Relationship between atrophy and β‐amyloid deposition in Alzheimer disease

Chételat, Gaël; Villemagne, Victor L.; Bourgeat, Pierrick; Pike, Kerryn E.; Jones, Gareth; Ames, David; Ellis, Kathryn A.; Szoeke, Cassandra; Martins, Ralph N.; O’Keefe, Graeme; Salvado, Olivier; Masters, Colin L.; Rowe, Christopher C.

doi:10.1002/ana.21955

Cited by 338 publications

(226 citation statements)

References 34 publications

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“…Correlations in earlier (elderly controls or subjective memory complainers) but not later disease stages were found between global amyloid burden measured by carbon-11 Pittsburgh compound B (PiB) PET and global gray matter volume [43] and between medial temporal lobe amyloid load and HV [17]. Significant correlations (r values in the 0.2 range) were found in a pooled sample of HC, MCI, and AD dementia ADNI cases between HV with precuneus and parietal cortices and mean cortical PiB SUVR [44].…”

Section: Discussionmentioning

confidence: 99%

Relationship of Hippocampal Volume to Amyloid Burden across Diagnostic Stages of Alzheimer's Disease

Trzepacz

Hochstetler²,

Yu³

et al. 2015

Dement Geriatr Cogn Disord

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Aims: To assess how hippocampal volume (HV) from volumetric magnetic resonance imaging (vMRI) is related to the amyloid status at different stages of Alzheimer's disease (AD) and its relevance to patient care. Methods: We evaluated the ability of HV to predict the florbetapir positron emission tomography (PET) amyloid positive/negative status by group in healthy controls (HC, n = 170) and early/late mild cognitive impairment (EMCI, n = 252; LMCI, n = 136), and AD dementia (n = 75) subjects from the Alzheimer's Disease Neuroimaging Initiative Grand Opportunity (ADNI-GO) and ADNI2. Logistic regression analyses, including elastic net classification modeling with 10-fold cross-validation, were used with age and education as covariates. Results: HV predicted amyloid status only in LMCI using either logistic regression [area under the curve (AUC) = 0.71, p < 0.001] or elastic net classification modeling [positive predictive value (PPV) = 72.7%]. In EMCI, age (AUC = 0.70, p < 0.0001) and age and/or education (PPV = 63.1%), but not HV, predicted amyloid status. Conclusion: Using clinical neuroimaging, HV predicted amyloid status only in LMCI, suggesting that HV is not a biomarker surrogate for amyloid PET in clinical applications across the full diagnostic spectrum.

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Section: Discussionmentioning

confidence: 99%

Relationship of Hippocampal Volume to Amyloid Burden across Diagnostic Stages of Alzheimer's Disease

Trzepacz

Hochstetler²,

Yu³

et al. 2015

Dement Geriatr Cogn Disord

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“…Reduction of HP volumes appears to be a relatively non-specific event that occurs in response to various degenerative and non- degenerative insults to the brain. Mild degrees of HP atrophy have been associated with neocortical amyloid deposition [37]. Conditions, such as Lewy body disease, depression, stress-related disorders, steroid treatment, seizures, multiple sclerosis, stroke and brain trauma have all been associated with mild HP atrophy [38].…”

Section: Discussionmentioning

confidence: 99%

Minimal Atrophy of the Entorhinal Cortex and Hippocampus: Progression of Cognitive Impairment

Varón

Loewenstein

Potter

et al. 2011

Dement Geriatr Cogn Disord

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Background: In Alzheimer’s disease, neurodegenerative atrophy progresses from the entorhinal cortex (ERC) to the hippocampus (HP), limbic system and neocortex. The significance of very mild atrophy of the ERC and HP on MRI scans among elderly subjects is unknown. Methods: A validated visual rating system on coronal MRI scans was used to identify no atrophy of the HP or ERC (HP₀; ERC₀), or minimal atrophy of the HP or ERC (HP_ma; ERC_ma), among 414 participants. Subjects fell into the following groups: (1) ERC₀/HP₀, (2) ERC_ma/HP₀, (3) ERC₀/HP_ma, and (4) ERC_ma/HP_ma. HP volume was independently measured using volumetric methods. Results: In comparison to ERC₀/HP₀ subjects, those with ERC₀/HP_ma had impairment on 1 memory test, ERC_ma/HP₀ subjects had impairment on 2 memory tests and the Mini Mental State Examination (MMSE), while ERC_ma/HP_ma subjects had impairment on 3 memory tests, the MMSE and Clinical Dementia Rating. Progression rates of cognitive and functional impairment were significantly greater among subjects with ERC_ma. Conclusion: Minimal atrophy of the ERC results in greater impairment than minimal atrophy of the HP, and the combination is additive when measured by cognitive and functional tests. Rates of progression to greater impairment were higher among ERC_ma subjects.

