Готові списки джерел за темами / Biomarkers of neurodegenerative disease

Добірка наукової літератури з теми "Biomarkers of neurodegenerative disease"

Автор: Grafiati
Опубліковано: 4 вересня 2022

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Статті в журналах з теми "Biomarkers of neurodegenerative disease":

1

Raghunathan, Rekha, Kathleen Turajane, and Li Chin Wong. "Biomarkers in Neurodegenerative Diseases: Proteomics Spotlight on ALS and Parkinson’s Disease." International Journal of Molecular Sciences 23, no. 16 (August 18, 2022): 9299. http://dx.doi.org/10.3390/ijms23169299.

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Neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD) are both characterized by pathogenic protein aggregates that correlate with the progressive degeneration of neurons and the loss of behavioral functions. Both diseases lack biomarkers for diagnosis and treatment efficacy. Proteomics is an unbiased quantitative tool capable of the high throughput quantitation of thousands of proteins from minimal sample volumes. We review recent proteomic studies in human tissues, plasma, cerebrospinal fluid (CSF), and exosomes in ALS and PD that identify proteins with potential utility as biomarkers. Further, we review disease-related post-translational modifications in key proteins TDP43 in ALS and α-synuclein in PD studies, which may serve as biomarkers. We compare relative and absolute quantitative proteomic approaches in key biomarker studies in ALS and PD and discuss recent technological advancements which may identify suitable biomarkers for the early-diagnosis treatment efficacy of these diseases.
2

Martínez-Iglesias, Olaia, Vinogran Naidoo, Natalia Cacabelos, and Ramón Cacabelos. "Epigenetic Biomarkers as Diagnostic Tools for Neurodegenerative Disorders." International Journal of Molecular Sciences 23, no. 1 (December 21, 2021): 13. http://dx.doi.org/10.3390/ijms23010013.

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Epigenetics is the study of heritable changes in gene expression that occur without alterations to the DNA sequence, linking the genome to its surroundings. The accumulation of epigenetic alterations over the lifespan may contribute to neurodegeneration. The aim of the present study was to identify epigenetic biomarkers for improving diagnostic efficacy in patients with neurodegenerative diseases. We analyzed global DNA methylation, chromatin remodeling/histone modifications, sirtuin (SIRT) expression and activity, and the expression of several important neurodegeneration-related genes. DNA methylation, SIRT expression and activity and neuregulin 1 (NRG1), microtubule-associated protein tau (MAPT) and brain-derived neurotrophic factor (BDNF) expression were reduced in buffy coat samples from patients with neurodegenerative disorders. Our data suggest that these epigenetic biomarkers may be useful in clinical practical for the diagnosis, surveillance, and prognosis of disease activity in patients with neurodegenerative diseases.
3

Miller, Elżbieta, Agnieszka Morel, Luciano Saso, and Joanna Saluk. "Isoprostanes and Neuroprostanes as Biomarkers of Oxidative Stress in Neurodegenerative Diseases." Oxidative Medicine and Cellular Longevity 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/572491.

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Accumulating data shows that oxidative stress plays a crucial role in neurodegenerative disorders. The literature data indicate thatin vivoor postmortem cerebrospinal fluid and brain tissue levels of F2-isoprostanes (F2-IsoPs) especially F4-neuroprotanes (F4-NPs) are significantly increased in some neurodegenerative diseases: multiple sclerosis, Alzheimer's disease, Huntington's disease, and Creutzfeldt-Jakob disease. Central nervous system is the most metabolically active organ of the body characterized by high requirement for oxygen and relatively low antioxidative activity, what makes neurons and glia highly susceptible to destruction by reactive oxygen/nitrogen species and neurodegeneration. The discovery of F2-IsoPs and F4-NPs as markers of lipid peroxidation caused by the free radicals has opened up new areas of investigation regarding the role of oxidative stress in the pathogenesis of human neurodegenerative diseases. This review focuses on the relationship between F2-IsoPs and F4-NPs as biomarkers of oxidative stress and neurodegenerative diseases. We summarize the knowledge of these novel biomarkers of oxidative stress and the advantages of monitoring their formation to better define the involvement of oxidative stress in neurological diseases.
4

Azevedo, Rita, Chloé Jacquemin, Nicolas Villain, François Fenaille, Foudil Lamari, and François Becher. "Mass Spectrometry for Neurobiomarker Discovery: The Relevance of Post-Translational Modifications." Cells 11, no. 8 (April 9, 2022): 1279. http://dx.doi.org/10.3390/cells11081279.

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Neurodegenerative diseases are incurable, heterogeneous, and age-dependent disorders that challenge modern medicine. A deeper understanding of the pathogenesis underlying neurodegenerative diseases is necessary to solve the unmet need for new diagnostic biomarkers and disease-modifying therapy and reduce these diseases’ burden. Specifically, post-translational modifications (PTMs) play a significant role in neurodegeneration. Due to its proximity to the brain parenchyma, cerebrospinal fluid (CSF) has long been used as an indirect way to measure changes in the brain. Mass spectrometry (MS) analysis in neurodegenerative diseases focusing on PTMs and in the context of biomarker discovery has improved and opened venues for analyzing more complex matrices such as brain tissue and blood. Notably, phosphorylated tau protein, truncated α-synuclein, APP and TDP-43, and many other modifications were extensively characterized by MS. Great potential is underlying specific pathological PTM-signatures for clinical application. This review focuses on PTM-modified proteins involved in neurodegenerative diseases and highlights the most important and recent breakthroughs in MS-based biomarker discovery.
5

Lemieszewska, Marta, Agnieszka Zabłocka, and Joanna Rymaszewska. "Parkinson’s disease: Etiopathogenesis, molecular basis and potential treatment opportunities." Postępy Higieny i Medycyny Doświadczalnej 73 (May 15, 2019): 256–68. http://dx.doi.org/10.5604/01.3001.0013.2021.

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Neurodegenerative diseases affect the life quality and lifespan of aging populations. Among all forms of neurodegenerative diseases, Parkinson’s disease (PD) has a massive impact on the elderly. Oxidative stress and mitochondrial dysfunction are the main causes of neurodegeneration and progression of PD. Oxidative stress, which plays a vital role in the pathophysiology of PD, is related to the dysfunction of cellular antioxidant mechanisms as a result of enhanced production of reactive oxygen species. A large number of studies have utilized oxidative stress biomarkers to investigate the severity of neurodegeneration and medications are available, but these only treat the symptoms. Extensive studies scientifically validated the beneficial effect of natural products against neurodegenerative diseases, using suitable animal models. The review focuses on the role of oxidative stress in the pathogenesis of Parkinson’s disease and the protective potential of natural products against neurodegeneration.
6

Harrington, Karra D., Andrew J. Aschenbrenner, Paul Maruff, Colin L. Masters, Anne M. Fagan, Tammie L. S. Benzinger, Brian A. Gordon, Carlos Cruchaga, John C. Morris, and Jason Hassenstab. "Undetected Neurodegenerative Disease Biases Estimates of Cognitive Change in Older Adults." Psychological Science 32, no. 6 (May 27, 2021): 849–60. http://dx.doi.org/10.1177/0956797620985518.

