Nachev, Vesela Ivanova, Rumen Marinov and Krassimir Minkin
Neuroglia 2025, 6(1), 7; https://doi.org/10.3390/neuroglia6010007 - 8 Feb 2025
Viewed by 219
Abstract
Background: The Notch signaling pathway is an important regulator of stem cell activity in various tissues, including the central nervous system. It has been implicated in neurodevelopmental processes, including neuronal differentiation and synaptic plasticity. Research suggests that its expression may be associated with [...] Read more.
Background: The Notch signaling pathway is an important regulator of stem cell activity in various tissues, including the central nervous system. It has been implicated in neurodevelopmental processes, including neuronal differentiation and synaptic plasticity. Research suggests that its expression may be associated with certain epileptogenic lesions, particularly those with neurodevelopmental origin. The aim of this study was to investigate the expression of Notch-1 in brain biopsies from various cases of pharmacoresistant epilepsy. Methods: Here, we used immunohistochemistry staining to retrospectively analyze 128 developmental lesions associated with pharmacoresistant epilepsy, including 13 cases with focal cortical dysplasia (FCD) type I, 39 with FCD type II, 37 with hippocampal sclerosis (HS), 23 with FCD IIIc, 9 with mild malformations of cortical development (MCD), 4 cases with mild malformation of cortical development with oligodendroglial hyperplasia and epilepsy (MOGHE), and 3 with tuberous sclerosis (TS). The tissues were stained for Neurofilament protein, Vimentin, S-100 protein, NeuN, and GFAP, as well as the stem cell marker Notch-1. Tissue that stained positively for Notch-1 was further characterized. Results: A positive Notch-1 reaction was found in all cases of FCD type IIb and TS, where it appeared in balloon cells but not in dysmorphic neurons, and in a single case of meningioangiomatosis (FCD IIIc), where it stained spider-like cells. Notch-1-positive cells showed a stem-like, glio-neuronal precursor immunophenotype. No staining was observed in the remaining cases with FCD type I, type III, HS, mild MCD, and MOGHE. Conclusions: Notch-1 displays a distinct pattern of expression in some epileptogenic lesions, potentially highlighting a stem cell-like origin or neurodevelopmental abnormalities contributing to pharmacoresistant epilepsy; however, it is not a general marker of such lesions. Its differential expression may prove useful in distinguishing between different types of FCD or other cortical malformations, which could assist in both their diagnosis and potentially in the development of more targeted therapeutic approaches. Further studies with different stem cell markers are needed in this direction. Full article
Show Figures

Figure 1

Figure 1
<p>FCD type IIa. (<b>A</b>) HE staining showing DNs with enlarged cell bodies and nuclei with visible nucleoli; (<b>B</b>) characteristic immunostaining of DNs demonstrating accumulation of non-phosphorylated heavy neurofilaments, IHC staining, SMI32; (<b>C</b>) DNs positive for the marker NeuN, IHC staining; (<b>D</b>) DNs negative for Notch-1; IHC staining.</p>
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<p>FCD type IIb. (<b>A</b>) HE staining showing DNs with enlarged cell bodies and nuclei and aggregated Nissl substance (black arrows) and balloon cells (white stars); (<b>B</b>) characteristic immunostaining of DNs positive for SMI32 and SMI32-negative large round BCs; (<b>C</b>) Vimentin-positive DNs; (<b>D</b>) DNs positive for S-100 protein; (<b>E</b>) BCs positive for the marker Notch-1, IHC staining; (<b>F</b>) higher-magnification Notch-1 IHC staining showing positively marked balloon (white star) and spider-like cells (black arrow), but not dysmorphic neurons (yellow arrow).</p>
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<p>Tuberous sclerosis, fetal autopsy case I. (<b>A</b>) HE staining showing a tendency for perivascular orientation of BCs; (<b>B</b>) immunostaining of BCs with the marker Vimentin; (<b>C</b>) BCs are negative for neurofilament proteins (IHC study with SMI32); (<b>D</b>) the biomarker NOTCH1 labels the BCs, again demonstrating a tendency for perivascular localization.</p>
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<p>Tuberous sclerosis, fetal autopsy case II. (<b>A</b>) HE staining showing BCs; (<b>B</b>) immunostaining of BCs with the marker Vimentin, BV—blood vessel; (<b>C</b>) BCs are positive for Notch-1; (<b>D</b>) higher magnification showing the marker NOTCH1 labels cells with a spider-like morphology (black arrows).</p>
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<p>Tuberous sclerosis, biopsy case. (<b>A</b>) HE staining showing a tendency for back-to-back arrangement of BCs; (<b>B</b>) immunostaining of BCs with the marker Vimentin; (<b>C</b>) BCs are positive for the marker GFAP; (<b>D</b>) biomarker NOTCH1 labels the BCs, showing a tendency for two patterns of immunoreactivity.</p>
Full article ">Figure 6
<p>Meningioangiomatosis. (<b>A</b>) H&amp;E staining demonstrating hamartomatous meningeal–angiomatous proliferation; (<b>B</b>) in some areas, individual cells with a morphology identical to that of DNs are observed; (<b>C</b>) positive immunostaining with GFAP; (<b>D</b>) positive immunohistochemical reaction for CD34, marking the angiomatous component; (<b>E</b>) positive immunohistochemical reaction for NeuN, marking the neuronal cell composition; (<b>F</b>) dysmorphic cells show identical immunostaining for neurofilament proteins similar to DNs in FCD type II (IHC analysis with SMI32 marker); (<b>G</b>) IHC analysis with the Vimentin marker, marking the cellular elements between the meningeal-angiomatous proliferation; (<b>H</b>) positive reaction for the stem cell biomarker Notch-1 in individual cells with irregular branching projections (spider-like cells), as seen in cases of FCD type IIb.</p>
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16 pages, 618 KiB  
Review
Plasma Biomarkers for Cerebral Amyloid Angiopathy and Implications for Amyloid-Related Imaging Abnormalities: A Comprehensive Review
by Mo-Kyung Sin, Jeffrey L. Dage, Kwangsik Nho, N. Maritza Dowling, Nicholas T. Seyfried, David A. Bennett, Allan I. Levey and Ali Ahmed
J. Clin. Med. 2025, 14(4), 1070; https://doi.org/10.3390/jcm14041070 - 7 Feb 2025
Viewed by 476
Abstract
Anti-amyloid therapies (AATs) are increasingly being recognized as promising treatment options for Alzheimer’s disease (AD). Amyloid-related imaging abnormalities (ARIAs), small areas of edema and microbleeds in the brain presenting as abnormal signals in MRIs of the brain for patients with AD, are the [...] Read more.
