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Biomarkers and Molecular Methodologies in Neurodegenerative Diseases Diagnostic

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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pathology, Diagnostics, and Therapeutics".

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 43905

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Special Issue Editors

Dr. Matthias Schmitz

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Guest Editor

Department of Neurology, University Medicine Goettingen, Göttingen, Germany
Interests: dementia; neurodegeneration; protein misfolding; biomarker research; diagnostic of prion diseases

Dr. Anna Villar-Piqué

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Guest Editor

Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain
Interests: dementia; prion diseases; neurodegeneration; diagnostic test; protein misfolding

Special Issue Information

Dear Colleagues,

Neurodegenerative diseases (NDs) are characterized by a progressive deterioration of the nervous system causing psychiatric and motor disfunctions. There is no treatment that can cure or effectively revert the symptoms of NDs. Because they affect mainly, but not exclusively, the elderly, the increase in life expectancy worldwide is rapidly raising the prevalence of NDs.

A major challenge in the field is the differential diagnosis of NDs at the time of disease onset, especially for those disorders characterized by phychiatric symptmatology. The wide clinical overlap among some NDs, the heterogenity of their clinical presentation, the difficulty of cognitive evaluation, and the inacurracy of most biochemical tests preclude or delay the achievement of a definite diagnosis, particularly in the absence of genetic mutations.

This Special Issue will provide a comprehensive update on the latest findings regarding biomarkers and molecular methodologies targeted to improve the diagnosis of NDs. The focus will be on the clinical application of protein biomarkers for diagnosis, prognosis, and treatment prediction. Original research papers and review articles that describe advances in biomarker accuracy and molecular methodologies targeted to improve the diagnostics of NDs are welcome.

Dr. Matthias Schmitz
Dr. Anna Villar-Piqué
Guest Editors

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Keywords

neurodegenetive diseases
movement disorders
dementia
neuroinflamation
body fluids
biomarker
molecular methods
neuroimaging
diagnosis
prognosis

Published Papers (10 papers)

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Research

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14 pages, 1141 KiB

Open AccessArticle

Thermodynamic Signatures of Blood Plasma Proteome in Neurodegenerative Pathologies

by Avgustina Danailova, Svetla Todinova, Lidia Gartcheva, Desislava Bogdanova, Elena Zlatareva, Nikolay Kalaydzhiev, Ivan Milanov, Sashka Krumova and Stefka G. Taneva

Int. J. Mol. Sci. 2023, 24(1), 789; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms24010789 - 02 Jan 2023

Viewed by 1674

Abstract

Discovery of diagnostic biomarkers for age-related neurodegenerative pathologies (NDDs) is essential for accurate diagnosis, following disease progression and drug development. Blood plasma and blood cells are important peripheral sources for NDDs’ biomarkers that, although present in lower concentrations than in cerebrospinal fluid, would allow noninvasive diagnostics. To identify new biomarkers for Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS), in this work we have evaluated the modifications in the thermodynamic behavior of blood plasma proteome exploring differential scanning calorimetry. The plasma thermodynamics reflected the complexity and heterogeneity of the two pathologies. The unfolding temperature of the most abundant plasma protein albumin and the weighted average center of the calorimetric profile appeared as the two thermodynamic signatures that reflected modifications of the plasma proteome, i.e., strong thermal stabilization of albumin and plasma proteins’ interaction network, related to both pathologies. Based on those two signatures, both PD and ALS patients were stratified in two sets, except several cases with thermodynamic parameters that strongly differed from those of the calorimetric sets. Along with modifications of the plasma thermodynamic behavior, we found altered globulin levels in all PD and ALS patients’ plasma (higher level of α- and β-globulin fractions and lower level of γ-globulin fraction than the respective reference values) employing capillary electrophoresis. The presented results reveal the potential of calorimetry to indirectly identify NDDs’ biomarkers in blood plasma. Full article

(This article belongs to the Special Issue Biomarkers and Molecular Methodologies in Neurodegenerative Diseases Diagnostic)

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14 pages, 2195 KiB

Open AccessArticle

Analysis of the Biomarkers for Neurodegenerative Diseases in Aged Progranulin Deficient Mice

by Xiangli Zhao, Sadaf Hasan, Benjamin Liou, Yi Lin, Ying Sun and Chuanju Liu

Int. J. Mol. Sci. 2022, 23(2), 629; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms23020629 - 06 Jan 2022