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Neurodegenerative disease is highly prevalent among older adults and, if undetected, may obscure estimates of cognitive change among aging samples. Our aim in this study was to determine the nature and magnitude of cognitive change in the absence of common neuropathologic markers of neurodegenerative disease. Cognitively normal older adults (ages 65–89 years, N = 199) were classified as normal or abnormal using neuroimaging and cerebrospinal-fluid biomarkers of β-amyloid, tau, and neurodegeneration. When cognitive change was modeled without accounting for biomarker status, significant decline was evident for semantic memory, processing speed, and working memory. However, after adjusting for biomarker status, we found that the rate of change was attenuated and that the biomarker-normal group demonstrated no decline for any cognitive domain. These results indicate that estimates of cognitive change in otherwise healthy older adults will be biased toward decline when the presence of early neurodegenerative disease is not accounted for.
7

Gasecka, Aleksandra, Dominika Siwik, Magdalena Gajewska, Miłosz J. Jaguszewski, Tomasz Mazurek, Krzysztof J. Filipiak, Marek Postuła, and Ceren Eyileten. "Early Biomarkers of Neurodegenerative and Neurovascular Disorders in Diabetes." Journal of Clinical Medicine 9, no. 9 (August 30, 2020): 2807. http://dx.doi.org/10.3390/jcm9092807.

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Diabetes mellitus (DM) is a common disease worldwide. There is a strong association between DM and neurovascular and neurodegenerative disorders. The first group mainly consists of diabetic retinopathy, diabetic neuropathy and stroke, whereas, the second group includes Alzheimer’s disease, Parkinson’s disease, mild cognitive impairment and dementia. The aforementioned diseases have a common pathophysiological background including insulin resistance, oxidative stress, atherosclerosis and vascular injury. The increasing prevalence of neurovascular and neurodegenerative disorders among diabetic patients has resulted in an urgent need to develop biomarkers for their prediction and/or early detection. The aim of this review is to present the potential application of the most promising biomarkers of diabetes-related neurodegenerative and neurovascular disorders, including amylin, β-amyloid, C-reactive protein (CRP), dopamine, gamma-glutamyl transferase (GGT), glycogen synthase kinase 3β, homocysteine, microRNAs (mi-RNAs), paraoxonase 1, phosphoinositide 3-kinases, tau protein and various growth factors. The most clinically promising biomarkers of neurovascular and neurodegenerative complications in DM are hsCRP, GGT, homocysteine and miRNAs. However, all biomarkers discussed in this review could become a part of the potential multi-biomarker screening panel for diabetic patients at risk of neurovascular and neurodegenerative complications.
8

Maciejczyk, Mateusz, Anna Zalewska, and Karolina Gerreth. "Salivary Redox Biomarkers in Selected Neurodegenerative Diseases." Journal of Clinical Medicine 9, no. 2 (February 12, 2020): 497. http://dx.doi.org/10.3390/jcm9020497.

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Neurodegenerative diseases (NDDs), such as Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease, are disorders, which cause irreversible and progressive deterioration of the central nervous system. The pathophysiology of NDDs is still not fully explained; nevertheless, oxidative stress is considered as a critical mediator of cerebral degeneration, brain inflammation, as well as neuronal apoptosis. Therefore, it is not surprising that redox biomarkers are increasingly used in the diagnosis of neurodegenerative diseases. As saliva is a very easy to obtain bioliquid, it seems promising to use this biomaterial in the diagnosis of NDDs. Saliva collection is easy, cheap, stress-free, and non-infectious, and it does not require the help of a specialised medical personnel. Additionally, the concentrations of many salivary redox biomarkers correlate with their content in blood serum as well as the degree of disease progression, which makes them non-invasive indicators of NDDs. This paper reviews the latest knowledge concerning the use of salivary redox biomarkers in the diagnosis and prognosis of selected neurodegenerative diseases.
9

Betts, Matthew J., Evgeniya Kirilina, Maria C. G. Otaduy, Dimo Ivanov, Julio Acosta-Cabronero, Martina F. Callaghan, Christian Lambert, et al. "Locus coeruleus imaging as a biomarker for noradrenergic dysfunction in neurodegenerative diseases." Brain 142, no. 9 (July 20, 2019): 2558–71. http://dx.doi.org/10.1093/brain/awz193.

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Abstract Pathological alterations to the locus coeruleus, the major source of noradrenaline in the brain, are histologically evident in early stages of neurodegenerative diseases. Novel MRI approaches now provide an opportunity to quantify structural features of the locus coeruleus in vivo during disease progression. In combination with neuropathological biomarkers, in vivo locus coeruleus imaging could help to understand the contribution of locus coeruleus neurodegeneration to clinical and pathological manifestations in Alzheimer’s disease, atypical neurodegenerative dementias and Parkinson’s disease. Moreover, as the functional sensitivity of the noradrenergic system is likely to change with disease progression, in vivo measures of locus coeruleus integrity could provide new pathophysiological insights into cognitive and behavioural symptoms. Locus coeruleus imaging also holds the promise to stratify patients into clinical trials according to noradrenergic dysfunction. In this article, we present a consensus on how non-invasive in vivo assessment of locus coeruleus integrity can be used for clinical research in neurodegenerative diseases. We outline the next steps for in vivo, post-mortem and clinical studies that can lay the groundwork to evaluate the potential of locus coeruleus imaging as a biomarker for neurodegenerative diseases.
10

Mollinari, Cristiana, Chiara De Dominicis, Leonardo Lupacchini, Luigi Sansone, Davide Caprini, Carlo Massimo Casciola, Ying Wang, et al. "Detection of Pathological Markers of Neurodegenerative Diseases following Microfluidic Direct Conversion of Patient Fibroblasts into Neurons." International Journal of Molecular Sciences 23, no. 4 (February 15, 2022): 2147. http://dx.doi.org/10.3390/ijms23042147.

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Neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease are clinically diagnosed using neuropsychological and cognitive tests, expensive neuroimaging-based approaches (MRI and PET) and invasive and time-consuming lumbar puncture for cerebrospinal fluid (CSF) sample collection to detect biomarkers. Thus, a rapid, simple and cost-effective approach to more easily access fluids and tissues is in great need. Here, we exploit the chemical direct reprogramming of patient skin fibroblasts into neurons (chemically induced neurons, ciNs) as a novel strategy for the rapid detection of different pathological markers of neurodegenerative diseases. We found that FAD fibroblasts have a reduced efficiency of reprogramming, and converted ciNs show a less complex neuronal network. In addition, ciNs from patients show misfolded protein accumulation and mitochondria ultrastructural abnormalities, biomarkers commonly associated with neurodegeneration. Moreover, for the first time, we show that microfluidic technology, in combination with chemical reprogramming, enables on-chip examination of disease pathological processes and may have important applications in diagnosis. In conclusion, ciNs on microfluidic devices represent a small-scale, non-invasive and cost-effective high-throughput tool for protein misfolding disease diagnosis and may be useful for new biomarker discovery, disease mechanism studies and design of personalised therapies.
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Статті в журналах Дисертації Книги

Дисертації з теми "Biomarkers of neurodegenerative disease":

1

Rittman, Timothy. "Connectivity biomarkers in neurodegenerative tauopathies." Thesis, University of Cambridge, 2015. https://www.repository.cam.ac.uk/handle/1810/248866.