Anti-amyloid therapies (AATs) are increasingly being recognized as promising treatment options for Alzheimer’s disease (AD). Amyloid-related imaging abnormalities (ARIAs), small areas of edema and microbleeds in the brain presenting as abnormal signals in MRIs of the brain for patients with AD, are the most common side effects of AATs. While most ARIAs are asymptomatic, they can be associated with symptoms like nausea, headache, confusion, and gait instability and, less commonly, with more serious complications such as seizures and death. Cerebral amyloid angiopathy (CAA) has been found to be a major risk for ARIA development. The identification of sensitive and reliable non-invasive biomarkers for CAA has been an area of AD research over the years, but with the approval of AATs, this area has taken on a new urgency. This comprehensive review highlights several potential biomarkers, such as Aβ40, Aβ40/42, phosphorylated-tau217, neurofilament light chain, glial fibrillary acidic protein, secreted phosphoprotein 1, placental growth factor, triggering receptor expressed on myeloid cells 2, cluster of differentiation 163, proteomics, and microRNA. Identifying and staging CAA even before its consequences can be detected via neuroimaging are critical to allow clinicians to judiciously select appropriate candidates for AATs, stratify monitoring, properly manage therapeutic regimens for those experiencing symptomatic ARIAs, and optimize the treatment to achieve the best outcomes. Future studies can test potential plasma biomarkers in human beings and evaluate predictive values of individual markers for CAA severity. Full article
(This article belongs to the Section Clinical Neurology)
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<p>Neurodegeneration, neuroinflammation, and CAA.</p>
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13 pages, 925 KiB  
Article
Plasma Biomarkers in the Distinction of Alzheimer’s Disease and Frontotemporal Dementia
by Estrella Gómez-Tortosa, Pablo Agüero-Rabes, Alicia Ruiz-González, Sonia Wagner-Reguero, Raquel Téllez, Ignacio Mahillo, Andrea Ruiz-Calvo, María José Sainz, Anna Lena Nystrom, Teodoro del Ser and Pascual Sánchez-Juan
Int. J. Mol. Sci. 2025, 26(3), 1231; https://doi.org/10.3390/ijms26031231 - 30 Jan 2025
Viewed by 546
Abstract
Plasma biomarkers are promising tools for the screening and diagnosis of dementia in clinical settings. We analyzed plasma levels of Alzheimer’s core biomarkers, neurofilament light chain (NfL) and glial fibrillary acid protein (GFAP), through single-molecule Array in 108 patients with Alzheimer’s (AD, cerebrospinal [...] Read more.
Plasma biomarkers are promising tools for the screening and diagnosis of dementia in clinical settings. We analyzed plasma levels of Alzheimer’s core biomarkers, neurofilament light chain (NfL) and glial fibrillary acid protein (GFAP), through single-molecule Array in 108 patients with Alzheimer’s (AD, cerebrospinal fluid with an amyloid+ tau+ neurodegeneration+ profile), 73 patients with frontotemporal dementia (FTD, 24 with genetic diagnosis), and 54 controls. The best area under the curve (AUC) was used to assess the discriminative power. Patients with AD had lower Aß42/40 ratios and NfL levels, along with higher levels of p-tau181 and GFAP, compared with FTD patients. Single biomarkers discriminated well between dementia patients and controls: the Aß42/40 ratio (AUC:0.86) or GFAP (AUC:0.83) was found for AD, and the NfL (AUC:0.84) was found for FTD patients. However, a combination of two (NfL with p-tau181, or the GFAP/NfL ratio, AUCs ~0.87) or three biomarkers (NfL, P-tau181, and Aß42/40 ratio, AUC: 0.90) was required to distinguish between AD and FTD. Biomarker profiles were similar across different FTD phenotypes, except for carriers of PGRN mutations, who had higher levels of NfL than C9orf72 expansion carriers. In our series, NfL alone provided the best distinction between FTD and controls, while a combination of two or three biomarkers was required to obtain good discrimination between AD and FTD. Full article
(This article belongs to the Section Molecular Neurobiology)
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<p>Boxplots of the biomarkers in the three groups. The boxplots depict the median in the center; the boundaries indicate the first and third quartiles, while the whiskers extend from the 5th to 95th percentile, and the black points indicate individual outliers. Post hoc comparisons are visualized with * <span class="html-italic">p</span> &lt; 0.05 (green), ** <span class="html-italic">p</span> &lt; 0.001 (orange), and *** <span class="html-italic">p</span> &lt; 0.0001 (red). Biomarker levels (y axis) are in pg/mL.</p>
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<p>Diagnostic accuracy of the most significant biomarkers.</p>
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<p>Biomarkers with significant differences according to clinical phenotypes (P-tau181, <b>left</b>) and gene mutation (NfL, <b>right</b>). P-tau181 was significantly higher in the behavioral variant than in Sv-PPA cases (<span class="html-italic">p</span> &lt; 0.043). <span class="html-italic">PGRN</span> mutations carriers (<span class="html-italic">n</span> = 7) had higher levels of NfL than <span class="html-italic">C9orf72</span> expansion carriers (<span class="html-italic">n</span> = 13, <span class="html-italic">p</span> = 0.001).</p>
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21 pages, 1784 KiB  
Review
From Cell Architecture to Mitochondrial Signaling: Role of Intermediate Filaments in Health, Aging, and Disease
by Emanuele Marzetti, Rosa Di Lorenzo, Riccardo Calvani, Vito Pesce, Francesco Landi, Hélio José Coelho-Júnior and Anna Picca
Int. J. Mol. Sci. 2025, 26(3), 1100; https://doi.org/10.3390/ijms26031100 - 27 Jan 2025
Viewed by 1010
Abstract
The coordination of cytoskeletal proteins shapes cell architectures and functions. Age-related changes in cellular mechanical properties have been linked to decreased cellular and tissue dysfunction. Studies have also found a relationship between mitochondrial function and the cytoskeleton. Cytoskeleton inhibitors impact mitochondrial quality and [...] Read more.
