Dissertations / Theses: 'Alzheimer’s disease – Diagnosis'

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Cisek, Katryna. "Rational Optimization of Small Molecules for Alzheimer’s Disease Premortem Diagnosis." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338325484.

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Schafer, Nicole D. "Targeting Tau Aggregation for the Diagnosis and Treatment of Alzheimer’s Disease." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366219959.

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Gonzalez, Murcia Josue David. "Diagnosis and the Role of Chemokine Receptors in Alzheimer's Disease." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/8888.

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Alzheimer’s disease (AD) is the most common neurodegenerative disorder and is the main cause of dementia in the elderly population. AD is pathologically characterized by the accumulation of amyloid plaques and neurofibrillary tangles that results in neurodegeneration and loss of memory function. However, diagnosis of AD and characterization of biological mechanisms that lead to pathology and modulate risk for disease has proven to be extremely difficult. Cerebrospinal fluid (CSF) contains critical biomarkers for AD such as levels of amyloid beta (Aβ) phosphorylated-tau (p-tau), total-tau (t-tau), and neurofilament light chain (NfL). The CSF levels of these biomarkers are useful in determining AD status in a patient, but data collection can be time consuming, technically difficult, and expensive. While still subject to the limitations of obtaining CSF, cell free single stranded DNA (cfssDNA) is much cheaper and more reliably measured than these biomarkers. We investigated cfssDNA as a biomarker for AD status. We observed an association between low levels of concentration isolated from CSF as a potential biomarker for diagnosis of AD. Inflammation is a vital process in the immune system. Acute inflammation plays an essential role in the normal response to tissue injury. This inflammatory response initiates a cascade of cellular activation signals in innate immune cells resulting in increased production of proinflammatory cytokines and chemokines. These chemokines are essential to the recruitment and activation of other cells in the innate and adaptive immune system. Deviations from the normal production of these chemokines can result in disease status. Recently published work has identified genetic variants that show strong associations with AD-related chemokine levels in CSF and plasma. We attempted to characterize the biological mechanisms that underlie the reported associations between the ACKR2-V41A variant and CCL2 levels and the CCRL2-V180M variant and CCL4 levels. Our data demonstrate that the ACKR2-V41A receptor has a lower CCL2 binding affinity, scavenging efficiency, and receptor upregulation compared to ACKR2-WT. For CCRL2-V180M our data demonstrate higher binding affinity with chemerin and CCL19 than CCRL2-WT. Our data also show that while CCRL2-V180M and CCRL2-WT do not directly bind with CCL4, interactions between CCRL2-V180M and CCL19 alter the secretion of CCL4 from leukocytes. These findings provide evidence for a novel biomarker for AD diagnosis, mechanistic insights into the functional impact of common genetic variants on chemokine levels, and highlight a potential role of atypical chemokines in altering the risk for AD.

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Li, Chunfei. "Multimodal Imaging for Enhanced Diagnosis and for Assessing Progression of Alzheimer’s Disease." FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3703.

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A neuroimaging feature extraction model is designed to extract region-based image features whose values are predicted by base learners trained on raw neuroimaging morphological variables. The main objectives are to identify Alzheimer’s disease (AD) in its earliest manifestations, and be able to predict and gauge progression of the disease through the stages of mild cognitive impairment (EMCI), late MCI (LMCI) and AD. The model was evaluated on the ADNI database and showed 75.26% accuracy for the challenging EMCI diagnosis based on the 10-fold cross-validation. Our approach also performed well for the other binary classifications: EMCI vs. LMCI (72.3%), EMCI vs. AD (95%), LMCI vs. AD (84.3%), CN vs. LMCI (77.5%), and CN vs. AD (96.5%). By applying the model to the Genome-wide Association Study, along with the sparse Partial Least Squares regression method, we successfully detected risk genes such as the APOE, TOMM40, RVRL2 and APOC1 along with the new finding of rs917100. Moreover, the research aimed to investigate the relationship of different biomarkers; especially the imaging biomarkers to better understand the precise biologic changes that characterize Alzheimer’s disease. The unique and independent contribution of APOE4 allele status (E4+\E4-), amyloid (Aβ) load status (Amy+\Amy-) and combined APOE4 and Aβ status on regional cortical thickness (CTh) and cognition were evaluated via a series of two-way ANCOVAs with post-hoc Tukey HSD tests. Results showed that decreased CTh is independently associated with Amy+ status in many brain regions, but with E4+ status in very restricted number of brain regions. Among CN and EMCI participants, E4+ status is associated with increased CTh, in medial and inferior temporal regions. Diverging association patterns of global and regional Aβ load with cortical volume were found in the entorhinal, temporal pole and parahippocampal regions, which were positively associated with regional Aβ load, but with a negative correlation for global Aβ load in MCI stages. In addition, strong positive correlations were shown between baseline regional CTh and the difference of CTh in each region between the CN and AD, even after adjusting for the regional Aβ and APOE genotype (E4+: r = 0.521 and E4-: r = 0.694).

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Gibson, Allison K. "Examining the Experiences of Caregivers During the Diagnosis of Alzheimer’s Disease and Related Dementias." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1275071723.

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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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Tarantello, Concetta. "The role of subjective memory complaints in predicting cognitive impairment associated with future Alzheimer’s disease: a community based study." University of Sydney, 2009. http://hdl.handle.net/2123/6190.

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Doctor of Philosophy(PhD) In recent years there has been a substantial increase in research examining the role of subjective memory complaints (SMC) in cognitive function and Alzheimer’s disease. These studies have related SMC to many different cognitive outcomes, such as retaining normal cognitive function, a fluctuating cognitive performance and the development of Alzheimer’s disease. Most of these studies have focused on older populations and have employed a limited assessment of cognitive function. This limits the available evidence regarding the clinical utility of SMC. The literature on the role of SMC in younger subjects is scarce. It is not known whether memory complaints are useful in predicting future cases of Alzheimer’s disease in younger community-based subjects. Aims: The main aim of the present study was to determine whether SMC predict the development of cognitive impairment in a younger cohort of subjects, many of whom were under the age of 70 years (73%), based on their risk profile and neuropsychological assessment. A further aim was to ascertain whether the DRS or 7MS are sensitive screening tools for MCI and examine whether the presence of SMC affects the 3-year cognitive outcome of subjects. To address these aims, this study consisted of two parts: a cross-sectional design and a longitudinal follow-up component. Methods: This study was carried out with 86 community-dwelling subjects recruited via advertisement within the catchment area of Central Sydney Area Health Service. The mean age of the subjects was 63.1 years (SD=8.4). Subjective memory complaints were assessed using a single question. Cognitive function was assessed using a comprehensive battery of tests, selected on the basis of their sensitivity to identifying cognitive impairment typically associated with Alzheimer’s disease. After the initial analysis between those with SMC and without SMC, subjects were further classified according to their performance on an episodic memory task (i.e., delayed verbal recall, Rey, 1964) as having normal memory function, SMC or aMCI. Results: Part 1 - Subjective memory complaints (SMC) were reported by 63% of the sample. The initial analysis between subjects with SMC (n=54) and without SMC (n=32) suggested an initial relationship between SMC and cognitive functioning. Subjects with SMC had impaired global cognitive functioning on two brief screening tests (7MS and DRS), working memory, verbal recall and visuomotor speed. However, subsequent screening with the delayed verbal recall test showed that 12 of the 54 subjects with SMC demonstrated significant cognitive impairment, scoring 2 SD below the control group mean. After these subjects were removed to form the aMCI group, the cognitive differences between subjects with SMC and without SMC were no longer apparent. Subjects with aMCI showed evidence of multiple cognitive deficits (below 1 SD of control group mean) with a high percentage of subjects demonstrating impairment on tests of verbal learning, verbal recall, verbal ability and visuomotor speed. Further analysis showed a significant association between age and subjects identified as having SMC (r=-.581, p<.001) and aMCI (r=.692, p<.001). From the age of 60 onwards, both the SMC and aMCI groups demonstrated a more rapid cognitive decline with increasing age in several cognitive domains. Part 2 - After a mean interval of 3.2 years, 43 subjects were followed up. Subjects with aMCI showed evidence of greater decline on both screening tests (7MS; DRS), whilst the SMC group had significantly higher scores. This trend was also apparent with other neuropsychological testing. The analysis of change over time in cognitive function showed that the majority of subjects (both SMC aMCI) either remained stable or improved their cognitive performance. It is likely that the small sample size and short follow-up interval of the present study contributed to the present observation of no change in cognitive function over time. Discussion: The present findings suggest that subjective memory complaints are a poor predictor of cognitive function. In isolation, SMC are unlikely to be useful for identifying cases with significant cognitive impairment. This is particularly relevant for subjects under the age of 70 years. However, for subjects over the age of 70 years, SMC are likely to identify significant cases with neuropsychological assessment (such as animal fluency and delayed recall). Conclusion: The present study showed that SMC are a poor predictor of cognitive function in subjects under the age of 70 years. This study provided evidence that selected and relatively quick to administer formal neuropsychological tests of cognitive function (in particular tests of animal fluency and delayed recall) are better able to identify those at risk of developing cognitive impairment associated with Alzheimer’s disease, at an earlier age. This would thus allow exposure to earlier treatment options, such as donepezil, aricept, vitamin E, and memantine”.

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Dhiman, Kunal. "Utility of CSF biomarkers for the diagnosis, prognosis and assessment of cognitive decline in Alzheimer’s disease." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2020. https://ro.ecu.edu.au/theses/2284.

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Alzheimer’s disease (AD) is a slow and progressive neurodegenerative disorder.With new treatment strategies failing in clinical trials, there is a need to initiate a targeted treatment strategy, by administering the right medication, to the right individual, at the right stage. This concept of precision medicine not only requires diagnosis at the preclinical stage, but a thorough understanding of the stage-associated neuropathological changes that occur along the continuum of AD. Pathophysiological biomarkers indicative of neuropathological changes in the brain are needed to identify the preclinical stage of AD, as well as track the extent of cognitive deficit that occurs with the evolution of such changes. The current study was conducted to assess the diagnostic and prognostic potential of cerebrospinal fluid (CSF) biomarkers in AD, associated with neurodegeneration (neurofilament light chain protein, NfL; visinin-like protein-1, VILIP-1; fatty acid binding protein 3, FABP3), neuroinflammation (YKL-40) and synaptic dysfunction (neurogranin, growth-associated protein 43, GAP-43; synaptosomal-associated protein 25, SNAP-25; synaptotagmin-1). CSF samples of participants (n = 221) from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing were used in the study. The study participants were clinically classified as healthy controls (HC, n = 159), mild cognitive impairment (MCI, n = 34) and AD (n = 28). The study aimed to assess the diagnostic potential of CSF biomarkers, their preclinical diagnostic utility, prediction of disease onset and progression, association with central AD pathology, as well as their ability to predict baseline cognition, brain atrophy and amyloid accumulation. The CSF biomarkers NfL, VILIP-1, FABP3, YKL-40, neurogranin, GAP-43 and SNAP-25 distinguished AD participants from HC with a fairly high area under the receiver operating characteristic curve (AUC). CSF biomarkers of neurodegeneration (NfL and FABP3) predicted disease onset among HC who converted from Clinical Dementia Rating (CDR) 0 to CDR ≥ 0.5, over a follow-up period of 4.5 years. CSF biomarkers predicted disease progression among patients (MCI and AD), assessed through the annual change in cognitive scores in patients, divided into tertiles based on 33rd and 66th percentile of CSF measures. CSF levels of NfL significantly increase in the earlier stages of the disease, but not in the later stages, indicating that the brain reaches a stage of irreversible neurodegeneration in late AD, with not much further evolution. CSF biomarkers significantly correlated with core CSF biomarkers total tau (T-tau) and phosphorylated tau (P-tau); classified study participants according to the A/T/N classification (based on biomarker of amyloid deposition, A; tau pathology, T and neurodegeneration, N) and predicted baseline cognition and brain atrophy. All CSF biomarkers were weak predictors of baseline amyloid load, and did not distinguish amyloid positives from negatives with a high sensitivity. This makes it apparent that neurodegeneration, neuroinflammation and synaptic dysfunction, all run independent of amyloid pathology along the disease continuum, but amyloid beta (Aβ) accumulation does contribute to the disruption of spines or neuritis, and inflammatory response. These biomarkers and the pathologies they drive conglomerate at one stage or the other to constitute the AD neuropathology, and demonstrate an excellent diagnostic accuracy in combination. Neurodegeneration and neuroinflammation evolve in synchronisation at all stages, along the disease continuum. Neurodegeneration and synaptic dysfunction are synchronised as well, but not in an advanced stage of the disease continuum. These biomarkers give a clear picture of the pathological changes that occur along the disease continuum, and can be used as endpoint measures in clinical trials.