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The primary tauopathies are a group of neurodegenerative diseases affecting movement and cognition. In this thesis I study Progressive Supranuclear Palsy (PSP) and the Corticobasal Syndrome (CBS), two parkinsonian disorders associated with accumulation of hyperphos- phorylated and abnormally folded tau protein. I contrast these two disorders with Parkinson’s disease (PD), which is associated with the accumulation of alpha-synuclein but has a genetic association with the MAPT gene encoding tau. Understanding the tauopathies to develop effective treatments will require a better grasp of the relationships between clinical syndromes and cognitive measures and how the anatomical and neurochemical networks that underlie clinical features might be altered by disease. I investigate simple clinical biomarkers, showing that a two-minute test of verbal fluency is a potential diagnostic biomarker to distinguish between PD and PSP and that the ACE-R and its subscores could play a role in monitoring cognition over time in PD, PSP and CBS. I assess the implementation of network analysis in Functional Mag- netic Resonance Imaging (fMRI) data, introduce Maybrain software for graphical network analysis and visualisation. I go on to show an overlap between graph theory network measures and I identify three main factors underlying graph network measures of: efficiency and distance, hub characteristics, network community measures. I apply these measures in PD, PSP and the CBS. All three diseases caused a loss of functional connectivity in com- parison to the control group that was concentrated in more highly connected brain regions and in longer distance connections. In ad- dition, widely localised cognitive function of verbal fluency co-varied with the connection strength in highly connected regions across PD, PSP and CBS. To take this further, I investigated specific functional covariance networks. All three disease groups showed reduced connectivity between the basal ganglia network and other networks, and between the anterior salience network and other networks. Localised areas of increased co- variance suggest a breakdown of network boundaries which correlated with motor severity in PSP and CBS, and duration of disease in CBS. I explore the link between gene expression of the tau gene MAPT and its effects on functional connectivity showing that the expression of MAPT correlated with connection strength in highly connected hub regions that were more susceptible to a loss of connection strength in PD and PSP. I conclude by discussing how tau protein aggregates and soluble tau oligomers may explain the changes in functional brain networks. The primary tauopathies are a group of neurodegenerative diseases affecting movement and cognition. In this thesis I study Progressive Supranuclear Palsy (PSP) and the Corticobasal Syndrome (CBS), two parkinsonian disorders associated with accumulation of hyperphos- phorylated and abnormally folded tau protein. I contrast these two disorders with Parkinson’s disease (PD), which is associated with the accumulation of alpha-synuclein but has a genetic association with the MAPT gene encoding tau. Understanding the tauopathies to develop effective treatments will require a better grasp of the relationships between clinical syndromes and cognitive measures and how the anatomical and neurochemical networks that underlie clinical features might be altered by disease. I investigate simple clinical biomarkers, showing that a two-minute test of verbal fluency is a potential diagnostic biomarker to distinguish between PD and PSP and that the ACE-R and its subscores could play a role in monitoring cognition over time in PD, PSP and CBS. I assess the implementation of network analysis in Functional Mag- netic Resonance Imaging (fMRI) data, introduce Maybrain software for graphical network analysis and visualisation. I go on to show an overlap between graph theory network measures and I identify three main factors underlying graph network measures of: efficiency and distance, hub characteristics, network community measures. I apply these measures in PD, PSP and the CBS. All three diseases caused a loss of functional connectivity in com- parison to the control group that was concentrated in more highly connected brain regions and in longer distance connections. In ad- dition, widely localised cognitive function of verbal fluency co-varied with the connection strength in highly connected regions across PD, PSP and CBS. To take this further, I investigated specific functional covariance networks. All three disease groups showed reduced connectivity between the basal ganglia network and other networks, and between the anterior salience network and other networks. Localised areas of increased co- variance suggest a breakdown of network boundaries which correlated with motor severity in PSP and CBS, and duration of disease in CBS. I explore the link between gene expression of the tau gene MAPT and its effects on functional connectivity showing that the expression of MAPT correlated with connection strength in highly connected hub regions that were more susceptible to a loss of connection strength in PD and PSP. I conclude by discussing how tau protein aggregates and soluble tau oligomers may explain the changes in functional brain networks.
2

Boman, Andrea. "Lysosomal network proteins as biomarkers and therapeutic targets in neurodegenerative disease." Doctoral thesis, Linköpings universitet, Avdelningen för cellbiologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-122347.

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The pre-symptomatic stage of neurodegenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) occurs several decades before the clinical onset. Changes in the lysosomal network, i.e. the autophagosomal, endosomal and lysosomal vesicular system, are among the first alterations observed. There are currently no treatments to slow or cure neurodegenerative diseases, and there is a great need for discovery of treatment targets in cellular pathways where pathology pre-dates the neuronal death. It is also crucial to be able to diagnose neurodegenerative diseases earlier, both to enable early intervention treatment and aid in selecting clinical trial populations before the patient has widespread pathology. This thesis aims at investigating the potential of lysosomal network proteins as biomarkers and therapeutic targets in neurodegenerative disease. A targeted search for lysosomal network proteins was performed in cerebrospinal fluid (CSF) from AD patients, and seven proteins: early endosomal antigen 1 (EEA1), lysosomal-associated membrane proteins 1 and 2 (LAMP-1, LAMP-2), lysozyme, microtubule-associated protein 1 light chain 3 (LC3), Rab3 and Rab7, were elevated. The levels of EEA1, LAMP-1, LAMP-2, LC3, lysozyme and Rab3 were also measured in CSF from parkinsonian syndrome patients: PD, clinically diagnosed 4-repeat tauopathy, pathologically confirmed corticobasal degeneration (CBD) and pathologically confirmed progressive supranuclear palsy (PSP) patients. LAMP-1 and LAMP-2 were decreased in PD. LC3 and lysozyme levels were increased in 4-repeat tauopathy patients. EEA1 was decreased and lysozyme increased in PSP, and LAMP-1, LAMP-2, LC3 and lysozyme were increased in CBD. The lysosomal network proteins had different CSF protein profiles in all the parkinsonian syndromes, as well as in AD. It should be emphasized that only a select few of the lysosomal network proteins were observed to be changed, rather than a general change in lysosomal network proteins, which implicates the involvement of these seven proteins in specific pathological processes. The most interesting candidates, LAMP-2 and lysozyme, were selected for further study for their involvement in the pathology of AD. Lysozyme was found to co-localise with Aβ plaques in AD patients and overexpression prolonged survival and improved the activity in a Drosophila model of AD. Lysozyme was found to alter the aggregation pathway of Aβ1-42, to counteract the formation of toxic Aβ species and to protect from Aβ1-42 induced cell toxicity. Aβ1-42 in turn was found to increase the expression of lysozyme in both neuronal and glial cells. These data suggest that lysozyme levels rise in AD as a compensatory response which is protective against Aβ associated toxicity. LAMP-2 mRNA and protein were found increased in brain areas relevant for AD pathology and various cellular models showed complex involvement of LAMP-2 in Aβ related pathology, with extensive crosstalk between LAMP-2 and Aβ. Exposure to oligomeric Aβ1-42 caused an upregulation of LAMP-2 and in turn, overexpression of LAMP-2 caused a reduction in secreted levels of Aβ1-42, as well as changing the generation pattern of Aβ and affecting clearance and secretion of Aβ1-42. These data indicate that the increased levels of LAMP-2 in AD could be an attempt to regulate Aβ generation and secretion. In summary, this thesis reports that utilising lysosomal network proteins as biomarkers and novel therapeutic targets for neurodegenerative diseases holds great promise.
3

Raby, Samantha Jade. "The development of biomarkers for neurodegenerative diseases." Thesis, Lancaster University, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.734440.