Cited by 2 | Viewed by 2475

Abstract

Neurodegenerative diseases are debilitating impairments that affect millions of people worldwide and are characterized by progressive degeneration of structure and function of the central or peripheral nervous system. Effective biomarkers for neurodegenerative diseases can be used to improve the diagnostic workup in the clinic as well as facilitate the development of effective disease-modifying therapies. Progranulin (PGRN) has been reported to be involved in various neurodegenerative disorders. Hence, in the current study we systematically compared the inflammation and accumulation of typical neurodegenerative disease markers in the brain tissue between PGRN knockout (PGRN KO) and wildtype (WT) mice. We found that PGRN deficiency led to significant neuron loss as well as activation of microglia and astrocytes in aged mice. Several characteristic neurodegenerative markers, including α-synuclein, TAR DNA-binding protein 43 (TDP-43), Tau, and β-amyloid, were all accumulated in the brain of PGRN-deficient mice as compared to WT mice. Moreover, higher aggregation of lipofuscin was observed in the brain tissue of PGRN-deficient mice compared with WT mice. In addition, the autophagy was also defective in the brain of PGRN-deficient mice, indicated by the abnormal expression level of autophagy marker LC3-II. Collectively, comprehensive assays support the idea that PGRN plays an important role during the development of neurodegenerative disease, indicating that PGRN might be a useful biomarker for neurodegenerative diseases in clinical settings. Full article

(This article belongs to the Special Issue Biomarkers and Molecular Methodologies in Neurodegenerative Diseases Diagnostic)

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18 pages, 2204 KiB

Open AccessArticle

Morphometry and Stiffness of Red Blood Cells—Signatures of Neurodegenerative Diseases and Aging

by Velichka Strijkova-Kenderova, Svetla Todinova, Tonya Andreeva, Desislava Bogdanova, Ariana Langari, Avgustina Danailova, Sashka Krumova, Elena Zlatareva, Nikolay Kalaydzhiev, Ivan Milanov and Stefka G. Taneva

Int. J. Mol. Sci. 2022, 23(1), 227; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms23010227 - 25 Dec 2021

Cited by 11 | Viewed by 2998

Abstract

Human red blood cells (RBCs) are unique cells with the remarkable ability to deform, which is crucial for their oxygen transport function, and which can be significantly altered under pathophysiological conditions. Here we performed ultrastructural analysis of RBCs as a peripheral cell model, looking for specific signatures of the neurodegenerative pathologies (NDDs)—Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS) and Alzheimer’s disease (AD), utilizing atomic force (AFM) and conventional optical (OM) microscopy. We found significant differences in the morphology and stiffness of RBCs isolated from patients with the selected NDDs and those from healthy individuals. Neurodegenerative pathologies’ RBCs are characterized by a reduced abundance of biconcave discoid shape, lower surface roughness and a higher Young’s modulus, compared to healthy cells. Although reduced, the biconcave is still the predominant shape in ALS and AD cells, while the morphology of PD is dominated by crenate cells. The features of RBCs underwent a marked aging-induced transformation, which followed different aging pathways for NDDs and normal healthy states. It was found that the diameter, height and volume of the different cell shape types have different values for NDDs and healthy cells. Common and specific morphological signatures of the NDDs were identified. Full article

(This article belongs to the Special Issue Biomarkers and Molecular Methodologies in Neurodegenerative Diseases Diagnostic)

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13 pages, 1439 KiB

Open AccessArticle

Cerebrospinal Fluid Mitochondrial DNA in Rapid and Slow Progressive Forms of Alzheimer’s Disease

by Petar Podlesniy, Franc Llorens, Margalida Puigròs, Nuria Serra, Diego Sepúlveda-Falla, Christian Schmidt, Peter Hermann, Inga Zerr and Ramon Trullas

Int. J. Mol. Sci. 2020, 21(17), 6298; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21176298 - 31 Aug 2020

Cited by 15 | Viewed by 2778

Abstract

Alzheimer’s type dementia (AD) exhibits clinical heterogeneity, as well as differences in disease progression, as a subset of patients with a clinical diagnosis of AD progresses more rapidly (rpAD) than the typical AD of slow progression (spAD). Previous findings indicate that low cerebrospinal fluid (CSF) content of cell-free mitochondrial DNA (cf-mtDNA) precedes clinical signs of AD. We have now investigated the relationship between cf-mtDNA and other biomarkers of AD to determine whether a particular biomarker profile underlies the different rates of AD progression. We measured the content of cf-mtDNA, beta-amyloid peptide 1–42 (Aβ), total tau protein (t-tau) and phosphorylated tau (p-tau) in the CSF from a cohort of 95 subjects consisting of 49 controls with a neurologic disorder without dementia, 30 patients with a clinical diagnosis of spAD and 16 patients with rpAD. We found that 37% of controls met at least one AD biomarker criteria, while 53% and 44% of subjects with spAD and rpAD, respectively, did not fulfill the two core AD biomarker criteria: high t-tau and low Aβ in CSF. In the whole cohort, patients with spAD, but not with rpAD, showed a statistically significant 44% decrease of cf-mtDNA in CSF compared to control. When the cohort included only subjects selected by Aβ and t-tau biomarker criteria, the spAD group showed a larger decrease of cf-mtDNA (69%), whereas in the rpAD group cf-mtDNA levels remained unaltered. In the whole cohort, the CSF levels of cf-mtDNA correlated positively with Aβ and negatively with p-tau. Moreover, the ratio between cf-mtDNA and p-tau increased the sensitivity and specificity of spAD diagnosis up to 93% and 94%, respectively, in the biomarker-selected cohort. These results show that the content of cf-mtDNA in CSF correlates with the earliest pathological markers of the disease, Aβ and p-tau, but not with the marker of neuronal damage t-tau. Moreover, these findings confirm that low CSF content of cf-mtDNA is a biomarker for the early detection of AD and support the hypothesis that low cf-mtDNA, together with low Aβ and high p-tau, constitute a distinctive CSF biomarker profile that differentiates spAD from other neurological disorders. Full article