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Correia, Marta Sofia da Silva. "Identification of potential Alzheimer’s disease biomarkers in plasma using FTIR." Master's thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/13622.

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Mestrado em Biomedicina Molecular Current clinical AD diagnosis criteria used to identify the disorder in patients who have already overt the advanced stage of dementia. This is too late for some kind of successful disease adjustment and consequently, early recognition of AD needs to be improved. Therefore, it is really needed different approaches for discovering new AD biomarkers, such as the application of metabolomics techniques (e.g. FTIR). The potential of FTIR in the clinical field has recently received particular attention, since it uses vibration frequencies of molecules present in the analysed sample to produce a metabolic fingerprint, which is then specific for each sample. This dissertation aims to identify biochemical alterations that might be related to dementia, being possible to distinguish between control and disease groups of plasma samples, through application of FTIR methodology at the 4000-600 cm-1 spectral region. Using plasma samples makes the process being minimally invasive, with other relevant clinical advantages. Besides the collection of blood samples used in this project, the volunteers were also submitted to cognitive evaluation trough Mini Mental State Examination (MMSE) and Clinical Dementia Rating (CDR), with other relevant clinical information being also collected. All the analysed samples were matched by age and sex. For a better discrimination between control and disease samples, Principal Component Analysis (PCA) was applied to spectra data at specific regions, namely 3500-2700 cm-1, 1700-1400 cm-1, and 1200-900 cm-1. This allowed to identify the main pathological changes that occurred at the biochemical level during neurodegenerative disorder development. In the former spectral region, disease samples presented a higher content of saturated lipids in relation to the unsaturated ones, which translates in a high potential brain damage. Besides, it was also noted the presence of carboxylic acids that are usually related to lipid hyperoxidation, production of reactive carbonyls and proteins structural and functional alterations. In turn, the spectral region 1700-1400 cm-1 allowed to identify differences in protein conformation between control and disease samples, and these last ones were still related with occurrence of protein aggregates. In other hand, the 1200-900 cm-1 region could be associated to cellular damage provoked by oxidative stress in disease samples. As an important note to take, FTIR analysis could have the potential to be applied in future not only for cognitive impairment diagnosis but also for identification of disease stage and prognostic evaluation, besides assessment of disease developing risk for control subjects. Os atuais critérios clínicos de diagnóstico da doença de Alzheimer geralmente identificam a patologia apenas quando os pacientes já atingiram a fase de demência, ou seja, o estágio mais avançado da doença. Isto revela-se demasiado tarde para que qualquer tipo de terapêutica seja bem-sucedida e, consequentemente é necessário desenvolver uma metodologia de diagnóstico que permita um reconhecimento mais precoce da doença. Desta forma, é preciso adotar diferentes abordagens para a descoberta de novos biomarcadores para a doença de Alzheimer, tais como a utilização de técnicas de metabolómica (ex. FTIR). O potencial do FTIR no campo clínico recebeu recentemente particular atenção, sendo que esta técnica utiliza as frequências de vibração das moléculas presentes na amostra analisada para produzir uma “impressão digital” metabólica, a qual é específica para cada amostra. Esta dissertação tem como objetivo a identificação de potenciais alterações bioquímicas que possam estar relacionadas com demência, tornando possível a distinção entre grupos controlo e de doentes no seio do conjunto de amostras de plasma analisadas. A utilização de amostras de plasma torna o processo minimamente invasivo, de entre outras vantagens clínicas. Para além da colheita das amostras de sangue utilizadas neste projeto, os voluntários foram submetidos a uma avaliação cognitiva através da realização do MMSE e do CDR, com outra informação clínica relevante a ser também recolhida. Todas as amostras analisadas foram emparelhadas de acordo com a idade e o sexo. Para uma melhor distinção entre amostras controlo e de doentes foi aplicada a metodologia de PCA aos dados dos espectros obtidos em regiões específicas, nomeadamente em 3500-2700 cm-1, 1700-1400 cm-1, e 1200-900 cm-1. Isto permitiu identificar as principais alterações patológicas que ocorrem a nível bioquímico durante o desenvolvimento da doença neurodegenerativa. Na primeira região espectral referida, as amostras dos doentes apresentaram um maior conteúdo de lípidos saturados comparativamente aos não saturados, o que se traduz num potencial risco cerebral maior. Para além disso, foi observada a presença de ácidos carboxílicos, usualmente relacionados com hiperoxidação de lípidos, produção de carbonilos reativos e alterações estruturais e funcionais de proteínas. Por sua vez, a região espectral 1700-1400 cm-1 permitiu identificar diferenças na conformação de proteínas entre amostras controlo e de doentes, tendo estas últimas sido ainda relacionadas com a ocorrência de agregados proteicos. Por outro lado, a região 1200-900 cm-1 pôde ser relacionada com presença de danos celulares provocados por stress oxidativo nas amostras de doentes. Como importante nota a reter, a análise por FTIR pode ter o potencial para ser aplicada no futuro não apenas para diagnóstico de disfunção cognitiva, mas também para identificação do estádio da doença e realização de prognósticos, para além da avaliação do risco de desenvolvimento da doença em sujeitos controlo.

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Padilla, Cerezo Berizohar. "Computer-Aided Diagnoses (CAD) System: An Artificial Neural Network Approach to MRI Analysis and Diagnosis of Alzheimer’s Disease (AD)." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1837.

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Alzheimer’s disease (AD) is a chronic and progressive, irreversible syndrome that deteriorates the cognitive functions. Official death certificates of 2013 reported 84,767 deaths from Alzheimer’s disease, making it the 6th leading cause of death in the United States. The rate of AD is estimated to double by 2050. The neurodegeneration of AD occurs decades before symptoms of dementia are evident. Therefore, having an efficient methodology for the early and proper diagnosis can lead to more effective treatments. Neuroimaging techniques such as magnetic resonance imaging (MRI) can detect changes in the brain of living subjects. Moreover, medical imaging techniques are the best diagnostic tools to determine brain atrophies; however, a significant limitation is the level of training, methodology, and experience of the diagnostician. Thus, Computer aided diagnosis (CAD) systems are part of a promising tool to help improve the diagnostic outcomes. No publications addressing the use of Feedforward Artificial Neural Networks (ANN), and MRI image attributes for the classification of AD were found. Consequently, the focus of this study is to investigate if the use of MRI images, specifically texture and frequency attributes along with a feedforward ANN model, can lead to the classification of individuals with AD. Moreover, this study compared the use of a single view versus a multi-view of MRI images and their performance. The frequency, texture, and MRI views in combination with the feedforward artificial neural network were tested to determine if they were comparable to the clinician’s performance. The clinician’s performances used were 78 percent accuracy, 87 percent sensitivity, 71 percent specificity, and 78 percent precision from a study with 1,073 individuals. The study found that the use of the Discrete Wavelet Transform (DWT) and Fourier Transform (FT) low frequency give comparable results to the clinicians; however, the FT outperformed the clinicians with an accuracy of 85 percent, precision of 87 percent, sensitivity of 90 percent and specificity of 75 percent. In the case of texture, a single texture feature, and the combination of two or more features gave results comparable to the clinicians. However, the Gray level co-occurrence matrix (GLCOM), which is the combination of texture features, was the highest performing texture method with 82 percent accuracy, 86 percent sensitivity, 76 percent specificity, and 86 percent precision. Combination CII (energy and entropy) outperformed all other combinations with 78 percent accuracy, 88 percent sensitivity, 72 percent specificity, and 78 percent precision. Additionally, a combination of views can increase performance for certain texture attributes; however, the axial view outperformed the sagittal and coronal views in the case of frequency attributes. In conclusion, this study found that both texture and frequency characteristics in combinations with a feedforward backpropagation neural network can perform at the level of the clinician and even higher depending on the attribute and the view or combination of views used.

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Jensen, Jordan Royce. "Development of Tau-Selective Imaging Agents for Improved Diagnosis of Alzheimer’s Disease and Other Tauopathies." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1306441097.

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Aderghal, Karim. "Classification of multimodal MRI images using Deep Learning : Application to the diagnosis of Alzheimer’s disease." Thesis, Bordeaux, 2021. http://www.theses.fr/2021BORD0045.

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Dans cette thèse, nous nous intéressons à la classification automatique des images IRM cérébrales pour le diagnostic de la maladie d’Alzheimer (MA). Nous cherchons à construire des modèles intelligents qui fournissent au clinicien des décisions sur l’état de la maladie d’un patient à partir de caractéristiques visuelles extraites d’images IRM. L’objectif consiste à classifier les patients (sujets) en trois catégories principales : sujets sains (NC), sujets atteints de troubles cognitifs légers (MCI), et sujets atteints de la maladie d’Alzheimer (AD). Nous utilisons des méthodes d’apprentissage profond (Deep learning), plus précisément les réseaux neuronaux convolutifs (CNN) basés sur des biomarqueurs visuels à partir d’images IRM multimodales (IRM structurelle et l’IRM de tenseur de diffusion - DTI), pour détecter les changements structurels dans le cerveau, en particulier dans la région hippocampique du cortex limbique. Nous proposons une approche appelée "2-D+e" appliquée sur notre ROI (Region-of-Interest): hippocampe. Cette approche permet d’extraire des coupes 2D à partir de trois plans (sagittale, coronale et axiale) de notre région en préservant les dépendances spatiales entre les coupes adjacentes selon chaque dimension. Nous présentons une étude complète de différentes méthodes artificielles d’augmentation de données, ainsi que différentes approches d’équilibrage de données pour analyser l’impact de ces conditions sur nos modèles pendant la phase d’entraînement. Ensuite, nous proposons nos méthodes pour combiner des informations provenant de différentes sources (projections/modalités) avec notamment deux stratégies de fusion (fusion précoce et fusion tardive). Enfin, nous présentons des schémas d’apprentissage par transfert en introduisant trois cadres : (i) un schéma inter-modale (IRM structurelle et DTI), (ii) un schéma inter-domaine qui implique des données externes (MNIST), (iii) et un schéma hybride avec ces deux méthodes (i) et (ii). Les méthodes que nous proposons conviennent à l’utilisation des réseaux (CNN) peu profonds pour les images IRM multimodales. Elles donnent des résultats encourageants même si le modèle est entraîné sur de petits ensembles de données, ce qui est souvent le cas en analyse d’images médicales In this thesis, we are interested in the automatic classification of brain MRI images to diagnose Alzheimer’s disease (AD). We aim to build intelligent models that provide decisions about a patient’s disease state to the clinician based on visual features extracted from MRI images. The goal is to classify patients (subjects) into three main categories: healthy subjects (NC), subjects with mild cognitive impairment (MCI), and subjects with Alzheimer’s disease (AD). We use deep learning methods, specifically convolutional neural networks (CNN) based on visual biomarkers from multimodal MRI images (structural MRI and DTI), to detect structural changes in the brain hippocampal region of the limbic cortex. We propose an approach called "2-D+e" applied to our ROI (Region-of-Interest): the hippocampus. This approach allows extracting 2D slices from three planes (sagittal, coronal, and axial) of our region by preserving the spatial dependencies between adjacent slices according to each dimension. We present a complete study of different artificial data augmentation methods and different data balancing approaches to analyze the impact of these conditions on our models during the training phase. We propose our methods for combining information from different sources (projections/modalities), including two fusion strategies (early fusion and late fusion). Finally, we present transfer learning schemes by introducing three frameworks: (i) a cross-modal scheme (using sMRI and DTI), (ii) a cross-domain scheme that involves external data (MNIST), and (iii) a hybrid scheme with these two methods (i) and (ii). Our proposed methods are suitable for using shallow CNNs for multimodal MRI images. They give encouraging results even if the model is trained on small datasets, which is often the case in medical image analysis