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The accumulation of misfolded proteins to form inclusion bodies and other protein aggregates outside of cells is a pathological hallmark of neurodegenerative diseases. These aggregating proteins represent potential biomarkers of disease that may facilitate disease diagnosis and the development of therapeutic treatments. Currently neurodegenerative diseases are diagnosed clinically using physical, behavioural and memory based tests along with brain imaging techniques. These methods are associated with variable sensitivity and specificity, and at the point of development of physical symptoms a large amount of neuronal damage has already occurred. Protein biomarkers in easily accessible fluids such as plasma and CSF, can provide additional information to aid in earlier diagnosis, therefore allowing treatments to have a better chance of not only alleviating symptoms but slowing disease progression or perhaps halting disease development.
4

Marková, Veronika. "Potential Neurophysiological Biomarkers for the Diagnosis of Age-related Neurodegenerative Diseases." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-18839.

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The global population with dementia is rapidly increasing around the world.The major risk factor for dementia is aging. There is currently no treatmentavailable and the cost of symptomatic treatment is high. There is a growinginterest in possible clinical applications of non-invasive methods that are safeand easy-to-perform in diagnosis of dementia. The purpose of this paper is toinvestigate the usage of transcranial magnetic stimulation (TMS) withelectroencephalography (EEG) to diagnose dementia in early stages of thedisease. Early diagnosis is needed to reduce the costs of symptomatic care.When investigating the usage of TMS-EEG technology, we will look at how wecan distinguish dementia in different neurodegenerative diseases between eachother. More research is needed to suggest an accurate parameters fordiagnosis of dementia with this type of technology.
5

Yousef, Jamil. "Development of Sandwich Assays for Potential Protein Biomarkers in Neurodegenerative Diseases." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278727.

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As the aging population is increasing worldwide, so is the prevalence of neurodegenerativediseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), frontotemporal dementia(FTD) and amyotrophic lateral sclerosis (ALS). Reliable biomarkers able to aid the diagnosis anddifferentiation of these diseases are needed in order to start the right treatment as early as possible.Due to its representative state of the central nervous system, cerebrospinal fluid (CSF) is afavorable sample material for biomarker discovery within neurodegenerative diseases. Alteredprotein levels of this body fluid might serve as a biomarker, but further validation of earlierfindings is needed. The aim of this project was to validate earlier studies suggesting potentialprotein biomarkers in CSF. From a list of 80 potential biomarkers in the CSF of patient samples,eight were chosen to be included in this validation effort. By utilizing a suspension bead array ina sandwich assay setup, 21 antibodies were tested in an initial screening. Antibody pairs that couldmeasure the protein levels in a dilution dependent manner was further optimized before individualpatient samples were analyzed. Sandwich assays targeting the three proteins Amphiphysin(AMPH), Chitotriosidase-1 (CHIT1) and Beta-synuclein (SNCB) were successfully developed andcorrelated to earlier generated data using a suspension bead array with a single binder setup.Therefore, the earlier findings of elevated levels of AMPH and SNCB in AD patients and CHIT1in ALS patients were successfully validated.
Prevalensen av neurodegenerativa sjukdomar såsom Alzheimers sjukdom (AD), Parkinsonssjukdom (PD), frontallobsdemens (FTD) och amyotrofisk lateralskleros (ALS) ökar i takt med denåldrande populationen. Pålitliga biomarkörer som kan hjälpa till vid diagnostiseringen av dessasjukdomar behövs för att starta rätt behandling så tidigt som möjligt. Ryggmärgsvätska, enkroppsvätska tillhörande det centrala nervsystemet, kan ge en inblick i det centrala nervsystemetstillstånd. Förändrade proteinnivåer i denna kroppsvätska skulle därför kunna fungera sombiomarkörer. Målet i detta projekt var att validera tidigare föreslagna proteinbiomarkörer iryggmärgsvätska. Utifrån en lista av 80 tidigare analyserade proteiner i ryggmärgsvätska hospatienter, inkluderades åtta proteiner i detta valideringsförsök. En antikroppsbaserad så kalladsandwich assay användes i en suspension bead array för att testa 21 stycken antikroppar i ett initialtscreeningsförsök. Antikroppspar som kunde mäta proteinnivåer på ett spädningsberoende vis i detinitiala screeningsförsöket optimerades vidare innan den utvecklade sandwich assayn användes föratt analysera proteinnivåer i individuella prover. Sandwich assays gentemot Amphiphysin(AMPH), Chitotriosidase-1 (CHIT1) och Beta-synuclein (SNCB) kunde bli framtagna ochkorrelerade gentemot tidigare genererat data från en single binder assay på ett framgångsrikt sätt.Projektet kunde därmed validera tidigare fynd som indikerat förhöjda nivåer av AMPH och SNCBi AD patienter, samt förhöjda nivåer av CHIT1 i ALS patienter.
6

Farajipour, Parisa. "In Vitro Biomarker Detection for Early Diagnosis of Neurodegenerative Diseases via the Ocular Fluid." University of Akron / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=akron1259778648.

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7

Cameron, James R. "Eye as a window to the brain : investigating the clinical utility of retinal imaging derived biomarkers in the phenotyping of neurodegenerative disease." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31379.

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Background: Neurodegenerative diseases, like multiple sclerosis, dementia and motor neurone disease, represent one of the major public health threats of our time. There is a clear persistent need for novel, affordable, and patient-acceptable biomarkers of these diseases, to assist with diagnosis, prognosis and impact of interventions. And these biomarkers need to be sensitive, specific and precise. The retina is an attractive site for exploring this potential, as it is easily accessible to non-invasive imaging. Remarkable technology revolutions in retinal imaging are enabling us to see the retina in microscopic level detail, and measure neuronal and vascular integrity. Aims and objectives: I therefore propose that retinal imaging could provide reliable and accurate markers of these neurological diseases. In this project, I aimed to explore the clinical utility of retinal imaging derived measures of retinal neuronal and vessel size and morphology, and determine their candidacy for being reliable biomarkers in these diseases. I also aimed to detail the methods of retinal imaging acquisition, and processing, and the principles underlying all these stages, in relation to understanding of retinal structure and function. This provides an essential foundation to the application of retinal imaging analysis, highlighting both the strengths and potential weaknesses of retinal biomarkers and how they are interpreted. Methods: After performing detailed systematic reviews and meta-analyses of the existing work on retinal biomarkers of neurodegenerative disease, I carried out a prospective, controlled, cross-sectional study of retinal image analysis, in patients with MS, dementia, and ALS. This involved developing new software for vessel analysis, to add value and maximise the data available from patient imaging episodes. Results: From the systematic reviews, I identified key unanswered questions relating to the detailed analysis and utility of neuroretinal markers, and diseases with no studies yet performed of retinal biomarkers, such as non-AD dementias. I recruited and imaged 961 participants over a two-year period, and found clear patterns of significance in the phenotyping of MS, dementia and ALS. Detailed analysis has provided new insights into how the retina may yield important disease information for the individual patient, and also generate new hypotheses with relation to the disease pathophysiology itself. Conclusions: Overall, the results show that retinal imaging derived biomarkers have an important and specific role in the phenotyping of neurodegenerative diseases, and support the hypothesis that the eye is an important window to neurological brain disease.
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Ismail, Kurimun. "Development and utilization of Luminex biomarker assays for diagnosis and monitoring of neurodegenerative disease." Thesis, Lancaster University, 2016. http://eprints.lancs.ac.uk/82998/.

