Diagnostic confirmation, severity, and subtypes of Alzheimer's disease

Förstl, Hans; Fischer, Peter

doi:10.1007/bf02190378

Cited by 11 publications

(12 citation statements)

References 81 publications

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“…These variations may be distinct enough to comprise specific subtypes of the disease and may identify patients who respond favourably to different treatment strategies. However, such variations are less convincing if there is no correlation between clinical and pathological features or if the ‘subtypes’ simply represent the extreme variants of a continuously varying phenotype 47 . Hence, it may be necessary to determine whether actual subtypes exist and to identify pathological criteria which may help to distinguish between them.…”

Section: Principal Components Analysismentioning

confidence: 99%

Quantifying the pathology of neurodegenerative disorders: quantitative measurements, sampling strategies and data analysis

Armstrong

2003

Histopathology

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The use of quantitative methods has become increasingly important in the study of neurodegenerative disease. Disorders such as Alzheimer's disease (AD) are characterized by the formation of discrete, microscopic, pathological lesions which play an important role in pathological diagnosis. This article reviews the advantages and limitations of the different methods of quantifying the abundance of pathological lesions in histological sections, including estimates of density, frequency, coverage, and the use of semiquantitative scores. The major sampling methods by which these quantitative measures can be obtained from histological sections, including plot or quadrat sampling, transect sampling, and point-quarter sampling, are also described. In addition, the data analysis methods commonly used to analyse quantitative data in neuropathology, including analyses of variance (anova) and principal components analysis (PCA), are discussed. These methods are illustrated with reference to particular problems in the pathological diagnosis of AD and dementia with Lewy bodies (DLB).

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Section: Principal Components Analysismentioning

confidence: 99%

Quantifying the pathology of neurodegenerative disorders: quantitative measurements, sampling strategies and data analysis

Armstrong

2003

Histopathology

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“…Variations in the abundance and distribution of senile plaques (SP) and neurofibrillary tangles (NFT) can be commonly observed in the brains of individuals with Alzheimer's disease (AD). [1][2][3][4] Three hypotheses have been proposed to account for this neuropathological heterogeneity. 5 First, distinct subtypes of AD may be present characterized by different combinations of cognitive deficits and pathological features ('subtype hypothesis').…”

Section: Introductionmentioning

confidence: 99%

Neuropathological heterogeneity in Alzheimer’s disease: A study of 80 cases using principal components analysis

Armstrong

Nochlin²,

Bird

2000

Neuropathology

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Three hypotheses have been proposed to explain neuropathological heterogeneity in Alzheimer's disease (AD): the presence of distinct subtypes ('subtype hypothesis'), variation in the stage of the disease ('phase hypothesis') and variation in the origin and progression of the disease ('compensation hypothesis'). To test these hypotheses, variation in the distribution and severity of senile plaques (SP) and neurofibrillary tangles (NFT) was studied in 80 cases of AD using principal components analysis (PCA). Principal components analysis using the cases as variables (Q-type analysis) suggested that individual differences between patients were continuously distributed rather than the cases being clustered into distinct subtypes. In addition, PCA using the abundances of SP and NFT as variables (R-type analysis) suggested that variations in the presence and abundance of lesions in the frontal and occipital lobes, the cingulate gyrus and the posterior parahippocampal gyrus were the most important sources of heterogeneity consistent with the presence of different stages of the disease. In addition, in a subgroup of patients, individual differences were related to apolipoprotein E (ApoE) genotype, the presence and severity of SP in the frontal and occipital cortex being significantly increased in patients expressing apolipoprotein (Apo)E allele epsilon4. It was concluded that some of the neuropathological heterogeneity in our AD cases may be consistent with the 'phase hypothesis'. A major factor determining this variation in late-onset cases was ApoE genotype with accelerated rates of spread of the pathology in patients expressing allele epsilon4.

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“…The multivariate analyses demonstrated significant variations within the AD cases studied [1, 4,10,11]. Both methods suggested that the distribution and overall abun dance of SP and NFT were important neuropathological variables associated with this variation.…”

Section: Discussionmentioning

confidence: 99%

“…Clinical and pathological studies of Alzheimer's dis ease (AD) have revealed significant variations between cases suggesting that the disease may comprise distinct subtypes [1][2][3][4]. Several possible sources of variation have been identified.…”

Section: Introductionmentioning

confidence: 99%

The Use of Multivariate Methods in the Identification of Subtypes of Alzheimer's Disease: A Comparison of Principal Components and Cluster Analysis

Armstrong¹,

Wood²,

Myers³

et al. 1996

Dement Geriatr Cogn Disord

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Two contrasting multivariate statistical methods, viz., principal components analysis (PCA) and cluster analysis were applied to the study of neuropathological variations between cases of Alzheimer''s disease (AD). To compare the two methods, 78 cases of AD were analysed, each characterised by measurements of 47 neuropathological variables. Both methods of analysis revealed significant variations between AD cases. These variations were related primarily to differences in the distribution and abundance of senile plaques (SP) and neurofibrillary tangles (NFT) in the brain. Cluster analysis classified the majority of AD cases into five groups which could represent subtypes of AD. However, PCA suggested that variation between cases was more continuous with no distinct subtypes. Hence, PCA may be a more appropriate method than cluster analysis in the study of neuropathological variations between AD cases.

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Diagnostic confirmation, severity, and subtypes of Alzheimer's disease

Cited by 11 publications

References 81 publications

Quantifying the pathology of neurodegenerative disorders: quantitative measurements, sampling strategies and data analysis

Quantifying the pathology of neurodegenerative disorders: quantitative measurements, sampling strategies and data analysis

Neuropathological heterogeneity in Alzheimer’s disease: A study of 80 cases using principal components analysis

The Use of Multivariate Methods in the Identification of Subtypes of Alzheimer's Disease: A Comparison of Principal Components and Cluster Analysis

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