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Beckett, Christina. "VARIANCE OF THE AMYLOID BETA PEPTIDE AS A METRIC FOR THE DIAGNOSIS OF ALZHEIMER'S DISEASE." UKnowledge, 2016. http://uknowledge.uky.edu/medsci_etds/6.

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Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder associated with aging. AD is by far the best understood and most studied neurodegenerative disease. Substantial advances have been made over the last decade, however it is debatable how much closer we are to a clinically useful therapy. A long standing goal in the AD field has been to improve the accuracy of early detection, with the assumption that the ability to intervene earlier in the disease process will lead to a better clinical outcome. Major facets of this effort have been the continued development and improvement of AD biomarkers, with a strong focus on developing imaging modalities. AD is accompanied by two pathological hallmarks in the brain: extracellular neuritic plaques composed of the beta-amyloid peptide (Aβ) and intracellular neurofibrillary tangles (NFTs) composed of hyperphosphorylated tau protein. Evidence of Aβ as the driving force behind the progression of AD (the amyloid cascade hypothesis) was first published by Hardy & Higgins in 1992, and this peptide has been the focus of therapeutic and diagnostic testing for decades. Significant technological advances in recent years now allow imaging of amyloid pathology in vivo. These methods evaluate Aβ burden in a living person, and could potentially serve as both a biomarker, and as a diagnostic tool to detect disease. Pittsburgh Compound B (PiB) is currently the best studied of these imaging agents, however, our current knowledge of the quantitative relationship between PiB binding and amyloid pathology in the brain is limited. A better understanding of how these variables relate to one another is essential for the continued development of reliable diagnostic biomarkers for AD. We analyzed increasingly insoluble pools of Aβ to quantify their relative contributions to the overall Aβ burden, and to determine if any of these measures could be used to predict disease status. We found that the amount of PiB binding in a cortical region of the brain could distinguish cases of mild cognitive impairment (MCI) when corrected to the amount of PiB binding in the cerebellum. As the Aβ peptide ages, the amino acid aspartate may spontaneously convert to an isoaspartate residue through a succinimide intermediary. The presence of iso-Asp Aβ has been used to indicate the presence of aged plaques in AD and Down syndrome cases. We sought to investigate the potential relationship between levels of ‘aged’ Aβ in the plasma as indicated by iso-Asp Aβ and disease state, as a potential biomarker for the presence of AD pathology. We found that AD cases had lower levels of all forms of Aβ in plasma when standardized to the group average, and that plasma levels of Aβ and iso-Asp Aβ were reversed between disease groups. A follow up study is required, however, these initial data are a promising step towards utilizing aged iso-Asp Aβ plasma levels as a potential biomarker to indicate disease state.

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Sundström, Torbjörn. "Human brain function evaluated with rCBF-SPECT : memory and pain related changes and new diagnostic possibilities in Alzheimer’s disease." Doctoral thesis, Umeå universitet, Diagnostisk radiologi, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-761.

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The aim of this doctoral thesis was to study the influence of memory, pain, age and education on the regional cerebral blood flow (rCBF), i.e. brain function, in early Alzheimer's disease (AD) and in chronic neck pain patients in comparison to healthy controls and in healthy elderly per se. This was done by optimizing single photon emission computed tomography (SPECT) as a method to study rCBF with the tracer Technetium-99m (99mTc) hexamethylpropyleneamine oxime (HMPAO) and by matching all image data to a brain atlas before evaluation. The rCBF-SPECT was evaluated and developed to obtain higher diagnostic accuracy in AD and in chronic neck pain patients it was used to study basic pain related cerebral processes in chronic pain of different origin. A new semimanual registration method, based on fiducial marker, suitable for investigations with low spatial resolution was developed. The method was used to reconstruct images with an improved attenuation and scatter correction by using an attenuation-map calculated from the patients' previously acquired CT images. The influence of age and education on rCBF was evaluated with statistical parametric mapping, SPM in healthy elderly. The main findings were age related changes in rCBF in regions close to interlobar and interhemispheric space but not in regions typically affected in early AD, except for the medial temporal lobe. The theory of a 'cognitive reserve' in individuals with a longer education was supported with findings in the lateral temporal lobe, a region related to semantic memory, and in the frontal lobe. A cross-sectional study of chronic neck pain patients showed extensive rCBF changes in coping related regions in a non-traumatic pain patients compared to both healthy and a pain group with a traumatic origin, i.e. whiplash syndrome. The whiplash group displayed no significant differences in rCBF in comparison with the healthy controls. This suggests different pain mechanisms in these groups. The AD-patients showed a significantly lower rCBF in temporoparietal regions including left hippocampus. These changes were associated to episodic memory performance, and especially to face recognition. The diagnostic sensitivity for AD was high. The face recognition test (episodic memory) was used in AD patients to improve the sensitivity of method, i.e. memory-provoked rCBF-SPECT (MP-SPECT). The results were compared to healthy controls and the reductions of rCBF in temporoparietal regions were more pronounced in mild AD during provocation. Memory provocation increased the sensitivity of AD-related rCBF changes at group level. If a higher sensitivity for AD at the individual level is verified in future studies, a single MP-SPECT study might then be of help to set diagnosis earlier. In conclusion rCBF in temporoparietal regions are associated to an impaired episodic memory in early AD. Changes in these regions do not have a strong connection to chronological age. The diagnostic sensitivity of rCBF-SPECT in AD is high and there is a potentially higher sensitivity if memory provoked investigations are used. The findings in this thesis have given an increased knowledge of underlying cerebral pain processing in non-traumatic and traumatic (whiplash) neck pain. Preliminary results supporting the theory of 'cognitive reserve' by showing a correlation between long education and preserved rCBF was found in healthy elderly.

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Martí, Juan Gerard. "Data-driven methods to characterize heterogeneity in Alzheimer’s disease using cross-sectional and longitudinal data." Doctoral thesis, Universitat Pompeu Fabra, 2021. http://hdl.handle.net/10803/671269.

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Alzheimer's disease (AD), the most common form of dementia, is an incurable neurodegenerative disease that affects millions of elderly people worldwide. Detecting the disease in its early stages is the key for a more effective treatment. AD is a multifactorial disease, where several biomarkers represent different pathophysiological processes in the brain, with distinct progression paths over time. Methods to facilitate the integration and interpretation of longitudinal, heterogeneous medical data could be of benefit for a better understanding of the disease and its progression. In this thesis, we present statistical and machine learning methods and studies for early detection and to assess disease progression. Contributions of this thesis are as follows: First, we present a review on machine learning applications in AD using longitudinal neuroimaging data: we analyze their approach to typical challenges in longitudinal data analysis and show that machine learning methods using this type of data have potential to improve disease progression modelling and computer-aided diagnosis. Our second contribution is a study of AD subtyping using novel plasma-based blood biomarkers. We used a multivariate, unsupervised multiple kernel learning method over blood-based biomarkers to find subgroups of patients defined by distinctive blood biomarker profiles, and we analyze those subgroups using cross-sectional and longitudinal neuroimaging data. Our third contribution is a novel method based on recurrent, multimodal variational autoencoders to model the progression of the disease. It can use a variable number of modalities and time-points across different subjects, and we show its performance quantitatively and qualitatively. Our fourth and final contribution is an analysis of the impact of APOE ε4 gene dose and its association with age on hippocampal shape, assessed with multivariate surface analysis, using a cognitive healthy, ε4-enriched cohort. La malaltia d'Alzheimer, o simplement Alzheimer, és una malaltia neurodegenerativa incurable que afecta milions de persones a tot el món. La detecció de la malaltia en els seus primers estadis és clau per a un tractament més eficaç. L’Alzheimer és una malaltia multifactorial, on diversos marcadors representen processos fisiopatològics diferents al cervell, amb diferents tipus de progressió al llarg del temps. Mètodes per facilitar la integració i la interpretació de dades mèdiques longitudinals i heterogènies poden ser útils per aconseguir una millor comprensió de la malaltia i la seva progressió. En aquesta tesi presentem mètodes estadístics i d’aprenentatge automàtic per a la detecció precoç i per avaluar la progressió de la malaltia. Les contribucions d’aquesta tesi són les següents: En primer lloc, presentem una revisió de mètodes d’aprenentatge automàtic aplicats a l'Alzheimer que utilitza dades de neuroimatge longitudinals: analitzem el seu enfocament als desafiaments típics en l’anàlisi d'aquestes dades i demostrem que els mètodes d’aprenentatge automàtic que utilitzen dades longitudinals tenen potencial per a millorar la modelització de la progressió de la malaltia i el diagnòstic assistit per ordinador. La nostra segona contribució és un estudi de subtipatge de l'Alzheimer mitjançant biomarcadors sanguinis basats en plasma. Utilitzem un mètode multivariat i no supervisat en biomarcadors sanguinis per trobar subgrups de pacients definits per perfils distintius d'aquests biomarcadors, i analitzem aquests subgrups utilitzant dades de neuroimatge transversal i longitudinal. La nostra tercera contribució és un mètode basat en "recurrent variational autoencoders", un tipus de xarxa neuronal, per modelar la progressió de la malaltia. El mètode utilitza un nombre variable de modalitats i adquisicions en diferents pacients, i mostrem el seu rendiment quantitativament i qualitativament. La nostra quarta i última contribució és una anàlisi de l’impacte del gen APOE ε4 i la seva associació amb l’edat en la superfície de l’hipocamp, evaluada amb un anàlisi multivariat sobre una cohort amb alta proporció de pacients sans amb el gen ε4.

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Kolanowski, Mikael, and David Stevens. "A Comparative Study of the Effect of Features on Neural Networks within Computer-Aided Diagnosis of Alzheimer's Disease." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-255260.