The coordination of cytoskeletal proteins shapes cell architectures and functions. Age-related changes in cellular mechanical properties have been linked to decreased cellular and tissue dysfunction. Studies have also found a relationship between mitochondrial function and the cytoskeleton. Cytoskeleton inhibitors impact mitochondrial quality and function, including motility and morphology, membrane potential, and respiration. The regulatory properties of the cytoskeleton on mitochondrial functions are involved in the pathogenesis of several diseases. Disassembly of the axon’s cytoskeleton and the release of neurofilament fragments have been documented during neurodegeneration. However, these changes can also be related to mitochondrial impairments, spanning from reduced mitochondrial quality to altered bioenergetics. Herein, we discuss recent research highlighting some of the pathophysiological roles of cytoskeleton disassembly in aging, neurodegeneration, and neuromuscular diseases, with a focus on studies that explored the relationship between intermediate filaments and mitochondrial signaling as relevant contributors to cellular health and disease. Full article
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<p>Schematic classification of intermediate filaments and protein types. Abbreviations: IF, intermediate filament; NF-H, high molecular weight neurofilaments; NF-L, low molecular weight neurofilaments; NF-M, middle molecular weight neurofilaments. Created in <a href="https://BioRender.com" target="_blank">https://BioRender.com</a>.</p>
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<p>Schematic representation of the cytoskeletal organization (<b>A</b>) and cytoskeletal–mitochondria interactions in a neuron (<b>B</b>) and the sarcomere (<b>C</b>). Created in <a href="https://BioRender.com" target="_blank">https://BioRender.com</a>.</p>
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23 pages, 2526 KiB  
Systematic Review
Effects of Physical Exercise on Neurofilament Light Chain and Glial Fibrillary Acidic Protein Level in Patients with Multiple Sclerosis: A Systematic Review and Bayesian Network Meta-Analysis
by Aitor Blázquez-Fernández, Víctor Navarro-López, Selena Marcos-Antón and Roberto Cano-de-la-Cuerda
J. Clin. Med. 2025, 14(3), 839; https://doi.org/10.3390/jcm14030839 - 27 Jan 2025
Viewed by 634
Abstract
Background: The prognosis of people with multiple sclerosis (MS) has improved substantially in recent decades due to advances in diagnosis and treatment. Due to the unpredictable course and heterogenous treatment response in MS, there is a clear need for biomarkers that reflect disease [...] Read more.
Background: The prognosis of people with multiple sclerosis (MS) has improved substantially in recent decades due to advances in diagnosis and treatment. Due to the unpredictable course and heterogenous treatment response in MS, there is a clear need for biomarkers that reflect disease activity in the clinical follow-up of these patients. We conducted a systematic review with Bayesian network meta-analysis with the aim of analyzing the effects of physical exercise on neurofilaments (NfL) and glial fibrillary acidic protein (GFAP) levels in patients with MS. Methods: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, starting with a PICO (patient/population, intervention, comparison, and outcome) question: what are the clinical effects of physical exercise (with independence of the type) on NfL and/or GFAP levels in patients with MS compared with other interventions or no intervention whatsoever? A systematically comprehensive literature search was conducted from January to March 2024 to identify original studies that answered the PICO question, using the main data sources. The quality of the studies included was assessed using the Quality Index of Downs & Black. For studies included in the systematic review that followed a randomized controlled trial (RCT) design, the methodological quality of each paper was assessed using the Physiotherapy Evidence Database (PEDro) Scale. Risk of bias was also explored by two independent reviewers. Finally, all articles were classified according to the levels of evidence and grades of recommendation for diagnosis studies established by the Oxford Center for Evidence-Based Medicine. For continuous outcome measures with enough comparisons and a methodological quality greater than or equal to good according to the PEDro scale, a Bayesian network meta-analysis (NMA) was applied. The statistical analyses were performed in R (version 4.1.3, R Core Team 2023) using the “BUGSnet” and “gemtc” packages. Bayesian NMA can be used to obtain a posterior probability distribution of all the relative treatment effects, which allows us to quantify the uncertainty of parameter estimates and to rank all the treatments in the network. Results: Eight studies were included in this systematic review and six articles in the NMA, and they were appraised for quality. The characteristics of the included studies, types of training and described protocols, methodological quality, risk of bias, and clinical effects on the studied biomarkers were outlined. Qualitative synthesis, effects of different exercise modalities in NfL with the Bayesian NMA, selection of the final model and model assessment, and ranking of interventions are also shown. Conclusions: Our findings indicated that moderate-intensity exercise is more likely to reduce NfL concentration compared to high-intensity exercise, and, in turn, high-intensity exercise is more likely to reduce NfL concentration than low-intensity exercise. However, the effects of high-intensity exercise on GFAP levels were inconclusive. Full article
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<p>Flow chart of the identified studies according to the PRISMA 2020 Statement.</p>
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<p>Traffic light plot and summary plot.</p>
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<p>Network diagram of the effect of interventions on NfL levels. The width of each line is proportional to the number of trials comparing every pair of treatments, and the size of each circle is proportional to the number of randomly allocated participants (sample size). Hig: High-Intensity Training; Low: Low-Intensity Training; Mod: Moderate-Intensity Training.</p>
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<p>Direct and indirect comparison of interventions on NfL levels in network meta-analysis. Evaluates the consistency between direct and indirect comparisons for a specific pair of treatments. Circles: Point estimates of treatment effect for direct and indirect comparisons. Lines: 95% confidence intervals. When the lines cross 0, it indicates that there are no significant differences between the compared treatments. If the direct and indirect comparisons differ markedly, it may indicate inconsistency in the network.</p>
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<p>Surface under the cumulative ranking curve. Higher SUCRA (surface under the cumulative ranking curve) values (close to 100%) indicate the probability that a treatment is more successful in reducing NfL levels compared to other treatments evaluated.</p>
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42 pages, 4503 KiB  
Review
Advances in Huntington’s Disease Biomarkers: A 10-Year Bibliometric Analysis and a Comprehensive Review
by Sarah Aqel, Jamil Ahmad, Iman Saleh, Aseela Fathima, Asmaa A. Al Thani, Wael M. Y. Mohamed and Abdullah A. Shaito
Biology 2025, 14(2), 129; https://doi.org/10.3390/biology14020129 - 26 Jan 2025
Viewed by 846
Abstract
Neurodegenerative disorders (NDs) cause progressive neuronal loss and are a significant public health concern, with NDs projected to become the second leading global cause of death within two decades. Huntington’s disease (HD) is a rare, progressive ND caused by an autosomal-dominant mutation in [...] Read more.
