Neuropathologically defined subtypes of Alzheimer’s disease differ significantly from neurofibrillary tangle-predominant dementia

Janocko, Nicholas J.; Brodersen, Kevin; Soto‐Ortolaza, Alexandra I.; Ross, Owen A.; Liesinger, Amanda M.; Duara, Ranjan; Graff‐Radford, Neill R.; Dickson, Dennis W.; Murray, Melissa E.

doi:10.1007/s00401-012-1044-y

Cited by 111 publications

(132 citation statements)

References 42 publications

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“…Although the disease progression has been traditionally assessed under the Braak and Braak staging scheme (Braak & Braak, 1991), several reports (Akatsu et al., 2002; Armstrong, Nochlin, & Bird, 2000; Janocko et al., 2012; Murray et al., 2014) have demonstrated a very variable AD clinical picture: Neither the progression patterns nor the same anatomical areas are involved or follow a reproducible anatomic sequence, even in series of patients belonging to comparable social and cultural environments. Approximately 25% of AD brains show atypical patterns of structural damage, usually classified as hippocampal sparing and limbic predominant AD (Murray et al., 2011).…”

Section: Introductionmentioning

confidence: 99%

Characterization of brain anatomical patterns by comparing region intensity distributions: Applications to the description of Alzheimer's disease

et al. 2018

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PurposeThis work presents an automatic characterization of the Alzheimer's disease describing the illness as a multidirectional departure from a baseline defining the control state, being these directions determined by a distance between functional‐equivalent anatomical regions.MethodsAfter a brain parcellation, a region is described by its histogram of gray levels, and the Earth mover's distance establishes how close or far these regions are. The medoid of the control group is set as the reference and any brain is characterized by its set of distances to this medoid.EvaluationThis hypothesis was assessed by separating groups of patients with mild Alzheimer's disease and mild cognitive impairment from control subjects, using a subset of the Open Access Series of Imaging Studies (OASIS) database. An additional experiment evaluated the method generalization and consisted in training with the OASIS data and testing with the Minimal Interval Resonance Imaging in Alzheimer's disease (MIRIAD) database.ResultsClassification between controls and patients with AD resulted in an equal error rate of 0.1 (90% of sensitivity and specificity at the same time). The automatic ranking of regions resulting is in strong agreement with those regions described as important in clinical practice. Classification with different databases results in a sensitivity of 85% and a specificity of 91%.ConclusionsThis method automatically finds out a multidimensional expression of the AD, which is directly related to the anatomical changes in specific areas such as the hippocampus, the amygdala, the planum temporale, and thalamus.

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Section: Introductionmentioning

confidence: 99%

Characterization of brain anatomical patterns by comparing region intensity distributions: Applications to the description of Alzheimer's disease

et al. 2018

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“…Alzheimer-and Lewyrelated pathologies were immunostained and then analyzed using 3 custom-designed color deconvolution ImageScope algorithms. 13 Antibody information and detailed methods on quantification are available in appendix e-1. All neuropathologic analyses were performed blinded to group status.…”

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MRI and pathology of REM sleep behavior disorder in dementia with Lewy bodies

et al. 2013

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“…Despite reasonable interrater agreement when using standardized criteria [84,[103][104][105], no one set of histopathologic criteria for AD has been uniformely accepted by neuropathologists. These algorithms that only considered the classical "plaque and tangle" phenotype of AD did not recognize other subtypes [74,106,107]. Analysis of 1,677 cases with antemortem diagnosis of dementia from the NACCR showed that 82.4% fell into diagnostic "boxes" that are within the consensus recommendations, while the others were "atypical" cases [108].…”

Section: Problems In the Neuropathologic Diagnosis Of Alzheimer's Dismentioning

confidence: 99%

“…While MAPT H1H1 genotype was high (~70 %) in NFTD and LP-AD, and similar to typical AD (59%), tau and Aβ burden in frontal cortex were very low in NFTD, differentiating it from AD subtypes, including LP-AD. Significant pathological differences between NFTD and LP-AD suggest that it may not merely be a variant of AD [106]. Volumetric MRI analysis could reliably track the distribution of NFT pathology and predict pathological subtypes of AD [118].…”

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Neuropathology of Dementia Disorders

Jellinger¹

2014

J Alzheimers Dis Parkinsonism

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IntroductionDementia, encompassing deficits in several cognitive domains that are severe enough to interfere with daily functioning [1], in the new DSM V classification is classified within the broad category of major neurocognitive disorders, proposing specific criteria for the various etiologies [2]. Previously defined as the manifestation of deteriorating brain functions over time due to cell deaths in the brain caused by neurodegeneration or any other disease [3], according to recent research dementia is not primarily caused by neuronal cell death/loss, but by dysfunction and loss of synapses [4] in AD [5] and in α-synucleinopathies [6]. Other causes include cholinergic neuronal and axonal abnormalities [7,8], as well as pre-and postsynaptic cortical cholinergic deficits also occurring in early AD [9]. These changes due to disconnection of major nervous circuitries causing default networks [10][11][12][13] have been demonstrated in vivo in early AD [14], suggesting that disease progress is transmitted by neuronal pathways [15]. A prionlike spread of misfolded protein aggregates in the pathogenesis and progression of neurodegeneration is a hot spot of discussion [16][17][18][19][20][21].Both the prevalence and incidence of dementia increase exponentially with age. In 2010, 35.6 million people worldwide lived with dementia, with around 8 million new cases every year. Numbers are expected to double or triple every 5-10 years, to 135 millions in 2050, 16 millions in Europe. In 2010, 58% of all demented people lived in low-cost countries, with their proportion anticipated to rise to 71% in 2050 [22]. According to recent data from China the incidence of dementia was 9.87/1000 person years and the median standardised mortality ratio was 1.94:1 [23]. With the disproportional growth of the elderly population, dementia has become a major public health and socio-economic problem that threatens to become the scourge of our century. The total costs for dementia were US$ 604 billion in 2010 worldwide, up to 70% for social care alone [24], total payments for AD for 2013 were expected to be $ 203 billion in USA alone, not included contributions of unpaid caregivers [25]. Neuropathology of Dementia DisordersKurt A Jellinger* Institute of Clinical Neurobiology, Kenyongasse 18, A 1070, Vienna, Austria AbstractDementia, being not a specific disease but a syndrome characterized by deficits in several cognitive domains, is a major public health and socio-economic problem of our century. It is caused by dysfunction/loss of synapses and neurons inducing default neuronal networks. Despite updated concensus criteria for the clinical diagnosis of the major neurodegenerative disorders and new biomarkers, the diagnostic accuracy ranges from 65 to 96% (for Alzheimer's disease /AD), with a sensitivity versus other dementias of around 85.4% and a specificity of up to 77.7%. Pathologic assessment, using genetic and molecular biological methods, based on homogenous definitions, harmonized interlaboratory and assessment standards, can achiev...

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Neuropathologically defined subtypes of Alzheimer’s disease differ significantly from neurofibrillary tangle-predominant dementia

Cited by 111 publications

References 42 publications

Characterization of brain anatomical patterns by comparing region intensity distributions: Applications to the description of Alzheimer's disease

Characterization of brain anatomical patterns by comparing region intensity distributions: Applications to the description of Alzheimer's disease

MRI and pathology of REM sleep behavior disorder in dementia with Lewy bodies

Neuropathology of Dementia Disorders

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