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Alzheimer’s disease is a neurodegenerative disease that affects approximately 6% of the global population aged over 65 and is forecasted to become even more prevalent in the future. Accurately diagnosing the disease in an early stage can play a large role in improving the quality of life for the patient. One key development for performing this diagnosis is applying machine learning to perform computer-aided diagnosis. Current research in the field has been focused on removing assumptions about the used data sets, but in doing so they have often discarded objective metadata such as the patient’s age, sex or priormedical history. This study aimed to investigate the effect of including such metadata as additional input features to neural networks used for diagnosing Alzheimer’s disease through binary classification of magnetic resonance imaging scans. Two similar neural networks were developed and compared, one with these additional features and the other without them. Including the metadata led to significant improvements in the network’s classification accuracy, and should therefore be considered in future computer-aided diagnostic systems for Alzheimer’s disease. Alzheimers sjukdom är en form av demens som påverkar ungefär 6% av den globala befolkningen som är äldre än 65 och förutspås bli ännu vanligare i framtiden. Tidig diagnos av sjukdomen är viktigt för att säkerställa högre livskvalitet för patienten. En viktig utveckling inom fältet är datorstödd diagnos av sjukdomen med hjälp av maskininlärning. Dagens forskning fokuserar på att ta bort subjektiva antaganden om datamängden som används, men har ofta även förkastat objektiv metadata såsom patientens ålder, kön eller tidigare medicinska historia. Denna studier ämnade därför undersöka om inkluderandet av denna metadata ledde till bättre prestanda hos neuronnät som används för datorstödd diagnos av Alzheimers genom binär klassificering av bilder tagna med magnetisk resonanstomografi. Två snarlika neuronnät utvecklades och jämfördes, med skillnaden att den ena även tog metadata om patienten som indata. Inkluderandet av metadatan ledde till en markant ökning i neuronnätets prestanda, och bör därför övervägas i framtida system för datorstödd diagnos av Alzheimers sjukdom.

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Lopes, Jéssica Sousa. "FTIR, a potential tool to dementia diagnosis trough analysis of plasma." Master's thesis, Universidade de Aveiro, 2016. http://hdl.handle.net/10773/16149.

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Mestrado em Biomedicina Molecular Nowadays it is still difficult to perform an early and accurate diagnosis of dementia, therefore many research focus on the finding of new dementia biomarkers that can aid in that purpose. So scientists try to find a noninvasive, rapid, and relatively inexpensive procedures for early diagnosis purpose. Several studies demonstrated that the utilization of spectroscopic techniques, such as Fourier Transform Infrared Spectroscopy (FTIR) and Raman spectroscopy could be an useful and accurate procedure to diagnose dementia. As several biochemical mechanisms related to neurodegeneration and dementia can lead to changes in plasma components and others peripheral body fluids, blood-based samples and spectroscopic analyses can be used as a more simple and less invasive technique. This work is intended to confirm some of the hypotheses of previous studies in which FTIR was used in the study of plasma samples of possible patient with AD and respective controls and verify the reproducibility of this spectroscopic technique in the analysis of such samples. Through the spectroscopic analysis combined with multivariate analysis it is possible to discriminate controls and demented samples and identify key spectroscopic differences between these two groups of samples which allows the identification of metabolites altered in this disease. It can be concluded that there are three spectral regions, 3500-2700 cm -1, 1800-1400 cm-1 and 1200-900 cm-1 where it can be extracted relevant spectroscopic information. In the first region, the main conclusion that is possible to take is that there is an unbalance between the content of saturated and unsaturated lipids. In the 1800-1400 cm-1 region it is possible to see the presence of protein aggregates and the change in protein conformation for highly stable parallel β-sheet. The last region showed the presence of products of lipid peroxidation related to impairment of membranes, and nucleic acids oxidative damage. FTIR technique and the information gathered in this work can be used in the construction of classification models that may be used for the diagnosis of cognitive dysfunction. Atualmente, não é possível fazer um diagnóstico precoce e diferencial da doença de Alzheimer, deste modo, é necessário encontrar biomarcadores que o permitam. Para isso, os cientistas tentam encontrar um procedimento nãoinvasivo, rápido, e relativamente barato. Os resultados de vários estudos demonstraram que a utilização de técnicas espectroscópicas, tais como a Espectroscopia de Infravermelho Transformada de Fourier (FTIR) e / ou espectroscopia de Raman, podem ser ferramentas úteis para diagnosticar a DA. Uma vez que, na DA, alguns mecanismos bioquímicos podem levar a mudanças em componentes do plasma, podem então ser utilizadas amostras de sangue nas análises espectroscópicas o que torna a técnica simples e menos invasiva. Com este trabalho pretende-se confirmar algumas das hipóteses de estudos anteriores em que o FTIR foi usado no estudo de amostras de plasma de possíveis doentes com DA e respetivos controlos e verificar a reprodutibilidade desta técnica espectroscópica na análise deste tipo de amostras. Através da análise espectroscopia combinada com análise multivariada é possível discriminar as amostras controlos e dementes e identificar as principais diferenças espectroscópicas entre estes dois grupos de amostras que permitem identificar os metabolitos alterados nesta patologia. Pode-se concluir que existem três regiões espectrais, 3500-2700 cm-1, 18001400 cm-1 e 1200-900 cm-1 onde se pode extrair informação espectroscópica relevante. Na primeira região, a principal conclusão que é possível tirar é que há um desequilíbrio entre o teor de lípidos saturados e insaturados. Na região entre 1800-1400 cm-1, é possível observar a presença de agregados de proteínas e a alteração na conformação das proteínas para folha β paralela altamente estável. A última região revelou a presença de produtos de peroxidação lipídica relacionados com a insuficiência de membranas, e danos oxidativos nos ácidos nucleicos. A técnica de FTIR e a informação reunida neste trabalho pode ser utilizada na construção de modelos de classificação que possam vir a ser utilizados para o diagnóstico de disfunções cognitivas.

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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.

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Walters, Elizabeth R. "Factors affecting neuropsychological testing in the elderly and the use of a newly developed virtual reality test. Implications for the accurate and early diagnosis of Alzheimer's disease." Thesis, University of Bradford, 2013. http://hdl.handle.net/10454/7353.

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Neuropsychological testing is one method used in the diagnosis of Alzheimer’s disease and other cognitive disorders. However, the testing process may be affected by subtle external factors which if not controlled for may have the ability to affect the scores obtained. The primary aim of this thesis was to investigate the effects of some of these external factors, namely caffeine, non-oily fish consumption and time of day. A secondary aim was to evaluate the use of a novel virtual assessment as a possible tool for the early detection of AD. Healthy elderly participants over the age of sixty with no existing cognitive impairment or neurological condition were recruited to take part. For each external factor investigated participants were required to undertake a cognitive assessment. The results demonstrated that subtle external factors present during a typical testing session have the ability to significantly affect the scores obtained. Scores on one part of the virtual test correlated with existing tests used for the early detection of cognitive impairment and were significantly lower in participants classified as mildly impaired. With further modification this test has the potential to be used as an early detection tool. The results have implications for the interpretation of neuropsychological test scores which may be considered when classifying participants, determining treatment interventions, selecting participants for research and making a diagnosis. These findings have important considerations for psychological and cognitive research that investigates human brain function.

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Walters, Elizabeth Rachel. "Factors affecting neuropsychological testing in the elderly and the use of a newly developed virtual reality test : implications for the accurate and early diagnosis of Alzheimer's disease." Thesis, University of Bradford, 2013. http://hdl.handle.net/10454/7353.

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Neuropsychological testing is one method used in the diagnosis of Alzheimer’s disease and other cognitive disorders. However, the testing process may be affected by subtle external factors which if not controlled for may have the ability to affect the scores obtained. The primary aim of this thesis was to investigate the effects of some of these external factors, namely caffeine, non-oily fish consumption and time of day. A secondary aim was to evaluate the use of a novel virtual assessment as a possible tool for the early detection of AD. Healthy elderly participants over the age of sixty with no existing cognitive impairment or neurological condition were recruited to take part. For each external factor investigated participants were required to undertake a cognitive assessment. The results demonstrated that subtle external factors present during a typical testing session have the ability to significantly affect the scores obtained. Scores on one part of the virtual test correlated with existing tests used for the early detection of cognitive impairment and were significantly lower in participants classified as mildly impaired. With further modification this test has the potential to be used as an early detection tool. The results have implications for the interpretation of neuropsychological test scores which may be considered when classifying participants, determining treatment interventions, selecting participants for research and making a diagnosis. These findings have important considerations for psychological and cognitive research that investigates human brain function.

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Malhis, Marwa [Verfasser], and Susanne Aileen [Akademischer Betreuer] Funke. "Selection and characterization of D-enantiomeric peptides for the investigation of options for therapy and diagnosis of Alzheimer’s disease / Marwa Malhis ; Betreuer: Susanne Aileen Funke." Bayreuth : Universität Bayreuth, 2021. http://d-nb.info/1240309651/34.

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Wen, Junhao. "Structural and microstructural neuroimaging for diagnosis and tracking of neurodegenerative diseases." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS415.

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L’identification et le suivi de biomarqueur de la démence sont essentiels pour mieux comprendre les mécanismes pathologiques et la trajectoire de la maladie. Le diagnostic précoce de la démence constitue un autre défi. Cette thèse a deux objectifs principaux. Premièrement, nous cherchons à identifier les biomarqueurs les plus prometteurs au stade présymptomatique de la démence. Plus spécifiquement, nous avons étudié ce phénomène dans le cas de la dégénérescence lobaire frontotemporale due à la mutation C9orf72. Le deuxième objectif est de faire progresser le diagnostic et le pronostic précoces en utilisant des méthodes d’apprentissage machine et des données d’imagerie par résonance magnétique. Nous abordons cette question dans le contexte de la maladie d’Alzheimer sporadique. Suivant ces deux objectifs, la thèse se compose de deux parties principales, chaque partie comprenant deux études. Dans la première étude, les biomarqueurs ont été identifiés à partir de l’IRM conventionnelle pondérée T1 et du modèle d’imagerie du tenseur de diffusion. La deuxième étude a comparé la sensibilité et la spécificité du modèle NODDI et celle de techniques conventionnelles, à savoir l’IRM pondérée en T1 et le DTI. La deuxième partie porte sur le diagnostic précoce de la MA et comprend les deux dernières études. La troisième étude propose un cadre open source pour une évaluation reproductible de la classification de la MA à l’aide de l’IRM de diffusion et des méthodes classiques d’apprentissage. La dernière étude étend ce cadre aux méthodes d’apprentissage profond et démontre son utilisation sur l’IRM pondérée en T1 Biomarker identification and tracking in dementia are essential to better understand the pathological mechanism and disease trajectory. The current PhD aims has two main objectives. First, we aim to identify the most promising biomarkers at the presymptomatic stage of dementia. More specifically, we studied this in the case of genetic frontotemporal lobar degeneration due to C9orf72 mutation. The second objective is to advance early diagnosis and prognosis by using machine learning methods with magnetic resonance imaging data. We tackle this in the context of sporadic Alzheimer’s disease. According to these two objectives, the thesis consists of two main parts, each part comprising two studies. In the first study, biomarkers were identified from conventional T1-weighted MRI and diffusion tensor imaging model. The second study compared the sensitivity and specificity of the advanced NODDI model and to that of conventional techniques, namely T1-weighted MRI and DTI. The second part focuses on early diagnosis of AD and comprises the last two studies. The third study proposes an open source framework for reproducible evaluation of AD classification using diffusion MRI and conventional ML methods. The last study extends this framework to deep learning methods and demonstrates its use on T1-weighted MRI

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Hamelin, Lorraine. "Analyse de la morphologie des sillons corticaux et de l'activation microgliale dans la maladie d'Alzheimer : étude couplée en IRM, TEP-PiB et TEP-DPA Sulcal morphology as a new imaging marker for the diagnosis of early onset Alzheimer’s disease Early and protective microgial activation in Alzheimer's diease: a prospective study using 18F-DPA-714 PET imaging Distinct dynamic profiles of microglial activation are associated with progression of Alzheimer’s disease." Thesis, Sorbonne Paris Cité, 2018. https://wo.app.u-paris.fr/cgi-bin/WebObjects/TheseWeb.woa/wa/show?t=2327&f=13526.