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A common pathological feature of various neurodegenerative disorders is the accumulation of misfolded proteins in the brain. Neurodegenerative disorders associated with protein misfolding include Alzheimer’s disease (AD), Parkinson’s disease (PD), dementia with Lewy bodies (DLB), fronto-temporal lobar degeneration (FTLD), motor neuron disease (MND), Huntington’s disease and the prion diseases. The incidence and prevalence of most of these diseases is rising, especially those that cause dementia, due to an increase in the average human life span. The diagnosis of neurodegenerative disorders is heavily reliant on physical examinations and assessment of clinical symptoms. The clinical symptoms of many of these neurodegenerative diseases overlap, which poses a huge difficulty for accurate diagnosis, especially in the early stages. This has led to an interest in identifying reliable and robust discriminatory molecular biomarkers. A successful biomarker test will not only provide a more accurate means of diagnosis, but will allow efficient tracking of disease progression, benefitting the process of developing therapeutic strategies. In this project, the development and validation of a bead based assay system that has multiplexing capabilities (simultaneously measure multiple analytes in a single sample via a single assay) has been described. This assay system uses the Luminex technology and has been developed to quantitatively measure phosphorylated α-synuclein, total α-synuclein, total DJ-1 and LRRK2 in human CSF and plasma. These proteins are predominantly implicated in diseases collectively termed α-synucleinopathies. The initial aim of the project was to develop assays for proteins that span a range of neurodegenerative disorders, however, for reasons discussed in the final chapter of this thesis, this was not possible. This project provides evidence on how the use of plasma as a possible matrix for potential markers associated with brain diseases can be justified, since levels of phosphorylated α-synuclein in matched plasma and CSF samples positively correlated with each other. Plasma would be an ideal sample source for biomarker studies, since it is less invasive than obtaining CSF, thus allowing longitudinal studies to be performed. It was also shown how the DJ-1 protein in plasma may carry diagnostic potential by allowing differentiation between PD patients and healthy controls (p=0.004) as well as between PD and MSA patients (p=0.005). The discrimination between PD and MSA is vital since the two diseases are symptomatically very similar, thus posing a greater issue with accurate diagnosis. There has been minimal research discussing the presence of LRRK2 in human biological fluids such as plasma and CSF. This thesis presents the use of western blotting, high performance liquid chromatography (HPLC) and the Luminex technology as a means of detecting this protein in human CSF and plasma. The data related to LRRK2 in this thesis, opens up avenues for further research into this protein; to definitively show whether it can be detected in such biological fluids and whether it has any value as a biomarker.
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Gavidia, Bovadilla Giovana. "Study of longitudinal neurodegeneration biomarkers to support the early diagnosis of Alzheimer’s disease." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/666067.

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Alzheimer’s Disease (AD) is a progressive and neurodegenerative disorder characterized by pathological brain changes starting several years before clinical symptoms appear. Earlier and accurate identification of those brain structures changes can help to improve diagnosis and monitoring, allowing that future treatments target the disease in its earliest stages, before irreversible brain damage or mental decline takes place. The brain of AD subjects shrinks significantly as the disease progress. Furthermore, ageing is the major risk factor for sporadic AD, older brains being more susceptible than young or middle-aged ones. However, seemingly healthy elderly brains lose matter in regions related to AD. Likewise, similar changes can also be found in subjects having mild cognitive impairment (MCI), which is a symptomatic pre-dementia phase of AD. This work proposes two methods based on statistical learning methods, which are focused on characterising the ageing-related changes in brain structures of healthy elderly controls (HC), MCI and AD subjects, and addressing the estimation of the current diagnosis (ECD) of HC, MCI and AD, as well as the prediction of future diagnosis (PFD) of these groups mainly focused on the early diagnosis of conversion from MCI to AD. Data correspond to longitudinal neurodegeneration measurements from Magnetic Resonance Imaging (MRI) images. These biomarkers were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Open Access Series of Imaging Studies (OASIS). ADNI data includes MRI biomarkers available at a 5-year follow up on HC, MCI and AD subjects, while OASIS data only includes biomarkers measured at baseline on HC and AD. In the first method, called M-res, variant (vr) and quasi-variant (qvr) biomarkers were identified on HC subjects by using a Linear Mixed Effects (LME) approach on males and females, separately. Then, we built an ageing-based null model, which would characterise the normal atrophy and growth patterns of vr and qvr biomarkers, as well as the correlation between them. By using the null model on those subjects who had been clinically diagnosed as HC, MCI or AD, normal age-related changes were estimated, and then, their deviation scores (residuals) from the observed MRI-based biomarkers were computed. In contrast to M-res, the second method, called M-raw, is focused on directly analyzing the raw MRI-based biomarkers values stratified by five-year age groups. M-raw includes a differential diagnosis-specific feature selection (FS) method, which is applied before classification. In both methods, the differential diagnosis problem was addressed by building Support Vector Machines (SVM) models to carry out three main experiments—AD vs. HC, MCI vs. HC, and AD vs. MCI. In M-res, the SVM models were trained by using as input the residuals computed for the vr biomarkers plus the age, whereas in M-raw, we used the pool of selected features plus age, gender and years of education. The advancement of early disease prediction was calculated as the average number of years advanced in the PFD of the subjects concerning the last known clinical diagnosis. Finally, the ability of both methods to correctly discriminate AD vs. HC subjects was evaluated and compared by testing them on OASIS subjects observed at baseline. Results confirm accelerated or reduced estimates of decline in all cortical biomarkers with increasing age and a frontotemporal pattern of atrophy in HC subjects, as well as in MCI and AD. Regarding the ECD problem, all SVM models obtained better results than comparable methods in the literature for most classification quality indicators, especially on AD vs. HC. Both methods also improve the PFD given the current clinical tests, both in prediction quality indicators and the amount of time by which the diagnosis is advanced.
La enfermedad de Alzheimer (AD) es un trastorno progresivo y neurodegenerativo caracterizado por cambios patológicos en el cerebro que comienzan varios años antes de aparecer los primeros síntomas clínicos. La identificación temprana y precisa de estos cambios ayuda a mejorar el diagnóstico y la monitorización, permitiendo que la enfermedad sea abordada en sus primeras etapas, antes de producirse un deterioro morfológico y mental irreversible. El cerebro de los sujetos con AD se reduce significativamente a medida que avanza la enfermedad, siendo el envejecimiento el principal factor de riesgo para la AD esporádica, donde los cerebros de la gente mayor son más susceptibles que los más jóvenes. Sin embargo, ha sido observado que los cerebros de los adultos mayores y de los sujetos en una fase anterior con deterioro cognitivo leve (MCI) pierden materia en regiones relacionadas con AD. Esta tesis propone dos métodos basados en métodos de aprendizaje estadísticos, que se centran en caracterizar los cambios relacionados con el envejecimiento en estructuras cerebrales de controles sanos de edad avanzada (HC), MCI y AD, y en abordar la estimación del diagnóstico actual (ECD) de estos grupos, así como la predicción de su diagnóstico futuro (PFD), principalmente en el diagnóstico precoz de la conversión de MCI a AD. Los datos utilizados corresponden a biomarcadores de neurodegeneración longitudinal obtenidas de imágenes de Resonancia Magnética (MRI). Estos biomarcadores se obtuvieron a partir de los estudios Alzheimer?s Disease Neuroimaging Initiative (ADNI) y Open Access Series of Imaging Studies (OASIS). Los datos de ADNI incluyeron biomarcadores de MRI disponibles en un seguimiento de 5 años en sujetos HC, MCI y AD, mientras que los datos de OASIS solo incluyeron biomarcadores medidos al inicio del estudio en HC y AD. En el primer método, denominado M-res, los biomarcadores que cambiaron significativamente (vr) y los que cambiaron en una reducida escala (qvr) fueron identificados en sujetos HC utilizando modelos lineales de efectos mixtos (LME). Asimismo, modelos nulos basados en el normal envejecimiento del cerebro fueron construidos para cada género. A través de estos ellos se buscó caracterizar la atrofia normal y los patrones de crecimiento de los biomarcadores vr y qvr, así como la correlación entre ellos. Estos modelos fueron utilizados en los sujetos HC, MCI y AD restantes para inferir los valores normales de los biomarcadores vr y luego calcular sus desviaciones (residuos) respecto a los biomarcadores observados. A diferencia de M-res, el segundo método denominado M-raw, se centra en el análisis de los valores directos de los biomarcadores MRI, estratificados por grupos de edad de cinco años. M-raw incluye un método de selección de características específicas del diagnóstico diferencial aplicado antes de la clasificación. En ambos métodos, se entrenaron máquinas soporte vectorial (SVM) para abordar tres experimentos: AD vs. HC, MCI vs. HC y AD vs. MCI. En M-res, los modelos SVM fueron entrenados a partir de los residuos calculados para los biomarcadores vr más la edad, mientras que en M-raw, se utilizó el grupo de características seleccionadas más la edad, el sexo y los años de educación. El avance de la predicción temprana de la enfermedad fue calculada como el promedio de años avanzados en el PFD con respecto al último diagnóstico clínico conocido. Los resultados confirman una reducción en todos los biomarcadores corticales a medida que la edad avanza, siendo el cambio de algunas regiones más acelerados que otras. Asimismo, se observó un patrón de atrofia frontotemporal en los tres grupos de sujetos. Con respecto al problema ECD, todos los modelos SVM obtuvieron mejor desempeño en la clasificación que los métodos comparables en la literatura, especialmente en AD vs. HC. Ambos métodos también mejoraron la PFD, tanto en los indicadores de calidad de predicción como en el tiempo de avance en el diagnóstico (hasta 1.87 años antes en sujetos de 80-84 años).
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Chaney, Aisling. "Investigating imaging biomarkers of neuroinflammation and neurodegeneration in rodent models of Alzheimer's disease." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/investigating-imaging-biomarkers-of-neuroinflammation-and-neurodegeneration-in-rodent-models-of-alzheimers-disease(16750cf1-eb30-49c5-b9eb-9f01d4a0560f).html.