Neurodegenerative disorders (NDs) cause progressive neuronal loss and are a significant public health concern, with NDs projected to become the second leading global cause of death within two decades. Huntington’s disease (HD) is a rare, progressive ND caused by an autosomal-dominant mutation in the huntingtin (HTT) gene, leading to severe neuronal loss in the brain and resulting in debilitating motor, cognitive, and psychiatric symptoms. Given the complex pathology of HD, biomarkers are essential for performing early diagnosis, monitoring disease progression, and evaluating treatment efficacy. However, the identification of consistent HD biomarkers is challenging due to the prolonged premanifest HD stage, HD’s heterogeneous presentation, and its multiple underlying biological pathways. This study involves a 10-year bibliometric analysis of HD biomarker research, revealing key research trends and gaps. The study also features a comprehensive literature review of emerging HD biomarkers, concluding the need for better stratification of HD patients and well-designed longitudinal studies to validate HD biomarkers. Promising candidate wet HD biomarkers— including neurofilament light chain protein (NfL), microRNAs, the mutant HTT protein, and specific metabolic and inflammatory markers— are discussed, with emphasis on their potential utility in the premanifest HD stage. Additionally, biomarkers reflecting brain structural deficits and motor or behavioral impairments, such as neurophysiological (e.g., motor tapping, speech, EEG, and event-related potentials) and imaging (e.g., MRI, PET, and diffusion tensor imaging) biomarkers, are evaluated. The findings underscore that the discovery and validation of reliable HD biomarkers urgently require improved patient stratification and well-designed longitudinal studies. Reliable biomarkers, particularly in the premanifest HD stage, are crucial for optimizing HD clinical management strategies, enabling personalized treatment approaches, and advancing clinical trials of HD-modifying therapies. Full article
(This article belongs to the Special Issue Young Researchers in Neuroscience)
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<p>The intricate molecular pathways and mechanisms underlying pathology of Huntington’s disease.</p>
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<p>Trends of HD biomarker publications over time.</p>
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<p>Journals where HD biomarkers research is published the most.</p>
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<p>International collaboration network of research on HD biomarkers.</p>
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<p>Most frequently used keywords in published studies investigating HD biomarkers.</p>
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<p>Network of the 50 keywords most frequently used in HD biomarkers published studies.</p>
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<p>The role of biomarkers in Huntington’s disease.</p>
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15 pages, 1073 KiB  
Article
Blood Neurofilament Light Chain and Phospho-Tau 181 in Subjects with Mild Cognitive Impairment Due to Age-Related Hearing Loss
by Giuseppe Alberti, Daniele Portelli, Francesca Polito, Anita Graceffa, Laura Licitri, Sabrina Loteta, Margherita Maria Torre, Irene Gasparo, Vincenzo Rizzo, M’hammed Aguennouz and Vincenzo Macaione
J. Clin. Med. 2025, 14(3), 672; https://doi.org/10.3390/jcm14030672 - 21 Jan 2025
Viewed by 553
Abstract
Background: Mild cognitive impairment is increasingly recognized as a precursor to more severe neurodegenerative conditions, particularly in the context of aging. Recent studies have highlighted the intersection of hearing loss and cognitive decline, suggesting that auditory deficits may exacerbate cognitive impairments in [...] Read more.
Background: Mild cognitive impairment is increasingly recognized as a precursor to more severe neurodegenerative conditions, particularly in the context of aging. Recent studies have highlighted the intersection of hearing loss and cognitive decline, suggesting that auditory deficits may exacerbate cognitive impairments in older adults, proposing the use of hearing aids to mitigate cognitive decline, and indicating that early intervention in hearing loss could be crucial for preserving cognitive function. The underlying mechanisms of the relationship between hearing and cognitive impairment may involve neuroinflammatory processes and neurodegeneration. Recent studies have evidenced the role of tau proteins and neurofilaments as biomarkers in the onset and progression of neurodegenerative diseases. Methods: We selected 30 subjects with age-related hearing loss, and we evaluated their cognitive status through the administration of screening tests, which also measured neurofilament light chain and phospho-tau 181 serum levels as biomarkers of neurodegeneration. The subjects were re-evaluated six months after the hearing aid fitting. Results: Patients with hearing impairment presented slightly altered results on cognitive tests, typical of a mild cognitive impairment. At the same time, serum levels of neurofilament light chain and phospho-tau 181 were significantly increased compared to the matched control group. After the hearing aids fitting, auditory, cognitive, and serum values results improved. Conclusions: The results of the study highlight the cognitive involvement in patients with hearing impairment and identify neurofilament light chain and phospho-tau 181 as serum biomarkers of neurodegeneration useful in monitoring the pathology. Full article
(This article belongs to the Section Otolaryngology)
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<p>Cognitive tests score before hearing aids. Mann–Whitney test. Data are expressed as means ± standard deviations. * = <span class="html-italic">p</span> &lt; 0.05; ** = <span class="html-italic">p</span> &lt; 0.005; **** = <span class="html-italic">p</span> &lt; 0.0001. ARHL, Age-related hearing loss group; MMSE, Mini-Mental State Examination; RAVLT, Rey Auditory Verbal Learning Task.</p>
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<p>Biomarkers level before hearing aids. Mann–Whitney test. Data are expressed as means ± standard deviations. **** = <span class="html-italic">p</span> &lt; 0.0001. ARHL, Age-related hearing loss group.</p>
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<p>MMSE and SRT score/biomarkers correlations in ARHL group before hearing aids. Spearman’s rank correlation coefficient. * = <span class="html-italic">p</span> &lt; 0.05; ** = <span class="html-italic">p</span> &lt; 0.005; ARHL, Age-related hearing loss group; MMSE, Mini-Mental State Examination; SRT, Speech Reception Threshold.</p>
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<p>ARHL group valuation after hearing aids use. Mann–Whitney test. Data are expressed as means ± standard deviations. *** = <span class="html-italic">p</span> &lt; 0.0005; **** = <span class="html-italic">p</span> &lt; 0.0001. ARHL, Age-related hearing loss group; MMSE, Mini-Mental State Examination; SRT, Speech Reception Threshold.</p>
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11 pages, 1045 KiB  
Article
Exploring the Link Between Renal Function Fluctuations Within the Physiological Range and Serum/CSF Levels of NfL, GFAP, tTAU, and UCHL1
by Kimberly Koerbel, Yavor Yalachkov, Tabea Rotter, Martin A. Schaller-Paule, Jan Hendrik Schaefer, Lucie Friedauer, Jasmin Jakob, Falk Steffen, Stefan Bittner, Christian Foerch and Michelle Maiworm
Int. J. Mol. Sci. 2025, 26(2), 748; https://doi.org/10.3390/ijms26020748 - 17 Jan 2025
Viewed by 709
Abstract
Impaired renal function can influence biomarker levels through mechanisms involving blood–brain barrier integrity and clearance pathways; however, the impact of variations within normal renal function remains unclear. The main aim of this study was to determine whether adjustment for the specific level of [...] Read more.