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La maladie d’Alzheimer (MA) est la première cause de démence dégénérative. Elle est ‏définie par l’accumulation anormale des protéines Tau et myloïdes, constituant des plaques‏ amyloïdes. Alors que l’atteinte neuro-pathologique de la MA est stéréotypée chez les malades, son ‏expression clinique et son pronostic sont hétérogènes. Les facteurs modulant l’expression de la ‏maladie sont actuellement peu connus.‏ Dans ce travail, nous avons analysé deux facteurs modulateurs de l’expression de la ‏maladie : l’âge et l’activation microgliale que nous avons étudié au sein d’une population de sujets‏ atteints de la MA (aux stades débutant et sévère) et de témoins, définis sur des critères‏ diagnostiques clinico-biologiques.‏Nous avons tout d’abord analysé l’effet de l’âge sur la modification de la morphologie des ‏sillons corticaux au cours de la MA. Nous avons mesuré l’ouverture des sillons corticaux ainsi que ‏le volume hippocampique sur l’IRM cérébrale de sujets MA jeunes (<65 ans), de sujets MA plus ‏âgés (>65 ans) ainsi que chez des sujets témoins appariés à l’âge. Dans un second temps, nous étudié ‏l’activation microgliale en quantifiant la fixation du ligand [18F]-DPA-14, grâce à la tomographie ‏par émission de positrons (TEP) au sein d’une population de sujets MA et de témoins suivis‏ cliniquement pendant deux ans. Finalement, nous avons mesuré et comparé l’évolution de‏ l’activation microgliale au cours du temps entre des sujets MA et des témoins, qui ont bénéficié de ‏la réalisation d’un second examen TEP. ‏Nos hypothèses étaient (1) que l’étude de la morphologie des sillons corticaux était plus ‏performante que la mesure du volume hippocamique pour distinguer les formes jeunes de MA des‏ formes du sujet âgé, (2) qu’en comparaison aux témoins, l’activation microgliale était plus‏ importante chez les sujets MA et qu’elle influait sur la progression clinique de la maladie, et (3)‏qu’il existait différents profils évolutifs d’activation microgliale.‏Nos résultats montrent (1) que la mesure de l’ouverture des sillons corticaux est un meilleur ‏marqueur diagnostique que la mesure du volume hippocampique dans le groupe de sujets MA jeune,‏ dès le stade débutant de la maladie. A l’inverse, elle entraîne un risque de diagnostic par excès chez ‏le patient de plus de 65 ans, où l’effet de l’âge se confond avec celui de la maladie ; (2) l'activité‏ microgliale est augmentée précocement au cours de la MA et est associée à une stabilité cognitive et fonctionnelle de la MA. Finalement, (3) qu’il existe différents profils d’activation microgliale‏ au cours du temps, avec des retentissements distincts sur la progression de la MA. ‏ Au total, ces travaux confirment l'hétérogéneité de la maladie d'Alzheimer. L'étude des‏effets de l'âge et de l'activation microgliale au sein d'une population atteinte d'une MA met en‏ évidence des sous-types de malades avec une expression et des trajectoires évolutives distinctes ; ‏les sujets jeunes présentent une expression corticale de la maladie plus étendue et les sujets avec‏ une faible activation de la microglie ont une dégradation fonctionnelle et cognitive plus sévère. ‏Ces facteurs de variabilité ouvrent des pistes de recherche clinique mais aussi‏ thérapeutiques. Ils pourraient être pris en compte dans les protocoles thérapeutiques ultérieurs. ‏ No abstract

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Andreasen, Niels. "Search for reliable diagnostic markers for Alzheimer's disease /." Stockholm, 2000. http://diss.kib.ki.se/2000/91-628-4039-8/.

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Wang, Xueli. "Organic molecules for diagnosis and therapy of Alzheimer's disease." HKBU Institutional Repository, 2020. https://repository.hkbu.edu.hk/etd_oa/883.

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Alzheimer's disease has become one of the most common diseases jeopardizing the health of the human being. The main pathological feature of AD is the accumulation of Aβ in the brain to form senile plaques. Therefore, it is of great significance to develop new and efficient drugs targeting at amyloid-β for the detection, diagnosis and therapeutics for Alzheimer's disease. Xanthohumol (Xn) naturally presents in hops (Humulus lupulus L). Studies have shown that it has anti-lipoperoxidative, anti-inflammatory, anti-proliferative activities, antiangiogenic and antioxidant effects, which further illustrates its potential therapeutic for AD. However, the bio-incompatibility and blood-brain barrier impermeability of Xanthohumol hindered it in vivo efficacy potential for treating Alzheimer's disease. Thus, we designed and prepared a series of Xanthohumol derivatives, namely, Xn-n, (n = 1-9) and its chalcone derivatives C-n, (n = 1-10) to enhance the desirable physical, biological and pharmacological properties, especially the blood-brain barrier permeability for intervention of AD. As an effective technique for in vivo visualization, Near-infrared fluorescence imaging based on organic small molecule probes has a promising application in the diagnosis of Alzheimer's disease. However, most of the reported imaging probes can only visualize Aβ-plaques but do not have therapeutic potential such as neuroprotection against Aβ induced toxicity. Herein, we designed and synthesized a series of oligomeric Aβ targeted near infrared (NIR) fluorescent probes for the diagnosis and therapeutics of Alzheimer's disease, namely DBAN-SLM, DBAN-SLOH, DBAN-OSLM which showed remarkably effective inhibitory effect on Aβ aggregation, significant neuroprotection effect against the Aβ-induced toxicities, and suppression on Aβ-induced ROS generation. indicating its great promise as a useful theragnostic agent for the early diagnosis and therapy of AD. Dual-modal imaging is an important approach to overcome the limitations of single imaging technology in the diagnosis of AD disease. Therefore, based on the dual-modal, we designed and synthesized the NIR/MR dual-modal detection and theragnostic probes namely Dyad-1, Dyad-2, Dyad-3 and NP@SiO2@F-SLOH. More surprising is that the two NIR/MR dual-modal probes show excellent biological properties, including the ability to inhibit Aβ aggregation to a certain extent, neuroprotective effects on cytotoxicity caused by different forms of Aβ species, blood-brain barrier (BBB) permeability, and high stability. All of these newly designed and synthesized molecules were characterized with 1H NMR, 13C NMR, and HRMS and found to show good agreement with the desired structures. The photophysical properties and biological properties of these novel designed and synthesized fluorescent probe such as UV-vis absorption, fluorescence emission, dissociation constant determined by fluorescence titration, cytotoxicity assay, neuroprotection, and inhibition of Aβ aggregation were investigated

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Haigh, Anne-Marie Francoise. "The Alzheimer's Disease Life Events Study." Thesis, Oxford Brookes University, 2009. http://radar.brookes.ac.uk/radar/items/9c1acdb7-0df9-4046-ec50-810f9122e1d0/1.

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The Alzheimer's Disease Life Events study examines whether there is a relationship between life events and Alzheimer's disease (AD). The ADLE study uses a mixed methods approach to answer the central research question:Are life events a risk factor for Alzheimer's disease? The central research question uses the following theory questions to examine:1. Is there a difference between the number of life events between patients and controls, using the Life Events and Difficulties Schedule (LEDS)(Brown and Harris, 1978) as a measurement tool?2. Is there a difference in the way (i.e. positive, neutral and negative) life events are discussed and in the range of emotions expressed when discussing life events between the patients and controls? 3. Are there any differences in the narrative constructions of life events, as interpreted by the Biographic Narrative Interpretive Method (BNIM)(Wengraf, 2001, 2008) between the patient and control groups? 4. Can the differences, between the patient and control groups, in the narratives be developed into a diagnostic marker? 5. Can the Emotion Word Coding (EWC)(Danner et aI., 2000) be used as a diagnostic marker by being applied to text collected from patients and controls over a period of decades? The ADLE study found that the patient group had experienced more life events in comparison with the control group as defined by the LEOS (Brown and Harris, 1978), and that the patient group had experienced more bereavements under the age of 51 years. The evidence supports the association between life events and AD.Even though there were significantly more life events experienced by the patients, the EWC (Danner et aI., 2001) found significantly fewer discussions expressing emotion bythe patients, particularly the negatively described ones. The range of negative and positive words used to describe the life events was significantly fewer too. This implies that the ways the patients express emotions about life events is substantially different from the controls. This finding was mirrored in the thematic field analysis of the BNIM interviews (Wengraf, 2001, 2008), which found differences in the content and structure of the narratives, and the emotional expression in the narratives about life events. A tool has been constructed using the differences between patients and controls to contribute to the early diagnosis of AD. In addition, the ADLE study has contributed to a gap in the knowledge about life events and AD.

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Bogdanovic, Nenad. "Alzheimer's disease : towards a multifaceted approach in neuropathological diagnosis /." Stockholm, 1998. http://diss.kib.ki.se/1998/91-628-2846-0.

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28

Sayeed, Abdul. "Positron emission tomography analysis of Alzheimer's disease." Thesis, University of Surrey, 2001. http://epubs.surrey.ac.uk/842834/.

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Alzheimer's Disease (AD) is a major concern for the elderly population, currently affecting over 670,000 people in the UK. With the continual increase in the age of the population the problem is expected to rise. There is no known cure to the condition and a definite diagnosis cannot be made in life. Clinical diagnosis is considered to be approximately 80% - 90% accurate, sometimes taking up to a year to assess. Early detection could aid in the care and possible development of better treatments or even a cure. AD has been shown to alter the structure and global texture of the brain. Studies using Magnetic Resonance imaging (MRI) and Computerised Tomography (CT) have been used to detect these changes with some success by some researchers. Positron Emission Tomography (PET) imaging is a functional imaging modality and in theory before structural changes are evident functional changes should be apparent. Therefore we utilise PET images for this study. This thesis will exploit the fact that AD alters the global texture of the brain. Texture features extracted from fluoro-deoxy-glucose (FDG) PET images and sinograms of the brain will be used. Most texture feature extraction methods fail, due to poor signal to noise ratio so we will use a novel texture feature extraction method known as the Trace transform - triple features, which can extract features directly from raw data acquired by PET scanners. Classifiers will be used to aid in the separation of the two groups, namely AD patients and normal controls. The Trace transform - triple feature method has proven its potential as a good feature extraction technique. It enabled us to achieve classification accuracy of up to 93% on raw sinogram data using a combination of five features. This result is very good compared with the clinical accuracy of 80% reported by most researcher. It is comparable to results obtained by Kippenhan et al [52, 53, 51, 50], who used regional metabolic activity using PET and a neural network classifier. Monomial features extracted from images achieved accuracies as high as 87%. These features are good discriminators, however, they suffer from lack of scaling invariance. This is problematic as brain sizes do vary considerably. The use of registration and extraction of regional information failed to produce fruitful results. This is principally due to poor registration. The registration failed primarily because a very small cross section of the brain was available. Also the effect of AD alters the structure of the brain. Since the registration relies on matching structure, it becomes questionable whether one can actually register automatically a very degraded AD brain. Gender and age are crucial to the progress of Alzheimer's disease. Age and gender matching is not sufficient to get the best results. This thesis has shown that performance gains of up to 11% can be attained by simply incorporating age and/or gender into the classification model. However, the maximum classification accuracy was not improved any further.