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Alzheimer’s disease (AD) is a progressive neurodegenerative disease resulting in alterations in memory, language, executive function and emotional behaviour. Although it can be characterised by symptoms, by the time they arise significant pathological alterations have already emerged in the central nervous system, namely increased amyloid plaques, neurofibrillary tangles and neuronal loss. Despite known pathological hallmarks the exact aetiology of AD is poorly understood and no current treatments are available. However, there is growing interest in the role of neuroinflammation in AD, with increases observed in the early stages of disease and with disease progression. Moreover, it has been suggested that peripheral inflammation can influence neuroinflammation and worsen neurodegeneration. Using Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRS) we can non-invasively measure biomarkers of neuroinflammation and degeneration allowing multi-modal investigation of its role in normal aging and AD. Considering this the objectives of this study were to (i) Use PET and MRS to investigate neuroinflammatory and metabolite alterations in transgenic (TG) models of AD and their wildtype (WT) animals. (ii) Assess rates of cognitive decline in these models using memory based tests. (iii) Investigate relatively new TgF344AD rat as an AD model by characterising younger time-points than previously reported. (iv) Investigate the contribution of peripheral inflammation on AD progression. PET and MRS imaging was carried out longitudinally in the APPswe×PS1de9 mouse. Neuroinflammation was confirmed ex vivo and cognitive ability was assessed by behavioural tests. Results revealed significantly increase hippocampal and thalamic neuoinflammation in old TG mice as assessed by [18F]DPA-714 PET and supported by immunohistochemistry. Reduced neuronal marker N-acetlyaspartate was seen with age and was exacerbated in the TG mice. Accelerated cognitive decline was also seen in TG mice. PET and MRS imaging was carried out at 6 and 12 months in the TgF344AD model, which expresses amyloid and tau pathology as well as neuronal loss. No cognitive decline was observed in TG rats; however increased anxiety behaviour was seen. Increased [18F]DPA-714 PET was observed as an effect of gene in the thalamus at 6 months and the hypothalamus at 12 months. Increases in glutamate were seen with age in the TG rats but not the WTs. Increased inflammation and metabolite alterations were seen with aging. The effect of peripheral urinary tract infection (UTI) on cognition and imaging out was assessed. Imaging was carried out prior to and after re-current UTI. Infection induced cognitive decline in infected TG but not WT rats. Infection had an increasing effect on hypothalamic neuroinflammation in WT rats but a decreasing effect on TG rats, which masked the original gene differences. This thesis is set out in the alternative format with each experimental study represented as a chapter. Results in this thesis implicate neuroinflammation in AD development and progression. In addition, we report systemic infection-CNS interactions accelerating cognitive decline in AD and highlight the importance of understanding the effects of comorbidities in disease.
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Книги з теми "Biomarkers of neurodegenerative disease":

1

Peplow, Philip V., Bridget Martinez, and Thomas A. Gennarelli, eds. Neurodegenerative Diseases Biomarkers. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-1712-0.

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2

Ingelsson, Martin, and Lars Lannfelt, eds. Immunotherapy and Biomarkers in Neurodegenerative Disorders. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3560-4.

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3

Lovestone, Simon. Biomarkers in brain disease. Boston, Mass: Published by Blackwell Pub. on behalf of the New York Academy of Sciences, 2009.

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4

Edelstein, Charles L. Biomarkers in kidney disease. London: Academic, 2010.

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5

de Lemos, James A., ed. Biomarkers in Heart Disease. Oxford, UK: Blackwell Publishing Ltd., 2008. http://dx.doi.org/10.1002/9781444300208.

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Patel, Vinood B., and Victor R. Preedy, eds. Biomarkers in Bone Disease. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-007-7693-7.

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7

Patel, Vinood B., and Victor R. Preedy, eds. Biomarkers in Cardiovascular Disease. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-007-7741-5.

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8

Preedy, Victor R., ed. Biomarkers in Liver Disease. Dordrecht: Springer Netherlands, 2016. http://dx.doi.org/10.1007/978-94-007-7742-2.

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9

Preedy, Victor R., ed. Biomarkers in Bone Disease. Dordrecht: Springer Netherlands, 2016. http://dx.doi.org/10.1007/978-94-007-7745-3.

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Patel, Vinood B., ed. Biomarkers in Kidney Disease. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-007-7743-9.

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Частини книг з теми "Biomarkers of neurodegenerative disease":

1

Surguchov, Andrei. "Biomarkers in Parkinson’s Disease." In Neurodegenerative Diseases Biomarkers, 155–80. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1712-0_7.

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2

Harker, Donald M. R., Bridget Martinez, and Ruben K. Dagda. "Possible Biomarkers for Frontotemporal Dementia and to Differentiate from Alzheimer’s Disease and Amyotrophic Lateral Sclerosis." In Neurodegenerative Diseases Biomarkers, 387–403. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1712-0_16.

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Mattsson, Niklas, Sotirios Grigoriou, and Henrik Zetterberg. "Fluid Biomarkers in Alzheimer’s Disease and Frontotemporal Dementia." In Neurodegenerative Diseases, 221–52. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72938-1_11.

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Bozzali, Marco, and Laura Serra. "Biomarkers for Alzheimer’s Disease and Frontotemporal Lobar Degeneration: Imaging." In Neurodegenerative Diseases, 253–77. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72938-1_12.