(This article belongs to the Special Issue Biomarkers and Molecular Methodologies in Neurodegenerative Diseases Diagnostic)

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Review

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27 pages, 1750 KiB

Open AccessReview

Tau as a Biomarker of Neurodegeneration

by Sarah Holper, Rosie Watson and Nawaf Yassi

Int. J. Mol. Sci. 2022, 23(13), 7307; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms23137307 - 30 Jun 2022

Cited by 29 | Viewed by 5110

Abstract

Less than 50 years since tau was first isolated from a porcine brain, its detection in femtolitre concentrations in biological fluids is revolutionizing the diagnosis of neurodegenerative diseases. This review highlights the molecular and technological advances that have catapulted tau from obscurity to the forefront of biomarker diagnostics. Comprehensive updates are provided describing the burgeoning clinical applications of tau as a biomarker of neurodegeneration. For the clinician, tau not only enhances diagnostic accuracy, but holds promise as a predictor of clinical progression, phenotype, and response to drug therapy. For patients living with neurodegenerative disorders, characterization of tau dysregulation could provide much-needed clarity to a notoriously murky diagnostic landscape. Full article

(This article belongs to the Special Issue Biomarkers and Molecular Methodologies in Neurodegenerative Diseases Diagnostic)

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17 pages, 1065 KiB

Open AccessReview

Biomarkers of Dementia with Lewy Bodies: Differential Diagnostic with Alzheimer’s Disease

by Olivier Bousiges and Frédéric Blanc

Int. J. Mol. Sci. 2022, 23(12), 6371; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms23126371 - 07 Jun 2022

Cited by 10 | Viewed by 6029

Abstract

Dementia with Lewy Bodies (DLB) is a common form of cognitive neurodegenerative disease. Only one third of patients are correctly diagnosed due to the clinical similarity mainly with Alzheimer’s disease (AD). In this review, we evaluate the interest of different biomarkers: cerebrospinal fluid (CSF), brain MRI, FP-CIT SPECT, MIBG SPECT, PET by focusing more specifically on differential diagnosis between DLB and AD. FP-CIT SPECT is of high interest to discriminate DLB and AD, but not at the prodromal stage (i.e., MCI). MIBG SPECT with decreased cardiac sympathetic activity, perfusion SPECT with occipital hypoperfusion, FDG PET with occipital hypometabolism and cingulate island signs are of interest at the dementia stage but with a lower validity. Brain MRI has shown differences in group study with lower grey matter concentration of the Insula in prodromal DLB, but its interest in clinical routines is not demonstrated. Concerning CSF biomarkers, many studies have already examined the relevance of AD biomarkers but also alpha-synuclein assays in DLB, so we will focus as comprehensively as possible on other biomarkers (especially those that do not appear to be directly related to synucleinopathy) that may be of interest in the differential diagnosis between AD and DLB. Furthermore, we would like to highlight the growing interest in CSF synuclein RT-QuIC, which seems to be an excellent discrimination tool but its application in clinical routine remains to be demonstrated, given the non-automation of the process. Full article

(This article belongs to the Special Issue Biomarkers and Molecular Methodologies in Neurodegenerative Diseases Diagnostic)

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31 pages, 9425 KiB

Open AccessReview

Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

by Koji Kamagata, Christina Andica, Ayumi Kato, Yuya Saito, Wataru Uchida, Taku Hatano, Matthew Lukies, Takashi Ogawa, Haruka Takeshige-Amano, Toshiaki Akashi, Akifumi Hagiwara, Shohei Fujita and Shigeki Aoki

Int. J. Mol. Sci. 2021, 22(10), 5216; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms22105216 - 14 May 2021

Cited by 32 | Viewed by 5434

Abstract

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases. Full article

(This article belongs to the Special Issue Biomarkers and Molecular Methodologies in Neurodegenerative Diseases Diagnostic)

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25 pages, 2392 KiB

Open AccessReview

Alteration of Iron Concentration in Alzheimer’s Disease as a Possible Diagnostic Biomarker Unveiling Ferroptosis

by Eleonora Ficiarà, Zunaira Munir, Silvia Boschi, Maria Eugenia Caligiuri and Caterina Guiot