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Creegan, Rhona. "Identification of plasma lipid biomarkers in Alzheimer's disease." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2014. https://ro.ecu.edu.au/theses/1340.

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Alzheimer’s disease (AD), the commonest form of dementia, is a chronic, progressive neurodegenerative disease which manifests clinically as a slow global decline in cognitive function, including deterioration of memory, reasoning, abstraction, language and emotional stability, culminating in a patient with end-stage disease, totally dependent on custodial care. With an ageing population, there is predicted to be a marked increase in the number of people diagnosed with AD in the coming decades, making this a significant challenge to socio-economic policy and aged care. Currently there is no cure for AD and while current therapies may temporarily ameliorate symptoms, death usually occurs approximately 8 years after diagnosis. Attention is now being directed to the discovery of biomarkers that may not only facilitate pre-symptomatic diagnosis but provide an insight into aberrant biochemical pathways that may reveal potential therapeutic targets. AD pathogenesis develops over many years before clinical symptoms appear, providing the opportunity to develop therapy that could slow or stop disease progression well before any clinical manifestations develop. Research and understanding of AD pathology has been driven in recent years by advances in technologies, enabling the precise investigation of the lipidome; the repertoire of lipid species present in cells and tissues that reflect the net effect of gene and protein expression, which in turn are influenced by the cellular environment. Lipidomic studies have identified abnormal lipid metabolism as a key component of the pathological processes which lead to the development of AD. Therefore, lipidomic studies are crucial for advancing the understanding of AD pathology and for identifying potential therapeutic targets; these studies may also facilitate biomarker discovery. Many studies have reported abnormal lipid profiles in both AD plasma and brain tissue. This thesis investigated plasma lipid species using a “shotgun” lipidomics approach by electrospray ionisation tandem mass spectrometry (ESI/MS/MS). Additionally, Phospholipid Transfer Protein (PLTP); a protein involved in lipid metabolism was assayed using a commercial kit. The utility of these analytes as potential AD biomarkers was investigated by testing plasma samples from the highly characterised Australian Imaging, Biomarkers and Lifestyle (AIBL) study. The study cohort comprised over 1000 participants at inception who were classified as either healthy control (n=733), mild cognitive impairment (MCI, n=125) or AD (n=204): Samples from the baseline and 18 month follow-up time points were utilised. Plasma PLTP activity levels were measured in a subset of the baseline samples (n=259). Lipid and PLTP measurements were analysed in conjunction with supplementary neuroimaging and blood biomarker data collected as part of the AIBL study. The thesis identified significant differences in several plasma lipids between clinical classification groups, including several ceramide, sphingomyelin (SM), phosphatidylethanolamine (PE), phosphatidylcholine (PC) and plasmalogen species. Additionally, a panel of lipids was identified which could distinguish AD participants from healthy controls with a sensitivity and specificity of 80%. Plasma PLTP activity was significantly lower in AD and MCI groups compared to healthy controls, and levels correlated with plasma Aβ in all groups and cerebral Aβ in the healthy controls. The results of this thesis validate and extend previous findings reported in the literature. The current findings provide evidence to indicate that several lipid species and PLTP show promise as potential blood biomarkers of AD. Further investigation using a targeted lipidomics platform and prospective longitudinal follow-up is warranted.

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Wons, Jonathan. "Alzheimer's disease--causes, risks, and diagnostic techniques." Thesis, Boston University, 2012. https://hdl.handle.net/2144/12681.

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Thesis (M.A.)--Boston University PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. Alzheimer's disease is the most significant cause of dementia in the elderly population. The rapid cognitive decline characteristic of this illness, coupled with the lack of a cure and a projected doubling of incidence within the next half century, has placed an impetus on research that focuses on developing early diagnostic tools. Earlier detection during the course of the disease may allow opportunities for the development of preventative and/or pharmaceutical measures that can possibly attenuate the progression or even prevent disease pathology for occurring. This paper outlines the current knowledge on the causes and diagnosis of AD in order to ascertain the most effective protocol for identifying pre-symptomatic individuals with the disease. One such method is to first select those at the highest risk of developing AD, and then performing periodic neuroimaging and cognitive assessments to ascertain the earliest manifestation. High-risk individuals include those with a family history of AD and/or other neurodegenerative disorders, in addition to those who already exhibit genetic markers for the disease, such as the Apolipoprotein Eε4 allele and the mutated protein Tau. Subjects who present with increased levels of cardiovascular risk factors for stroke, particularly hypertension and diabetes, are also at high risk for developing vascular dementia, which is another significant cause of AD. Disease incidence increases exponentially with advancing age. Consequently, individuals past the age of 65 who possess any combination of the above risk factors fall within the highest risk group. Advances in neuroimaging techniques and technology, like Magnetic Resonance Imaging and Positron Emission Tomography (PET), have allowed researchers to pinpoint the earliest pathological characteristics of AD, which includes cortical degeneration, amyloid plaques and neurofibrillary tangles. However, notwithstanding the recent discovery of the Pittsburg Compound B tracer used in PET, AD diagnosis via neuroimaging remains possible only when the pathological features are already present. Neuropsychological assessments, such as the Mini-Mental State Examination, are frequently used to assess the cognitive decline of patients with AD. Recent enhancements within the scoring of these tests, which has allowed for the incorporation of qualitative data, has given fruitful results and hopeful directions for diagnosing AD before pathogenesis occurs. However, due to the failure of clinical trials in discovering a cure, continued research into the realms of diagnosis and prevention of AD is of paramount importance in order to combat the impending epidemic.

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Douglass, Carolinda. "Diagnostic assessment and treatment service utilization among Alzheimer's disease clients in California." Santa Monica, CA : Rand, 1994. http://books.google.com/books?id=wPfaAAAAMAAJ.

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32

Casson, Roland James. "Making sense of a diagnosis of Alzheimer's disease : partners' experiences." Thesis, University of Hertfordshire, 2004. http://hdl.handle.net/2299/14242.

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Objectives This study aimed to explore the personal experiences and meanings that people develop in response to their partner being diagnosed with Alzheimer's disease, and how these inform the ways in which they cope with and manage their situation in the early stages. Method In-depth interviews were conducted with four women whose partners had received a diagnosis of early-stage Alzheimer's disease from specialist services within the past six months. Interpretative Phenomenological Analysis was used to identify themes running within their accounts. Results Three key themes emerged from the analysis: `Receiving confirmation of a diagnosis of Alzheimer's disease', `Making sense of the diagnosis' and "Staying on an even keel'. `Receiving confirmation of a diagnosis ofAlzheinzer's disease' came at the end of a chain of events for participants. By the time they had been through the process of searching for an explanation for their husband's cognitive difficulties and consulted with professionals, most had half-expecteda diagnosis, although it provoked some strong emotional responsesT. hey described a range of strategies to 'make sense of the diagnosis', including making social comparisons, interpreting professional and social discourses about Alzheimer's disease, making comparisons with previous phases of their life, and attempting to understand and empathise with their partner's experience. The core theme that emerged from participants' accounts was an emphasis on 'staying on an even keel' and protecting their partners' sense of competence and selfhood. They engaged in a range of idiosyncratic intra-personal and interpersonal adjustments to achieve this goal, including re-evaluating their life story and redefining themselves or their partners as `old', re-defining social boundaries to avoid social stigma, and subtly taking on an increasingly powerful position within the relationship in a way that their partners would not be aware of. Conclusions The results are discussed in relation to current clinical debates about the ethics and practicalities of diagnostic disclosure as well as how services can better engage with and respond to the psychosocial needs of family caregivers in the early stages of dementia.

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Fedotova, M. S. "Current issues in the diagnosis and treatment of Alzheimer's disease." Thesis, БДМУ, 2021. http://dspace.bsmu.edu.ua:8080/xmlui/handle/123456789/18901.

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34

Smith, André P. "Medicalizing intersubjectivity : diagnostic practices and the self in Alzheimer's disease." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=36792.

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Alzheimer's disease (AD) is a condition marked by progressive intellectual decline and memory loss, which typically affects individuals over the age of 60. Its origins are unknown but genetic factors are suspected in some cases. There is limited information about the subjective experience of AD although it is often described as a calamity that inevitably destroys the self irrespective of its victims' social circumstances. This dissertation offers an alternative to this nihilistic portrayal that draws on a critical phenomenological framework. It explores the loss of self as an intersubjective phenomenon that is mediated by three contexts: (1) Western representations of the self as autonomous and individualistic; (2) the public description of AD; and (3) the biomedical practices that construct AD as a diagnostic object. The dissertation examines the experiences of 16 patients and 37 family members who participated in a multi-disciplinary assessment at a dementia clinic. The participants also include 14 clinicians and staff members from the clinic. The findings are derived from a prospective study that includes in-depth, at-home interviews and observations of clinical assessment activities and research-based genetic counseling. The dissertation examines how memory trouble interferes with the intersubjective fabric of everyday life in families as affected participants lose the ability to meaningfully reciprocate on the basis of their individualistic identities. The analysis emphasizes the role of the clinical assessment, diagnosis, and public description in restoring intersubjective order. A salient aspect of this process is the way in which medicalized interpretations of memory trouble facilitate reinterpretation of the eroding self as being animated by pathology. The self is thus rendered meaningful again as it is being indexed to lay descriptions of what people do and say in AD. The analysis also considers how this process extends to participants who came to perceive themselves as victims of AD although they were assessed as not having a dementia disorder. The dissertation finally considers the impact of acquiring genetic knowledge about AD on interpretations of the self. Overall, the research underscores the loss of self in AD as a phenomenological process that is mediated by familial and institutional contexts.

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Goranson, Tamara Elaine. "On diagnosing Alzheimer's disease, assessing abstract thinking and reasoning." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/NQ62516.pdf.

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Voyle, Nicola Joanne. "Creating an early diagnostic test for Alzheimer's Disease." Thesis, King's College London (University of London), 2016. https://kclpure.kcl.ac.uk/portal/en/theses/creating-an-early-diagnostic-test-for-alzheimers-disease(fc5e88d2-7552-44cd-95a4-7eca4c93202f).html.