Impaired renal function can influence biomarker levels through mechanisms involving blood–brain barrier integrity and clearance pathways; however, the impact of variations within normal renal function remains unclear. The main aim of this study was to determine whether adjustment for the specific level of renal function is necessary when renal function remains within physiological levels. We studied n = 183 patients (NID n = 122; other neurological diseases n = 39; somatoform controls n = 22) who underwent lumbar puncture at University Hospital Frankfurt. Serum and cerebrospinal fluid (CSF) levels of neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), total tau protein (tTAU), and ubiquitin C-terminal hydrolase-L1 (UCHL1) were measured using the single molecule array (SIMOA) technique. Estimated glomerular filtration rate (eGFR) correlated negatively with CSF GFAP (r = −0.217, p = 0.004) and serum NfL (r = −0.164, p = 0.032). Patients with impaired renal function exhibited higher CSF NfL (p = 0.036) and CSF GFAP (p = 0.026) levels. However, these findings did not remain significant after adjusting for BMI and age. Importantly, in patients with normal renal function, no significant correlations with eGFR and biomarker levels were observed after adjustment. Our findings indicate that serum and CSF concentrations of NfL, GFAP, tTAU, and UCHL1 are not significantly affected by fluctuations in physiological kidney function but emphasize the importance of considering comorbidities in impaired renal function when interpreting biomarker levels. Full article
(This article belongs to the Section Molecular Neurobiology)
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<p>Boxplots displaying median values and interquartile range (IQR) of biomarker concentrations in cerebrospinal fluid (CSF) for normal and impaired renal function (defined as an eGFR under 90 mL/min/1.73 m<sup>2</sup>). For clarity, absolute values are displayed in this figure. For the <span class="html-italic">t</span>-test, log-transformed values were used. CSF NfL (<span class="html-italic">p</span> = 0.036) and CSF GFAP (<span class="html-italic">p</span> = 0.026) concentrations were higher in patients with impaired kidney function. * <span class="html-italic">p &lt;</span> 0.05.</p>
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<p>Boxplots showing median values and interquartile range (IQR) of biomarker concentrations in serum for normal and impaired renal function (defined as an eGFR under 90 mL/min/1.73 m<sup>2</sup>). For clarity, absolute values are displayed in this figure. Following log-transformation, no significant differences were found between the two groups for any of the biomarkers.</p>
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<p>Scatterplots showing the association between kidney function, measured as eGFR CKD-Epi (ml/min/1.73 m<sup>2</sup>), and the log-transformed serum (<b>A</b>) or cerebrospinal fluid (CSF) concentrations (<b>B</b>) with the fitting of a linear regression curve. sNfL (<span class="html-italic">p</span> = 0.032), sGFAP (<span class="html-italic">p</span> = 0.097), sUCHL1 (<span class="html-italic">p</span> = 0.371), stTAU (<span class="html-italic">p</span> = 0.548) cNfL (<span class="html-italic">p</span> = 0.137), cGFAP (<span class="html-italic">p</span> = 0.004), cUCHL1 (<span class="html-italic">p</span> = 0.718), ctTAU (<span class="html-italic">p</span> = 0.644).</p>
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19 pages, 1567 KiB  
Article
No Relation Between Cognitive Impairment, Physical Disability and Serum Biomarkers in a Cohort of Progressive Multiple Sclerosis Patients
by Bartosz Gajewski, Iwona Karlińska, Małgorzata Domowicz, Igor Bednarski, Mariola Świderek-Matysiak and Mariusz Stasiołek
Biomolecules 2025, 15(1), 68; https://doi.org/10.3390/biom15010068 - 6 Jan 2025
Viewed by 705
Abstract
Despite significant efforts, there is still an existing need to identify diagnostic tools that would enable fast and reliable detection of the progressive stage of multiple sclerosis (MS) and help in monitoring the disease course and/or treatment effects. The aim of this prospective [...] Read more.