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“…Indeed, recent studies suggested that hypometabolism of glucose in the brain of AD patients is closely linked to cognitive decline [48] and can be indicative of larger subsequent cerebral atrophy [49]. Although cerebral atrophy is not generally related to the regional binding of the Pittsburgh compound B (measuring levels of Aβ aggregation), a relationship between Aβ deposition and atrophy was observed in early AD [49,50]. Interestingly, it was also recently suggested that brain areas of high resting glucose metabolism (reflecting high neuronal activity) in healthy elderly individuals generally correspond to those where the level of regional Pittsburgh compound B uptake is greater in AD patients [51].…”

Section: Brain Metabolism In Admentioning

confidence: 99%

Metabolic Alterations Associated to Brain Dysfunction in Diabetes

Duarte¹

2014

aging dis

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From epidemiological studies it is known that diabetes patients display increased risk of developing dementia. Moreover, cognitive impairment and Alzheimer's disease (AD) are also accompanied by impaired glucose homeostasis and insulin signalling. Although there is plenty of evidence for a connection between insulin-resistant diabetes and AD, definitive linking mechanisms remain elusive. Cerebrovascular complications of diabetes, alterations in glucose homeostasis and insulin signalling, as well as recurrent hypoglycaemia are the factors that most likely affect brain function and structure. While difficult to study in patients, the mechanisms by which diabetes leads to brain dysfunction have been investigated in experimental models that display phenotypes of the disease. The present article reviews the impact of diabetes and AD on brain structure and function, and discusses recent findings from translational studies in animal models that link insulin resistance to metabolic alterations that underlie brain dysfunction. Such modifications of brain metabolism are likely to occur at early stages of neurodegeneration and impact regional neurochemical profiles and constitute non-invasive biomarkers detectable by magnetic resonance spectroscopy (MRS).Key words: Neurodegeneration, Diabetes, Alzheimer's disease, Insulin, Metabolism Diabetes mellitus can be defined as a chronic metabolic disorder characterized by hyperglycaemia, resulting from inappropriate insulin secretion and/or action [1]. The vast majority of the diabetes cases are included in two main categories, classified according to the underlying cause, which are type 1 diabetes (T1D) or insulindependent diabetes, generally caused by an autoimmune reaction to antigens of pancreatic β-cells, leading to impaired insulin production, and type 2 diabetes (T2D) or insulin-resistant diabetes, characterised by inefficiency of insulin action. While T1D is mainly observed in children and adolescents, T2D is more common among adults, accounting for more than 90% of the diabetes cases worldwide. The prevalence of diabetes and impaired glucose tolerance achieved now epidemic proportions, respectively at 6.9% and 8.3% of the world population, and predicted to raise to 8. 0% and 10.1% in 2035 [2]. Moreover, diabetes is nowadays a leading cause of death accounting for 8.4% of global mortality in people aged between 20 and 79 years [2]. The main contributor for the high prevalence of diabetes is the rise of obesity, related to the combination of ample food availability and a sedentary lifestyle, contrasting to less abundant food supplies and higher physical activity observed until a century ago.Diabetes is associated with the occurrence of well described microvascular complications that affect different organs, leading most commonly to retinopathy, nephropathy and peripheral neuropathy, which development is dependent on the duration of the disease and glycaemia control [3]. When the control of the disorder allowed patients to live longer and without these Volume 6, N...

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Relationship between atrophy and β‐amyloid deposition in Alzheimer disease

Cited by 338 publications

References 34 publications

Relationship of Hippocampal Volume to Amyloid Burden across Diagnostic Stages of Alzheimer's Disease

Relationship of Hippocampal Volume to Amyloid Burden across Diagnostic Stages of Alzheimer's Disease

Minimal Atrophy of the Entorhinal Cortex and Hippocampus: Progression of Cognitive Impairment

Metabolic Alterations Associated to Brain Dysfunction in Diabetes

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