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The aim of the research in this thesis was to discover and validate blood biomarkers of early Alzheimer's Disease (AD). Existing and novel datasets from cohort studies were used for discovery and to attempt validation of previously reported biomarkers. For example, this thesis presents the first study to investigate associations between brain amyloid and blood metabolites. Further, this thesis presents the first study to combine more than one modality of blood biomarker in AD research and the first study to use a Bayesian methodology in this field. This thesis begins by aiming to validate candidate protein markers of brain amyloid burden in a novel proteomics dataset. Secondly, pathway-based methods are used to investigate the use of gene expression measurements as a potential biomarker of AD diagnosis. In the fourth chapter I generated a novel metabolomics dataset to investigate associations between blood metabolites and brain amyloid burden. A panel is found that predicts dichotomized amyloid burden with reasonable accuracy. The accuracy is improved by the inclusion of a candidate protein in the model. The fifth chapter of this thesis is focused on the use of a Bayesian methodology to predict measurements of amyloid using a variety of omics data. The Bayesian methodology allows incorporation of historical information by placing informative priors on demographic variables. No improvement is seen over demographics alone. The final chapter of this thesis aims to predict amyloid and tau burden using a polygenic risk score and levels of tau in blood. I have also considered a combined amyloid and tau pathology endpoint. The blood markers considered here do not improve predictive ability over demographics alone. Much of the work in this thesis highlights the importance of demographic factors in the diagnosis of early AD. The metabolite discovery work shows an improvement in predictive ability over demographics alone and warrants further investigation and replication. The other chapters of this thesis highlight that (in the settings investigated so far) blood measurements add minimal information above demographics alone.

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Garrison, Lisa Rae. "The syntactic comprehension deficit observed in Alzheimer's patients using an object manipulation task." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/27927.

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In the present study, the syntactic deficit of Alzheimer's patients was investigated, using an object manipulation task. Four case studies were presented, using data from test batteries devised by Caplan (pers. comm.) and the author. Subjects responded by acting out stimulus sentences presented in aural and written modes, using a set of small figurines. Responses were evaluated following criteria described by Caplan (1986, pers. comm.). Data from the four subjects were compared with each other, and with data obtained from a similar battery administered to aphasic patients. An impairment in the ability to interpret certain syntactic structures was found for all subjects, indicating that Alzheimer's patients do suffer from a syntactic comprehension deficit in the early stages of the disease. Several syntactic structures which caused errors in the responses of the Alzheimer's subjects, also caused errors for the aphasic patients, suggesting that the parsing model underlying the design of the stimuli, described by Caplan (in press) is a valid description of normal language function. Results of the present investigation are examined in relation to a model of syntactic comprehension suggested by Caplan (in press). Contradictions to hypotheses proposed are noted. The limitations and diagnostic use of the object manipulation test, are discussed. Medicine, Faculty of Audiology and Speech Sciences, School of Graduate

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Kixmiller, Jeffrey S. "Subtyping patients with Senile Dementia of the Alzheimer type using cluster analysis." Virtual Press, 1992. http://liblink.bsu.edu/uhtbin/catkey/833474.

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The purpose of this study was to determine if distinct subgroups of patients with Senile Dementia of the Alzheimer Type (SDAT) could be identified using seven scales of the Cognitive Behavior Rating Scale (CBRS). Ward's method of cluster analysis was used to group 104 patients with a probable diagnosis of SDAT into subtypes.The following three clusters were identified: (a) Moderately Impaired, (b) Severely Impaired, and (c) Emotionally Intact which displayed differences in symptom severity. Clusters could be partially defined by the amount of time they had been diagnosed with the disease. Differences in the cluster's configuration of scores had little/no descriptive utility. Subsequent discrimination analyses indicated that patient demographics were not as useful as the CBRS in classification of patients.This study provided evidence for the CBRS's ability to differentially portray SDAT patients' profiles. Results provide partial support for a stage model of SDAT. Implications of existing subgroups in SDAT are discussed as they pertain to patient management issues. Department of Counseling Psychology and Guidance Services

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Rudge, John. "Early onset frontotermporal dementia and alzheimers disease: diagnosis, treatment and care." Thesis, Rudge, John (2007) Early onset frontotermporal dementia and alzheimers disease: diagnosis, treatment and care. Professional Doctorate thesis, Murdoch University, 2007. https://researchrepository.murdoch.edu.au/id/eprint/468/.

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This research investigated two groups of patients diagnosed with dementia before the age of sixty-five. The patients were diagnosed with Alzheimer's Disease (AD, n = 25) and Frontotemporal Dementia (FTD, n = 37). Patients were assessed for approximately 3 years. The study found that FTD is a valid and useful diagnostic category, and can be reliably differentiated from AD. A combination of behavioural, neurological, and neuropsychological assessments were found to be complementary in the early and accurate diagnosis of early-onset dementia, and the differential diagnosis of FTD from AD. FTD patients were found to have relatively preserved visuo-spatial abilities compared to the AD patients. Problems associated with administering neuropsychological tests to early-onset dementia patients were highlighted. FTD patients were found to deteriorate more rapidly than AD patients, and to have significantly increased behavioural disturbances throughout the course of the illness in comparison with the AD patients. Practical guidelines to assist with care and management of early-onset dementia patients were presented. A strengths-based model of care was outlined. Individualised assessments and care plans were recommended for the development and provision of humane services to early-onset dementia patients. Issues surrounding providing palliative care were discussed.

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Rudge, John. "Early onset frontotermporal dementia and alzheimers disease : diagnosis, treatment and care." Murdoch University, 2007. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20090424.143035.

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This research investigated two groups of patients diagnosed with dementia before the age of sixty-five. The patients were diagnosed with Alzheimers Disease (AD, n = 25) and Frontotemporal Dementia (FTD, n = 37). Patients were assessed for approximately 3 years. The study found that FTD is a valid and useful diagnostic category, and can be reliably differentiated from AD. A combination of behavioural, neurological, and neuropsychological assessments were found to be complementary in the early and accurate diagnosis of early-onset dementia, and the differential diagnosis of FTD from AD. FTD patients were found to have relatively preserved visuo-spatial abilities compared to the AD patients. Problems associated with administering neuropsychological tests to early-onset dementia patients were highlighted. FTD patients were found to deteriorate more rapidly than AD patients, and to have significantly increased behavioural disturbances throughout the course of the illness in comparison with the AD patients. Practical guidelines to assist with care and management of early-onset dementia patients were presented. A strengths-based model of care was outlined. Individualised assessments and care plans were recommended for the development and provision of humane services to early-onset dementia patients. Issues surrounding providing palliative care were discussed.

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Jobst, Kim Anthony. "Neuroimaging in Alzheimer's disease : a longitudinal prospective clinicopathological study." Thesis, University of Oxford, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318899.

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Cardona, Francisco Miguel Ribeiro. "Synthesis of new Aβ-ligands useful in diagnosis of Alzheimer's disease". Doctoral thesis, Universidade de Aveiro, 2013. http://hdl.handle.net/10773/12243.

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Doutoramento em Química Alzheimer’s disease is a chronic progressive neurodegenerative disease and is the most common form of dementia (estimated 50−60% of all cases), associated with loss of memory (in particular episodic memory), cognitive decline, and behavioural and physical disability, ultimately leading to death. Alzheimer’s disease is a complex disease, mostly occurring sporadically with no apparent inheritance and being the age the main risk factor. The production and accumulation of amyloid-beta peptide in the central nervous system is a key event in the development of Alzheimer’s disease. This project is devoted to the synthesis of amyloid-beta ligands, fluorophores and blood brain barrier-transporters for diagnosis and therapy of Alzheimer’s disease. Different amyloid-beta ligands will be synthesized and their ability to interact with amyloid-beta plaques will be studied with nuclear magnetic resonance techniques and a process of lead optimization will be performed. Many natural and synthetic compounds able to interact as amyloid-beta ligands have been identified. Among them, a set of small molecules in which aromatic moieties seem to play a key role to inhibit amyloid-beta aggregation, in particular heteroaromatic polycyclic compounds such as tetracyclines. Nevertheless tetracyclines suffer from chemical instability, low water solubility and possess, in this contest, undesired anti-bacterial activity. In order to overcome these limitations, one of our goals is to synthesize tetracyclines analogues bearing a polycyclic structure with improved chemical stability and water solubility, possibly lacking antibacterial activity but conserving the ability to interact with amyloid-beta peptides. Known tetracyclines have in common a fourth cycle without an aromatic character and with different functionalisations. We aim to synthesize derivatives in which this cycle is represented by a sugar moiety, thus bearing different derivatisable positions or create derivatives in which we will increase or decrease the number of fused rings. In order to generate a potential drug-tool candidate, these molecules should also possess the correct chemical-physical characteristics. The glycidic moiety, not being directly involved in the binding, it assures further possible derivatizations, such as conjugation to others molecular entities (nanoparticles, polymeric supports, etc.), and functionalization with chemical groups able to modulate the hydro/lipophilicity. In order to be useful such compounds should perform their action within the brain, therefore they have to be able to cross the blood brain barrier, and to be somehow detected for diagnostic purposes. A doença de Alzheimer é uma doença crónica neurodegenerativa e uma das formas mais comuns de demência. Está associada à perda de memória, declínio cognitivo, incapacidade física e comportamental, e, em última análise, pode levar à morte. A doença de Alzheimer é uma doença complexa, ocorrendo na maioria dos casos esporadicamente, sendo a idade o principal fator de risco. A produção e acumulação do péptido beta-amilóide no sistema nervoso central é um facto importante no desenvolvimento da doença de Alzheimer. O principal objetivo deste projeto consiste na síntese de ligandos beta-amilóide, de compostos fluoróforos e transportadores de fármacos através da barreira hematoencefálica para o diagnóstico e tratamento da doença de Alzheimer. Serão sintetizados diversos ligandos do péptido beta-amilóide e estudada a capacidade destes compostos interatuarem com as placas beta-amilóides através de espectroscopia de ressonância magnética nuclear. Será também realizado um estudo de otimização do composto líder. Já foram identificados muitos compostos naturais e sintéticos capazes de interagir com o péptido beta-amilóide, entre eles um conjunto de pequenas moléculas nas quais se constata que a parte aromática possui um papel importante na inibição da sua agregação, nomeadamente compostos hetero-aromáticos policíclicos, tais como as tetraciclinas. Porém as tetraciclinas apresentam instabilidade química, baixa solubilidade em água e possuem atividade antibacteriana, a qual é neste contexto indesejada. De modo a ultrapassar estas limitações, um dos objectivos deste trabalho é sintetizar compostos análogos de tetraciclinas, possuindo uma estrutura policíclica com uma melhor estabilidade química e solubilidade em água e possivelmente não possuindo atividade antibacteriana, mas conservando a capacidade de interação com o péptido beta-amilóide. As tetraciclinas possuem em comum um quarto ciclo sem carácter aromático e possuindo diferentes grupos funcionais. Com este projeto pretende-se sintetizar derivados nos quais este quarto ciclo é constiuído por uma entidade glucídica, portanto, possuindo diferentes posições funcionalizáveis ou criar derivados nos quais se irá acrescentar ou diminuir o número de anéis fundidos. De modo a criar um potencial fármaco, estas moléculas deverão também possuir as corretas propriedades físico-químicas. A entidade glucídica, não estando diretamente envolvida na interação com o péptido beta-amilóide, assegura possíveis derivatizações, tais como a conjugação a outras entidades moleculares (nanopartículas, suportes poliméricos, etc.) e a funcionalização com outros grupos funcionais capazes de modularem as propriedades lipofílicas e hidrofílicas. Estes compostos só serão úteis se atravessarem a barreira hematoencefálica e serem de algum modo detetados para fins de diagnóstico.