Despite significant efforts, there is still an existing need to identify diagnostic tools that would enable fast and reliable detection of the progressive stage of multiple sclerosis (MS) and help in monitoring the disease course and/or treatment effects. The aim of this prospective study in a group of people with progressive MS was to determine whether changes in the levels of selected serum biomarkers and in cognitive function may predict disease progression, and therefore refine the decision-making process in the evaluation of MS patients. Forty two (42) patients with progressive MS completed all the study procedures; the mean duration of follow-up was 12.97 months. During the observation period, serum concentration of chitinase-3 like-protein-1 (CHI3L1/YKL-40) decreased significantly in the whole study group (from 4034.95 ± 262.62 to 2866.43 ± 173.37; p = 0.0005), as well as in subgroups of people with secondary progressive and primary progressive MS (SPMS: from 3693.81 ± 388.68 to 2542.76 ± 256.59; p = 0.0207; and PPMS: from 4376.09 ± 353.27 to 3190.09 ± 233.22; p = 0.0089, respectively). A significant worsening of Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) scores was detected in the whole study group (from 1.18 ± 0.14 to 1.34 ± 0.15; p = 0.0331) as well as in the PPMS subgroup (from 1.04 ± 0.18 to 1.26 ± 0.20; p = 0.0216). No correlations between the analyzed molecular parameters or the results of neuropsychological tests and physical disability were observed. In conclusion, an emphasis should be placed on furthering the search for multimodal biomarkers of disease progression, especially in the PMS population, based on simultaneous analysis of several factors, such as blood biomarkers and cognitive profiles. Full article
(This article belongs to the Section Molecular Biomarkers)
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<p>Flowchart of enrollment and follow-up of participants.</p>
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<p>Changes in mean EDSS during study period. Data presented as means (points) with SE (whiskers). Values did not reach statistical significance. EDSS—Expanded Disability Status Scale, PPMS—primary progressive multiple sclerosis, SPMS—secondary progressive multiple sclerosis.</p>
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<p>Changes in serum YKL-40 levels. Data presented as means with standard error (SE). “*” statistical significance <span class="html-italic">p</span> &lt; 0.05. <a href="#app1-biomolecules-15-00068" class="html-app">Figure S1A,B</a> regarding changes in serum levels of NfL and CXCL-13, respectively, are included in <a href="#app1-biomolecules-15-00068" class="html-app">Supplementary Materials</a>. PPMS—primary progressive multiple sclerosis, SPMS—secondary progressive multiple sclerosis, NfL—neurofilament light chain, CXCL-13—C-X-C Motif Chemokine Ligand 13, YKL-40—chitanse-3 like-protein-1.</p>
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<p>(<b>A</b>–<b>C</b>): Correlations between EDSS and serum biomarkers change. Values did not reach statistical significance. (<b>A</b>) PMS; (<b>B</b>) PPMS and (<b>C</b>) SPMS. EDSS—Expanded Disability Status Scale, PMS—progressive multiple sclerosis, PPMS—primary progressive multiple sclerosis, SPMS—secondary progressive multiple sclerosis, NfL—neurofilament light chain, CXCL-13—C-X-C Motif Chemokine Ligand 13, YKL-40—chitanse-3 like-protein-1.</p>
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<p>Generalized linear model with repeated measures for BICAMS (<b>A</b>), BVMT-R (<b>B</b>), CVLT (<b>C</b>), SDMT (<b>D</b>), VFT (<b>E</b>,<b>F</b>), and SCWT (<b>G</b>,<b>H</b>). Data presented as means with standard error (SE). Values did not reach statistical significance. As previously, blue indicates PPMS group and red indicates SPMS group. PPMS—primary progressive multiple sclerosis, SPMS—secondary progressive multiple sclerosis.</p>
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<p>Generalized linear model with repeated measures for BICAMS (<b>A</b>), BVMT-R (<b>B</b>), CVLT (<b>C</b>), SDMT (<b>D</b>), VFT (<b>E</b>,<b>F</b>), and SCWT (<b>G</b>,<b>H</b>). Data presented as means with standard error (SE). Values did not reach statistical significance. As previously, blue indicates PPMS group and red indicates SPMS group. PPMS—primary progressive multiple sclerosis, SPMS—secondary progressive multiple sclerosis.</p>
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11 pages, 1653 KiB  
Article
Neurofilament Light Chain Levels in Serum and Cerebrospinal Fluid Do Not Correlate with Survival Times in Patients with Prion Disease
by Mika Shimamura, Kong Weijie, Toshiaki Nonaka, Koki Kosami, Ryusuke Ae, Koji Fujita, Taiki Matsubayashi, Tadashi Tsukamoto, Nobuo Sanjo and Katsuya Satoh
Biomolecules 2025, 15(1), 8; https://doi.org/10.3390/biom15010008 - 25 Dec 2024
Viewed by 612
Abstract
Prion diseases, including Creutzfeldt–Jakob disease (CJD), are deadly neurodegenerative disorders characterized by the buildup of abnormal prion proteins in the brain. This accumulation disrupts neuronal functions, leading to the rapid onset of psychiatric symptoms, ataxia, and cognitive decline. The urgency of timely diagnosis [...] Read more.
Prion diseases, including Creutzfeldt–Jakob disease (CJD), are deadly neurodegenerative disorders characterized by the buildup of abnormal prion proteins in the brain. This accumulation disrupts neuronal functions, leading to the rapid onset of psychiatric symptoms, ataxia, and cognitive decline. The urgency of timely diagnosis for effective treatment necessitates the identification of strongly correlated biomarkers in bodily fluids, which makes our research crucial. In this study, we employed a fully automated multiplex ELISA (Ella®) to measure the concentrations of 14-3-3 protein, total tau protein, and neurofilament light chain (NF-L) in cerebrospinal fluid (CSF) and serum samples from patients with prion disease and analyzed their link to disease prognosis. However, in North American and European cases, we did not confirm a correlation between NF-L levels and survival time. This discrepancy is believed to stem from differences in treatment policies and measurement methods between Japan and the United States. Nonetheless, our findings suggest that NF-L concentrations could be an early diagnostic marker for CJD patients with further enhancements. The potential impact of our findings on the early diagnosis of CJD patients is significant. Future research should focus on increasing the number of sCJD cases studied in Japan and gathering additional evidence using next-generation measurement techniques. Full article
(This article belongs to the Section Molecular Medicine)
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<p>Correlation between disease duration and CSF/serum NF-L (<b>A</b>). Correlation between disease duration and CSF NF-L (R<sup>2</sup> = 0.0042, Pearson’s CC = 0.0064) (<b>B</b>). Correlation between disease duration and serum NF-L (R<sup>2</sup> = 0.0022, Pearson’s CC = 0.047) (<b>C</b>). Correlation between CSF and serum NF-L levels (R<sup>2</sup> = 0.3298, Pearson’s CC = 0.576).</p>
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<p>Correlation between duration of illness from onset to akinetic mutism and NF-L concentration (<b>A</b>), CSF c (<b>B</b>), serum (R<sup>2</sup> = 3 × 10<sup>5</sup>, Pearson’s CC = −0.005) (<b>C</b>), and average NF-L in CSF and serum (median ± S.D.).</p>