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Bozzali, Marco, and Laura Serra. "Biomarkers for Alzheimer’s Disease and Frontotemporal Lobar Degeneration: Imaging." In Neurodegenerative Diseases, 159–78. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6380-0_10.

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Mattsson, Niklas, and Henrik Zetterberg. "Cerebrospinal Fluid Biomarkers in Alzheimer’s Disease and Frontotemporal Dementia." In Neurodegenerative Diseases, 131–57. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6380-0_9.

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Killoran, Annie. "Biomarkers in Huntington’s." In Neurodegenerative Diseases Biomarkers, 235–62. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1712-0_10.

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De Natale, Edoardo Rosario, Heather Wilson, and Marios Politis. "Imaging in Huntington’s." In Neurodegenerative Diseases Biomarkers, 457–505. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1712-0_19.

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Xi, Hui, and Yang Zhang. "Aptamer Detection of Neurodegenerative." In Neurodegenerative Diseases Biomarkers, 361–86. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1712-0_15.

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10

Hor, Jin-Hui, Munirah Mohamad Santosa, and Shi-Yan Ng. "Role of SIRT3 and in Neurodegeneration." In Neurodegenerative Diseases Biomarkers, 99–120. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1712-0_5.

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Тези доповідей конференцій з теми "Biomarkers of neurodegenerative disease":

1

Faria, Gustavo Hugo de Souza. "The impact of epigenetics on the development of neurodegenerative diseases." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.654.

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Introduction: Neurodegenerative diseases affect thousands of people in Brazil and have been increasing in frequency with the aging population. However, little is known about the molecular mechanisms and biomarkers of these diseases, which leads to a medical approach based on symptomatic and unresolving characteristics. Epigenetics, including DNA methylation, histone modifications, and changes in regulatory RNAs, emerges as a tool for prevention of neurodegenerative diseases. Objectives: To review studies that discuss the role of epigenetics in the development of neurodegenerative diseases. Methodology: This study involved an integrative review of papers published from 2016 to 2021 by searching PubMed and Scopus. Results: The studies showed that there is evidence that epigenetic mechanisms interfere with the development of major neurodegenerative diseases. Huntington’s disease presents an altered gene from birth, but transcriptional dysregulation is characteristic of the pathology that may be correlated to the age of disease onset in the cortex. In Parkinson’s disease dysregulation of expression of a specific protein is believed to play a central role in the disease and occurs through aberrant methylation that controls activation or suppression. In relation to Alzheimer’s disease, it has been found that deregulated DNA methylation and demethylation is linked to the onset and progression of the disease. In addition, these epigenetic factors are interfered with by diet, aging, and exercise. Conclusions: Investment in epigenetic studies is needed to understand possible markers of neurodegenerative diseases, for early diagnosis and the formation of epidrugs with the ability to treat.
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Rizzi, Liara, and Marcio Balthazar. "THE SUSPECTED NON-ALZHEIMER’S DISEASE PATHOPHYSIOLOGY." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda070.

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Background: Individuals that are negative for amyloid biomarkers and positive for p-Tau and/or neurodegeneration ones are known as with the suspected non-Alzheimer’s disease pathophysiology (SNAP). It is a biomarker-based concept that underlying etiology has not been completely understood. Objective: To report the main characteristics of the SNAP group. Methods: PubMed was searched to identify articles about the SNAP for inclusion. Results: The prevalence of SNAP varies from 18% to 35% among cognitively normal individuals, from 16,6% to 35% among mild cognitive impairment (MCI), and from 7% to 39% among clinical probable Alzheimer’s Disease (AD). SNAP subjects have a lower risk of clinical progression to MCI or AD dementia than those with positive amyloid biomarkers, but higher than those whose biomarkers for amyloid and neurodegeneration are negative. SNAP predominate in older men and have a lower incidence of the APOE ε4 allele than in individuals with AD. Cognitive decline in SNAP subjects is related to neuronal damage. They present greater hippocampal atrophy than AD, but a similar pattern of hypometabolism. Hippocampus-specific pathologies and cerebrovascular diseases may underlie neurodegeneration and cognitive impairments. Conclusion: The construct of SNAP has been challenging, therefore, a deeper understanding of the main pathways that underlie SNAP can allow substrates for disease prevention and/or remission in the future.
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Pinheiro, Mariana Maciel, Victor Albuquerque, Pedro Albuquerque, Eduardo Maranhão, Jonathan Diniz, and Breno Barbosa. "CORTICOBASAL SYNDROME DUE TO ALZHEIMER’S DISEASE." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda055.

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Background: Corticobasal Syndrome (CBS) is a neurodegenerative syndrome that combines cortical and cognitive deficits secondary to different underlying pathological entities. Objectives: to report an early onset dementia case fulfilling criteria of probable CBS due to Alzheimer’s Disease (AD) based on biomarkers and neuroimaging. Methods: case report. Results: a 57-yearsold woman with college-level education and 18 months of cognitive decline. The first symptom was progressive inability to change gears in her car, followed by difficulties to get dressed, cognitive and motor complaints. Neurological examination revealed marked limb bilateral ideomotor apraxia and mild asymetric parkinsonism. Cognitive tests showed mild visuospatial and language impairments, scoring 18/30 in the MoCA. Brain MRI and FDG PET showed bilateral posterior atrophy and hypometabolism worse to the left. CSF biomarkers revealed decreased amyloid and increased tau and p-tau levels, a pattern suggestive of CBS due to AD. Conclusions: this case illustrates recent evidence that suggests when AD presents as CBS (CBS-AD), limb apraxia and language impairment are more prevalent. CBS patients with underlying AD pathology and tauopathies correctly diagnosed in the future may benefit from symptomatic therapies and future disease-modifying agents.
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Mariano, Luciano, Larissa Salvador, Patrícia Peles, Clarisse Friedlaender, Viviane Carvalho, Etelvina dos Santos, Leonardo de Souza, and Paulo Caramelli. "AT(N) MODEL AND ITS ASSOCIATION WITH NEUROPSYCHOLOGICAL MARKERS." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda019.

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Background: The National Institute on Aging and Alzheimer’s Association (NIA-AA) proposed the AT(N) model to diagnose Alzheimer’s disease (AD) considering some biomarkers: amyloid beta (A), phosphorylated tau (T), and neurodegeneration (N). Still, AT(N) correlation with cognitive markers is not yet covered. Objective: To investigate the neuropsychological profile of patients with CSF biomarkers according to AT(N) classification. Methods: Sixty-five patients with thorough neuropsychological data and results of CSF biomarkers were included in the study. We performed a cluster analysis using biomarkers results. The validity was checked by neuropsychological tests scores. Results: We found three clusters: Cluster 1 (n=24), classified as non-AD; Clusters 2 (n=9) and 3 (n=32), classified as AD. Cluster 2 had a higher burden of phosphorylated tau and total tau. All groups were similar regarding sociodemographics and functionality. AD groups had worse memory deficits than the non-AD cluster, but Cluster 2 was more affected than Cluster 3. No other cognitive difference was found, except in the Cubes subtest (Cluster 3>Cluster 2).Conclusion: Memory was the sole domain able to discriminate AD from non-AD, probably due to Cluster 1 heterogeneity. Further studies are warranted to explore this hypothesis. A smaller cluster with AD shows variability in the biomarker profile, which is relevant given its worse cognitive scores.
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Parmera, Jacy, Artur Coutinho, Isabel Almeida, Camila Carneiro, Carla Ono, Adalberto Studart-Neto, Egberto Barbosa, Carlos Buchpiguel, Ricardo Nitrini, and Sonia Brucki. "CORTICOBASAL SYNDROME: A PROSPECTIVE STUDY OF CLINICAL PROFILES AND IMAGING BIOMARKERS." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda010.