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Dooley, Jemima Mary Beatrice. "Communicating a diagnosis of dementia." Thesis, University of Exeter, 2016. http://hdl.handle.net/10871/27939.

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Background: There has been a rise in dementia awareness, with policy changes leading to increased diagnosis rates. However, the stigma of dementia is likely to cause challenges in diagnostic communication. This is complicated by the effect of dementia on cognitive functioning. The aims of this study were to (1) identify how diagnoses of dementia are communicated, (2) identify how people with dementia respond to the diagnosis, and (3) explore doctors’ perspectives on dementia diagnosis delivery. Methodology: A systematic literature review was conducted. Twenty doctors from 9 memory clinics across 4 NHS trusts participated. Eighty-one dementia diagnosis feedback meetings were video-recorded. Conversation analysis was used to identify patterns in diagnosis delivery. Four focus groups with the participating doctors were analysed using thematic analysis (inter-rater reliability 0.89). Findings: The literature review highlighted the dilemma of communicating both sensitively and honestly with people with dementia, as well as challenges stemming from cognitive impairment. This was also evident in diagnostic communication. Prior to diagnosis doctors elicited patient orientation to the meeting purpose (“do you know why you’re here?) and perspective into symptoms (“how is your memory?”). The majority of patients displayed some confusion as to the meeting purpose and offered non-medicalised explanations for their symptoms. Doctors attempted to address this through repeated explication of test results and statements of the clinic purpose. Dementia was always explicitly named. Diagnoses were often delivered indirectly (“that is dementia”), a practice to manage patient resistance and negative responses. However, over 40% were delivered directly (“you have dementia”), especially when patients were more cognitively impaired. Doctors pursued non-minimal responses to diagnosis, apparently to obtain perspective before progressing to treatment. However, resistance was not always addressed and prognosis was often avoided. Doctors highlighted pressure to make diagnoses and an aim to emphasise “living well” rather than discussing prognosis. Conclusion: The findings of this study highlighted the delicate balance between minimising likely resistance and distress and maximising understanding in the context of cognitive impairment. Instilling hope is evidently a priority for doctors. The diagnosis meeting is just one part of the journey of the person with dementia, and sufficient pre- and post-diagnosis support is integral.

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Ben, Ahmed Olfa. "Features-based MRI brain classification with domain knowledge : application to Alzheimer's disease diagnosis." Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0002/document.

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Les outils méthodologiques en indexation et classification des images par le contenu sont déjà assez matures et ce domaine s’ouvre vers les applications médicales. Dans cette thèse,nous nous intéressons à l'indexation visuelle, à la recherche et à la classification des images cérébrales IRM par le contenu pour l'aide au diagnostic de la maladie d'Alzheimer (MA). L'idée principale est de donner au clinicien des informations sur les images ayant des caractéristiques visuelles similaires. Trois catégories de sujets sont à distinguer: sujets sains (NC), sujets à troubles cognitifs légers (MCI) et sujets atteints par la maladie d'Alzheimer(AD). Nous représentons l’atrophie cérébrale comme une variation de signal dans des images IRM (IRM structurelle et IRM de Tenseur de Diffusion). Cette tâche n'est pas triviale,alors nous nous sommes concentrés uniquement sur l’extraction des caractéristiques à partir des régions impliquées dans la maladie d'Alzheimer et qui causent des changements particuliers dans la structure de cerveau : l'hippocampe le Cortex Cingulaire Postérieur. Les primitifs extrais sont quantifiés en utilisant l'approche sac de mots visuels. Cela permet de représenter l’atrophie cérébrale sous forme d’une signature visuelle spécifique à la MA.Plusieurs stratégies de fusion d’information sont appliquées pour renforcer les performances de système d’aide au diagnostic. La méthode proposée est automatique (sans l’intervention de clinicien), ne nécessite pas une étape de segmentation grâce à l'utilisation d'un Atlas normalisé. Les résultats obtenus apportent une amélioration par rapport aux méthodes de l’état de l’art en termes de précision de classification et de temps de traitement Content-Based Visual Information Retrieval and Classification on Magnetic Resonance Imaging (MRI) is penetrating the universe of IT tools supporting clinical decision making. A clinician can take profit from retrieving subject’s scans with similar patterns. In this thesis, we use the visual indexing framework and pattern recognition analysis based on structural MRIand Tensor Diffusion Imaging (DTI) data to discriminate three categories of subjects: Normal Controls (NC), Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD). The approach extracts visual features from the most involved areas in the disease: Hippocampusand Posterior Cingulate Cortex. Hence, we represent signal variations (atrophy) inside the Region of Interest anatomy by a set of local features and we build a disease-related signature using an atlas based parcellation of the brain scan. The extracted features are quantized using the Bag-of-Visual-Words approach to build one signature by brain/ROI(subject). This yields a transformation of a full MRI brain into a compact disease-related signature. Several schemes of information fusion are applied to enhance the diagnosis performance. The proposed approach is less time-consuming compared to the state of thearts methods, computer-based and does not require the intervention of an expert during the classification/retrieval phase

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Jones, Phyllis L. (Phyllis Lee). "Caregivers' Appraisal of Alzheimer's Disease Symptoms and the Relationship to Decisions About Care." Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc278991/.

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The purpose of the present study was to compare 42 community-dwelling spouse and child Alzheimer's Disease caregivers with 38 community-dwelling potential caregivers on salience of illness symptoms, and accuracy of judging symptoms of illnesses.

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Jelic, Vesna. "Early diagnosis of Alzheimer's disease : focus on quantitative EEG in relation to genetic, biochemical and neuroimaging markers /." Stockholm, 1999. http://diss.kib.ki.se/1999/91-628-3431-2/.

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Daniels, Katherine Jean. "Couples' construction of meaning of an Alzheimer's disease diagnosis : a systemic approach." Diss., Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/1057.

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Jackson, Stanita. "Caregivers' Perceptions of an Early Diagnosis of Alzheimer's Disease in African Americans." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2290.

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Alzheimer's disease (AD) is significantly more prevalent among African Americans than within the general population, but rates of early detection are lower in the African American community. Researchers have demonstrated that both pessimistic Alzheimer's-directed health beliefs, and negative perceptions of the effectiveness and the accessibility of medical care act as barriers to care seeking by African American family members of individuals with the disease. Recent research into causal judgments made by potential caregivers about individuals with undiagnosed AD suggests that gender bias and errors in attribution may constitute covert barriers to both lay and professional interpretations regarding the need for cognitive assessment. This study used grounded theory to investigate whether African American family caregivers hold integrated, gender-distinct beliefs about causal attributions of their family member's cognitive decline which may contribute to a delay in care-seeking behaviors. The health belief model was used in conjunction with the attribution theory as the conceptual framework for understanding the data. Purposive sampling of geriatric and memory clinics, and a church was used to recruit eight family caregivers who participated in in-depth interviews. The results indicated that there is a significant lack of caregivers' knowledge and understanding of AD regardless of gender, and that this lack is linked to delays in diagnosis. These results may be used to support the development of a new theory of family caregivers' knowledge and understanding of AD. The social change implications include decreasing delayed diagnosis through increased educational awareness, community outreach programs, and universal mandatory cognitive testing of AD for at-risk individuals.

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Everitt, Alaina. "Differential Scoring Patterns on the Clock Drawing Test: a Comparison of Vascular Dementia and Alzheimer's Dementia." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5283/.

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This study examined differences in scoring patterns among those diagnosed with Alzheimer's dementia and vascular dementia on the clock-drawing test. Archival clock drawing data was retrieved on 279 patients presenting at a county hospital-based memory clinic. Analysis of drawings was based on frequency of qualitative errors, as well as an overall quantitative score. Mean comparisons found those patients with Alzheimer's dementia to perform worse on both quantitative and qualitative scoring measures. However, Pearson's chi-squared test revealed a significantly higher rate of spacing errors among subjects with vascular dementia. Such lends support to my hypothesis that impaired executive functioning in vascular dementia patients would lead to poor qualitative performance. Logistic regression found significant predictive ability for the qualitative criteria in diagnosis (χ2 = 25.49, p < .001), particularly the rate of omission (z = 8.96, p = .003) and addition errors (z = 7.58, p = .006). Such findings hold important implications for the use of qualitative criteria in cognitive screening assessments.

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Shah, Dipti Jigar. "Discovery of Novel Serum Biomarkers for Diagnosing and Staging Alzheimer's Disease." BYU ScholarsArchive, 2014. https://scholarsarchive.byu.edu/etd/5268.

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Discovery of Novel Serum Biomarkers for Diagnosing and Staging Alzheimer’s DiseaseDipti Jigar ShahDepartment of Chemistry and Biochemistry, BYUDoctor of PhilosophyAlzheimer’s disease (AD) is an untreatable neurologic disease affecting more than 5 million Americans, most over 60 years of age. Protein plaques and neurofibrillary tangles typify AD brain pathology and are thought to cause the progressive dementia and brain shrinkage observed in AD. Currently there are no methods to diagnose the disease at a time before damage becomes irreversible.Biochemical tests for AD using cerebrospinal fluid analysis or neuroimaging are not yet sufficiently sensitive and specific, and they are invasive. This points to a need for a more easily applied and more sensitive diagnostic test. Although the gross anatomical changes are localized to the brain, AD is likely to involve changes throughout the body. As a result of this, changes in the abundance of certain biomolecules present in the circulation system are likely to occur. Consequently, a serum proteomics approach able to measure such changes, when applied to AD, would likely find quantitative changes in relevant molecules that can help diagnose the disease correctly, ideally early in the disease process. The goal of this work was to discover and validate novel diagnostic serum biomarkers for AD. For biomarker discovery and validation, we used a novel serum proteomics approach involving reversed phase capillary-liquid chromatography-electrospray ionization-quadrupole-time of flight mass spectrometry. Our samples were protein depleted, which helped us survey low molecular weight species in the serum without ion suppression from larger proteins like albumin. We were able to observe more than 8000 molecular species in a single run. The overall project was comprised of four studies: (i) discovery of novel potential serum AD markers, (ii) blinded validation of diagnostically promising biomarkers found in the initial study, with their further chemical identification, (iii) exploring gender-based serum AD biomarkers, and (v) discovery of biomarkers that distinguish early versus moderate stage AD. In the first study, the approach found 38 significant (p < 0.05) biomarkers and 21 near significant (p = 0.05 to 0.099) biomarkers. On using the forward selection approach, we built multi-marker panels with specificities and sensitivities higher than 80%.The second study reports on a blinded validation study that was performed on a new set of serum samples. We focused on the 13 most promising AD biomarkers found as part of the initial study. We successfully validated 4 of these biomarkers that showed highly significant statistical p-values. As part of this study, research was conducted to identify these 4 biomarkers, which was accomplished using tandem mass spectrometry with fragmentation experiments. The third study used data from the initial study but looked at gender specific biomarkers. We found 31 significant and near significant serum AD biomarkers for women, 16 for men, and 25 that were gender independent. Multi-marker panels of AD biomarkers for women or men had sensitivities of >60% and specificities >85%.In the fourth study, cases with moderate AD were compared to cases with very mild or mild AD to find novel biomarkers that could be used for staging. We found 44 significant and near significant biomarkers that were quantitatively different between mild and severe AD. In conclusion, we were successful in accomplishing the goal of this work of finding, validating and identifying novel serum biomarkers that diagnose AD.

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Dissertations / Theses on the topic 'Alzheimer’s disease – Diagnosis'

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