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<p>Correlation between cerebrospinal fluid NF-L/serum NF-L levels and disease duration (short-term vs. long-term). (<b>A</b>) and (<b>B</b>): 0-20 months (short-term). (<b>A</b>): R<sup>2</sup> = 0.0189; Pearson’s CC = 0.137. (<b>B</b>): R<sup>2</sup> = 0.0397, Pearson’s CC = −0.0199. (<b>C</b>) and (<b>D</b>) ≥20 months (long-term). (<b>C</b>): R<sup>2</sup> = 0.006, Pearson’s CC = 0.077. (<b>D</b>): R<sup>2</sup> = 0.0003; Pearson’s CC = −0.016. (<b>E</b>) Correlation between CSF NF-L levels and serum NF-L levels in the short term (0–20 months) (R<sup>2</sup> = 0.053, Pearson’s CC = 0.2303).</p>
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<p>Relationship between age at onset and CSF NF-L. (<b>A</b>,<b>B</b>) Age at onset and NF-L concentration ((<b>A</b>): CSF; (<b>B</b>): Serum). (<b>C</b>,<b>D</b>) Correlation between age at onset and CSF/serum NF-L<sup>©</sup>, and correlation between age at onset and CSF NF-L (R<sup>2</sup> = 0.0184, Pearson’s CC = 0.135). (<b>D</b>) Correlation between age at onset and serum NF-L (R<sup>2</sup> = 0.0557, Pearson’s CC = 0.236).</p>
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16 pages, 684 KiB  
Review
Neurofilament Light Protein as a Biomarker in Severe Mental Disorders: A Systematic Review
by Rosanna Squitti, Antonio Fiorenza, Alessandra Martinelli, Viviana Brembati, Daniela Crescenti, Mauro Rongioletti and Roberta Ghidoni
Int. J. Mol. Sci. 2025, 26(1), 61; https://doi.org/10.3390/ijms26010061 - 25 Dec 2024
Viewed by 920
Abstract
Severe mental disorders (SMDs), such as schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD), are heterogeneous psychiatric diseases that impose a significant societal burden due to their chronic disabling nature. There are no objective and reliable diagnostic tests for SMDs; thus, [...] Read more.
Severe mental disorders (SMDs), such as schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD), are heterogeneous psychiatric diseases that impose a significant societal burden due to their chronic disabling nature. There are no objective and reliable diagnostic tests for SMDs; thus, there is an urgent need for specific biomarkers to improve diagnosis, treatment, and resource allocation. Neurofilaments, found in cerebrospinal fluid and blood, offer reliable diagnostic and prognostic potential. This review discusses the link between neurofilament light chain (NfL) involvement in psychiatric and neurodegenerative diseases and gives insights into the diagnostic and prognostic value of NfL in SMDs. This systematic review searched PubMed, Scopus, and Web of Science databases to answer the research question “Are NfL levels higher in individuals with SMDs compared to healthy controls?” using terms related to neurofilament, SMDs, SZ, BD, and depression. Of 8577 initial papers, 115 were relevant. After exclusions and manual additions, 17 articles were included. Studies indicate elevated NfL levels in SMDs compared to healthy controls, suggesting its potential as a biomarker for SMDs and for distinguishing neurodegenerative diseases from psychiatric disorders. However, further longitudinal research is needed to confirm its reliability for differential diagnosis, disease prediction, and treatment assessment in psychiatry. Full article
(This article belongs to the Section Molecular Neurobiology)
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<p>PRISMA flow diagram showing the inclusion and exclusion process of relevant studies. Abbreviations: n, numbers; SMDs, severe mental disorders.</p>
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16 pages, 943 KiB  
Article
Neurological Biomarker Profiles in Royal Canadian Air Force (RCAF) Pilots and Aircrew
by Shawn G. Rhind, Maria Y. Shiu, Oshin Vartanian, Shamus Allen, Miriam Palmer, Joel Ramirez, Fuqiang Gao, Christopher J. M. Scott, Meissa F. Homes, Gary Gray, Sandra E. Black and Joan Saary
Brain Sci. 2024, 14(12), 1296; https://doi.org/10.3390/brainsci14121296 - 23 Dec 2024
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Abstract
Background/Objectives: Military aviators can be exposed to extreme physiological stressors, including decompression stress, G-forces, as well as intermittent hypoxia and/or hyperoxia, which may contribute to neurobiological dysfunction/damage. This study aimed to investigate the levels of neurological biomarkers in military aviators to assess the [...] Read more.
Background/Objectives: Military aviators can be exposed to extreme physiological stressors, including decompression stress, G-forces, as well as intermittent hypoxia and/or hyperoxia, which may contribute to neurobiological dysfunction/damage. This study aimed to investigate the levels of neurological biomarkers in military aviators to assess the potential risk of long-term brain injury and neurodegeneration. Methods: This cross-sectional study involved 48 Canadian Armed Forces (CAF) aviators and 48 non-aviator CAF controls. Plasma samples were analyzed for biomarkers of glial activation (GFAP), axonal damage (NF-L, pNF-H), oxidative stress (PRDX-6), and neurodegeneration (T-tau), along with S100b, NSE, and UCHL-1. The biomarker concentrations were quantified using multiplexed immunoassays. Results: The aviators exhibited significantly elevated levels of GFAP, NF-L, PRDX-6, and T-tau compared to the CAF controls (p < 0.001), indicating increased glial activation, axonal injury, and oxidative stress. Trends toward higher levels of S100b, NSE, and UCHL-1 were observed but were not statistically significant. The elevated biomarker levels suggest cumulative brain damage, raising concerns about potential long-term neurological impairments. Conclusions: Military aviators are at increased risk for neurobiological injury, including glial and axonal damage, oxidative stress, and early neurodegeneration. These findings emphasize the importance of proactive monitoring and further research to understand the long-term impacts of high-altitude flight on brain health and to develop strategies for mitigating cognitive decline and neurodegenerative risks in this population. Full article
(This article belongs to the Section Molecular and Cellular Neuroscience)
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<p>Neurological biomarker profiles in plasma from CAF <span class="html-italic">aviators</span> (pilots and flight crew; red dots, <span class="html-italic">n</span> = 48) versus healthy <span class="html-italic">controls</span> (blue dots, <span class="html-italic">n</span> = 48), plotted for S100b (<b>A</b>), neuron-specific enolase (NSE; (<b>B</b>)), glial fibrillary acidic protein (GFAP; (<b>C</b>)), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1; (<b>D</b>)), neurofilament light (NF-L; (<b>E</b>)), phosphorylated neurofilament heavy (pNF-H; (<b>F</b>)), peroxiredoxin 6 (PRDX-6; (<b>G</b>)), and total tau (T-tau; (<b>H</b>)). Each dot represents the biomarker concentration (as indicated) for an individual subject; solid lines show medians with interquartile ranges. Significant group differences (<span class="html-italic">p</span> &lt; 0.05) in biomarker values by <span class="html-italic">Mann–Whitney U-test</span> are displayed for each marker, corrected for multiple comparisons at FDR = 0.05.</p>
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15 pages, 3307 KiB  
Article
Exposure to Cadmium and Other Trace Elements Among Individuals with Mild Cognitive Impairment
by Teresa Urbano, Marco Vinceti, Chiara Carbone, Lauren A. Wise, Marcella Malavolti, Manuela Tondelli, Roberta Bedin, Giulia Vinceti, Alessandro Marti, Annalisa Chiari, Giovanna Zamboni, Bernhard Michalke and Tommaso Filippini
Toxics 2024, 12(12), 933; https://doi.org/10.3390/toxics12120933 - 22 Dec 2024
Viewed by 941
Abstract
Background: A limited number of studies have investigated the role of environmental chemicals in the etiology of mild cognitive impairment (MCI). We performed a cross-sectional study of the association between exposure to selected trace elements and the biomarkers of cognitive decline. Methods: During [...] Read more.