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Background: Corticobasal syndrome (CBS) is neurodegenerative disorder related to multiple underlying pathologies. Objective: To investigated if dividual FDG-PET patterns could distinguish CBS due to Alzheimer’s disease (AD) from other pathologies based on [11C]Pittsburgh Compound-B (PIB)-PET. Methods: Forty-five patients with probable CBS were prospectively evaluated. They underwent FDG-PET and were divided into groups: related to AD (CBS FDG-AD) or non-AD (CBS FDG-nonAD). Thirty patients underwent PIB-PET on a PET-MRI to assess their amyloid status. FDG and PIB-PET were classified individually on visual analysis, and PET-MRI quantitative group analyses were performed. Results: CBS FDG-AD group (33.3%) showed worse cognitive performances, displayed more myoclonus and hallucinations. CBS FDG-nonAD group (66.7%) presented more dystonia, ocular motor dysfunction, perseveration, and dysarthria. All CBS FDG-AD patients tested positive at PIB-PET compared to 3 out of 20 in the non-AD group. The individual FDG-PET classification had 76.92% of sensitivity, 100% of specificity and 88.5% of accuracy to detect positive PIB-PET scans. Individuals with positive and negative PIB-PET showed hypometabolism in temporoparietal areas and in thalamus and brainstem, respectively, disclosing metabolic signatures. Conclusion: CBS is mainly distinguished by two variants (AD and non-AD), with different cognitive profiles and possibly motor features. FDG-PET was useful depicting their specific degeneration patterns and brain amyloid deposition.
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Chiu, Shu-I., Chin-Hsien Lin, Wee Shin Lim, Ming-Jang Chiu, Ta-Fu Chen, and Jyh-Shing Roger Jang. "Predicting Neurodegenerative Diseases Using a Novel Blood Biomarkers-based Model by Machine Learning." In 2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI). IEEE, 2019. http://dx.doi.org/10.1109/taai48200.2019.8959854.

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7

Arisi, Ivan, Patrizia Mecocci, Giuseppe Bruno, Marco Canevelli, Magda Tsolaki, Natalia Pelteki, Fabrizio Stocchi, et al. "Mining clinical and laboratory data of neurodegenerative diseases by Machine Learning: transcriptomic biomarkers." In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2018. http://dx.doi.org/10.1109/bibm.2018.8621072.

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8

Meghdadi, Amir H., Marija Stevanovic Karic, and Chris Berka. "EEG analytics: benefits and challenges of data driven EEG biomarkers for neurodegenerative diseases." In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 2019. http://dx.doi.org/10.1109/smc.2019.8914065.

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9

Innocencio, Giovanna de Camargo, Juliana de Souza Rosa, Patrick de Abreu Cunha Lopes, Paulo Roberto Hernandes Júnior, and Jhoney Francieis Feitosa. "Clinical overview and therapeutic management of the cognitive and behavorial aspects of Huntington’s disease." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.177.

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Background: Huntington’s disease (HD) is an autosomal dominant neurodegenerative disease classified among chorea that, in addition to motor symptoms, is characterized by neuropsychiatric disorders. Objectives: to analyze the cognitive and behavioral clinical aspects of Huntington’s disease and the therapeutic management of these symptoms. Methods: a literature review was carried out from the Scielo and PubMed database, using “Huntington’s disease”, “Cognition”, “Behavior” and “Treatment” as descriptors, where 11 articles were selected between 2001 and 2018. Results: the nature of cognitive and behavioral symptoms in HD are very dynamic, and cognitive dysfunctions are present prior to diagnosis. The most common clinical challenges include executive dysfunction, mainly slow thinking and attention disorders, apathy, depression and irritability. One study used data from the European Huntington’s Disease Network and evaluated almost 2.000 carriers of the mutation, in which 47.4% reported apathy, while depression and irritability occurred in 42.1%, and aggression and psychosis occurred in 38.6%. Other studies have confirmed apathy as an early manifestation related to its progression. For the therapeutic management of chorea, tetrabenazine is used, while antidepressants can be effective in mood symptoms. On the other hand, antipsychotics can lead to the advance and rapid progress of the disease. Small controlled studies with atomoxetine, donepezil and rivastigmine have found no positive effects on patients’ cognition. Recent publications have shown that circulating levels of brain-derived neutrotrophic factors in HD correlate with mood, cognition and motor function and can serve as markers of treatment success, while growth factor I is associated with cognitive decline and can provide biomarker targets for treatment validation. Conclusion: cognitive and behavioral symptoms in HD are very diversified and some strategies may have potential therapies and/or deleterious ones.
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Iwabuchi, Manna, Marcel Hetu, Eric Maxwell, Jean S. Pradel, Sashary Ramos, and William G. Tong. "Nonlinear multi-photon laser wave-mixing optical detection in microarrays and microchips for ultrasensitive detection and separation of biomarkers for cancer and neurodegenerative diseases." In SPIE Optical Engineering + Applications, edited by G. Groot Gregory, Arthur J. Davis, and Cornelius F. Hahlweg. SPIE, 2015. http://dx.doi.org/10.1117/12.2188797.

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Звіти організацій з теми "Biomarkers of neurodegenerative disease":

1

Lim, Soojin. Fluorescent Indicators for Disease Biomarkers. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.262.

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2

Potashkin, Judith. Splice Variant Biomarkers for Parkinson's Disease. Fort Belvoir, VA: Defense Technical Information Center, May 2014. http://dx.doi.org/10.21236/ada600497.

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3

Bailey, Charles L. Infectious Disease Proteome Biomarkers: Final Technical Report. Office of Scientific and Technical Information (OSTI), December 2011. http://dx.doi.org/10.2172/1090082.

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4

Hakuna, Lovemore. Selective Indicators for Optical Determination of Disease Biomarkers. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2052.

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5

Gordon, Terry. Development of Biomarkers for Chronic Beryllium Disease in Mice. Office of Scientific and Technical Information (OSTI), January 2013. http://dx.doi.org/10.2172/1060004.

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6

Millhorn, David E. Signal Transduction and Gene Regulation During Hypoxic Stress: A Potential Role in Neurodegenerative Disease. Fort Belvoir, VA: Defense Technical Information Center, August 2000. http://dx.doi.org/10.21236/ada383039.

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Millhorn, David E. Signal Transduction and Gene Regulation During Hypoxia Stress: A Potential Role in Neurodegenerative Disease. Fort Belvoir, VA: Defense Technical Information Center, August 2002. http://dx.doi.org/10.21236/ada416979.

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Millhorn, David E. Signal Transduction and Gene Regulation During Hypoxic Stress: A Potential Role in Neurodegenerative Disease. Fort Belvoir, VA: Defense Technical Information Center, August 2001. http://dx.doi.org/10.21236/ada397765.

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9

Mayes, Maureen D. Predicting Disease Progression in Scleroderma with Skin and Blood Biomarkers. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada613314.

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10

Vlad, Anda. Disease Heterogeneity and Immune Biomarkers in Preclinical Mouse Models of Ovarian Carcinogenesis. Fort Belvoir, VA: Defense Technical Information Center, August 2012. http://dx.doi.org/10.21236/ada568359.

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