Int. J. Mol. Sci. 2021, 22(9), 4479; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms22094479 - 25 Apr 2021

Cited by 18 | Viewed by 4127

Abstract

Proper functioning of all organs, including the brain, requires iron. It is present in different forms in biological fluids, and alterations in its distribution can induce oxidative stress and neurodegeneration. However, the clinical parameters normally used for monitoring iron concentration in biological fluids (i.e., serum and cerebrospinal fluid) can hardly detect the quantity of circulating iron, while indirect measurements, e.g., magnetic resonance imaging, require further validation. This review summarizes the mechanisms involved in brain iron metabolism, homeostasis, and iron imbalance caused by alterations detectable by standard and non-standard indicators of iron status. These indicators for iron transport, storage, and metabolism can help to understand which biomarkers can better detect iron imbalances responsible for neurodegenerative diseases. Full article

(This article belongs to the Special Issue Biomarkers and Molecular Methodologies in Neurodegenerative Diseases Diagnostic)

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34 pages, 913 KiB

Open AccessReview

Genetic Architecture and Molecular, Imaging and Prodromic Markers in Dementia with Lewy Bodies: State of the Art, Opportunities and Challenges

by Romina Combi, Maria Salsone, Chiara Villa and Luigi Ferini-Strambi

Int. J. Mol. Sci. 2021, 22(8), 3960; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms22083960 - 12 Apr 2021

Viewed by 2893

Abstract

Dementia with Lewy bodies (DLB) is one of the most common causes of dementia and belongs to the group of α-synucleinopathies. Due to its clinical overlap with other neurodegenerative disorders and its high clinical heterogeneity, the clinical differential diagnosis of DLB from other similar disorders is often difficult and it is frequently underdiagnosed. Moreover, its genetic etiology has been studied only recently due to the unavailability of large cohorts with a certain diagnosis and shows genetic heterogeneity with a rare contribution of pathogenic mutations and relatively common risk factors. The rapid increase in the reported cases of DLB highlights the need for an easy, efficient and accurate diagnosis of the disease in its initial stages in order to halt or delay the progression. The currently used diagnostic methods proposed by the International DLB consortium rely on a list of criteria that comprises both clinical observations and the use of biomarkers. Herein, we summarize the up-to-now reported knowledge on the genetic architecture of DLB and discuss the use of prodromal biomarkers as well as recent promising candidates from alternative body fluids and new imaging techniques. Full article

(This article belongs to the Special Issue Biomarkers and Molecular Methodologies in Neurodegenerative Diseases Diagnostic)

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12 pages, 265 KiB

Open AccessReview

Machine Learning and Novel Biomarkers for the Diagnosis of Alzheimer’s Disease

by Chun-Hung Chang, Chieh-Hsin Lin and Hsien-Yuan Lane

Int. J. Mol. Sci. 2021, 22(5), 2761; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms22052761 - 09 Mar 2021

Cited by 80 | Viewed by 9118

Abstract

Background: Alzheimer’s disease (AD) is a complex and severe neurodegenerative disease that still lacks effective methods of diagnosis. The current diagnostic methods of AD rely on cognitive tests, imaging techniques and cerebrospinal fluid (CSF) levels of amyloid-β1-42 (Aβ42), total tau protein and hyperphosphorylated tau (p-tau). However, the available methods are expensive and relatively invasive. Artificial intelligence techniques like machine learning tools have being increasingly used in precision diagnosis. Methods: We conducted a meta-analysis to investigate the machine learning and novel biomarkers for the diagnosis of AD. Methods: We searched PubMed, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews for reviews and trials that investigated the machine learning and novel biomarkers in diagnosis of AD. Results: In additional to Aβ and tau-related biomarkers, biomarkers according to other mechanisms of AD pathology have been investigated. Neuronal injury biomarker includes neurofiliament light (NFL). Biomarkers about synaptic dysfunction and/or loss includes neurogranin, BACE1, synaptotagmin, SNAP-25, GAP-43, synaptophysin. Biomarkers about neuroinflammation includes sTREM2, and YKL-40. Besides, d-glutamate is one of coagonists at the NMDARs. Several machine learning algorithms including support vector machine, logistic regression, random forest, and naïve Bayes) to build an optimal predictive model to distinguish patients with AD from healthy controls. Conclusions: Our results revealed machine learning with novel biomarkers and multiple variables may increase the sensitivity and specificity in diagnosis of AD. Rapid and cost-effective HPLC for biomarkers and machine learning algorithms may assist physicians in diagnosing AD in outpatient clinics. Full article

(This article belongs to the Special Issue Biomarkers and Molecular Methodologies in Neurodegenerative Diseases Diagnostic)

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