Background: A limited number of studies have investigated the role of environmental chemicals in the etiology of mild cognitive impairment (MCI). We performed a cross-sectional study of the association between exposure to selected trace elements and the biomarkers of cognitive decline. Methods: During 2019–2021, we recruited 128 newly diagnosed patients with MCI from two Neurology Clinics in Northern Italy, i.e., Modena and Reggio Emilia. At baseline, we measured serum and cerebrospinal fluid (CSF) concentrations of cadmium, copper, iron, manganese, and zinc using inductively coupled plasma mass spectrometry. With immuno-enzymatic assays, we estimated concentrations of β-amyloid 1-40, β-amyloid 1-42, Total Tau and phosphorylated Tau181 proteins, neurofilament light chain (NfL), and the mini-mental state examination (MMSE) to assess cognitive status. We used spline regression to explore the shape of the association between exposure and each endpoint, adjusted for age at diagnosis, educational attainment, MMSE, and sex. Results: In analyses between the serum and CSF concentrations of trace metals, we found monotonic positive correlations between copper and zinc, while an inverse association was observed for cadmium. Serum cadmium concentrations were inversely associated with amyloid ratio and positively associated with Tau proteins. Serum iron concentrations showed the opposite trend, while copper, manganese, and zinc displayed heterogeneous non-linear associations with amyloid ratio and Tau biomarkers. Regarding CSF exposure biomarkers, only cadmium consistently showed an inverse association with amyloid ratio, while iron was positively associated with Tau. Cadmium concentrations in CSF were not appreciably associated with serum NfL levels, while we observed an inverted U-shaped association with CSF NfL, similar to that observed for copper. In CSF, zinc was the only trace element positively associated with NfL at high concentrations. Conclusions: In this cross-sectional study, high serum cadmium concentrations were associated with selected biomarkers of cognitive impairment. Findings for the other trace elements were difficult to interpret, showing complex and inconsistent associations with the neurodegenerative endpoints examined. Full article
(This article belongs to the Special Issue Cadmium and Trace Elements Toxicity)
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<p>Study flowchart. Abbreviations: CSF, cerebrospinal fluid; SCD, subjective cognitive decline (SCD).</p>
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<p>Violin plots distribution of trace element concentrations in serum and cerebrospinal fluid (CSF) according to sex (M, males; F, females). MCI, serum n = 89; CSF n = 45. Abbreviations: Cd, cadmium; Cu, copper; Fe, iron; MCI, mild cognitive impairment; Mn, manganese; NfL, neurofilament light chain; SCD, subjective cognitive decline; Zn, zinc.</p>
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<p>Spline regression analysis of the association between trace element concentration in serum and cerebrospinal fluid among patients with mild cognitive impairment. The solid line indicates the multivariable analysis; the shaded area represents upper and lower confidence interval limits. The dashed line represents association assuming linearity. Diamonds represent individual observations (n = 45). Abbreviations: Cd, cadmium; CSF, cerebrospinal fluid; Cu, copper; Fe, iron; Mn, manganese; NfL, neurofilament light chain; Zn, zinc.</p>
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<p>Spline regression analysis of the association between trace element concentration in serum (dark blue) and cerebrospinal fluid (CSF-light blue) with serum (<b>A</b>) and CSF neurofilament light (NfL) concentrations (<b>B</b>) among patients with mild cognitive impairment. The solid line indicates the multivariable analysis; the shaded area represents the upper and lower confidence interval limits. The dashed line represents the association assuming linearity. Diamonds represent individual observations (serum n = 89; CSF n = 45). Abbreviations: Cd, cadmium; Cu, copper; Fe, iron; MMSE, mini-mental state examination; Mn, manganese; Zn, zinc.</p>
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<p>Spline regression analysis of the association between trace element concentration in serum (dark green) and cerebrospinal fluid (CSF—light green) with CSF concentration of amyloid ratio (<b>A</b>), Total Tau (<b>B</b>) and phosphorylated Tau (p-Tau181) protein (<b>C</b>) among patients with mild cognitive impairment. The solid line indicates the multivariable analysis; the shaded area represents the upper and lower confidence interval limits. The dashed line represents the association assuming linearity. Diamonds represent individual observations (serum n = 89; CSF n = 45). Red lines represent laboratory cut-offs (&gt;0.069 for amyloid ratio; &lt;400 pg/mL for Total Tau; &lt;56.5 pg/mL for p-Tau181). Abbreviations: Cd, cadmium; Cu, copper; Fe, iron; MMSE, mini-mental state examination; Mn, manganese; Zn, zinc.</p>
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