Nonlinear time course of brain volume loss in cognitively normal and impaired elders

Schuff, Norbert; Tosun, Duygu; Insel, Philip S.; Chiang, Gloria; Truran, Diana; Aisen, Paul S.; Jack, Clifford R.; Weiner, Michael W.

doi:10.1016/j.neurobiolaging.2010.07.012

Cited by 72 publications

(75 citation statements)

References 32 publications

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“…The annual rate of change from baseline (estimated at 0.8% per year) (Figs. 2 and 4; Table 3) over the whole medial temporal lobe is within the range found by other means, namely 1.41% (CI: 0.52, 2.30) for hippocampal atrophy, according to a meta-analysis from Barnes et al (2009), and around 1% for either the hippocampus, the parahippocampal gyrus, and the entorhinal cortex, according to a recent study by Schuff et al (2012) on similar ADNI data.…”

Section: Tracking Neurodegeneration Related To Agingsupporting

confidence: 80%

See 1 more Smart Citation

Single time point high-dimensional morphometry in Alzheimer's disease: group statistics on longitudinally acquired data

Duchesne¹,

Valdivia²,

Mouiha³

et al. 2015

Neurobiology of Aging

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Section: Tracking Neurodegeneration Related To Agingsupporting

confidence: 80%

“…A similar issue was noticed in other volumetric studies (e.g., Schuff et al, 2012). Given that as the disease progresses, areas in the frontal and cingulate areas exhibit pathology and atrophy, one alternative to maintain sensitivity could be to use different VOIs at different disease stages.…”

Section: Statistically Significant Differences In Trajectoriesmentioning

confidence: 55%

Single time point high-dimensional morphometry in Alzheimer's disease: group statistics on longitudinally acquired data

Duchesne¹,

Valdivia²,

Mouiha³

et al. 2015

Neurobiology of Aging

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“…5 Several studies have attempted to fit sigmoidal models for the trajectory of cerebral tissue loss (e.g., hippocampus and cortical thickness) using cross-sectional data from ADNI. 11,30,31 The sigmoidal model implies that atrophy rates within a subject initially increase from zero, remain constant for a period, and then eventually decrease to zero. In the current study, we modeled the trajectory of cerebral tissue loss in each disease group using longitudinal data from AD-NI over a 2-or 3-year period.…”

Section: Resultsmentioning

confidence: 99%

Cerebral atrophy in mild cognitive impairment and Alzheimer disease

et al. 2013

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Objective: To quantify the regional and global cerebral atrophy rates and assess acceleration rates in healthy controls, subjects with mild cognitive impairment (MCI), and subjects with mild Alzheimer disease (AD).Methods: Using 0-, 6-, 12-, 18-, 24-, and 36-month MRI scans of controls and subjects with MCI and AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we calculated volume change of whole brain, hippocampus, and ventricles between all pairs of scans using the boundary shift integral. Results:We found no evidence of acceleration in whole-brain atrophy rates in any group. There was evidence that hippocampal atrophy rates in MCI subjects accelerate by 0.22%/year 2 on average (p 5 0.037). There was evidence of acceleration in rates of ventricular enlargement in subjects with MCI (p 5 0.001) and AD (p , 0.001), with rates estimated to increase by 0.27 mL/year 2 (95% confidence interval 0.12, 0.43) and 0.88 mL/year 2 (95% confidence interval 0.47, 1.29), respectively. A post hoc analysis suggested that the acceleration of hippocampal loss in MCI subjects was mainly driven by the MCI subjects that were observed to progress to clinical AD within 3 years of baseline, with this group showing hippocampal atrophy rate acceleration of 0.50%/year 2 (p 5 0.003). Conclusions:The small acceleration rates suggest a long period of transition to the pathologic losses seen in clinical AD. The acceleration in hippocampal atrophy rates in MCI subjects in the ADNI seems to be driven by those MCI subjects who concurrently progressed to a clinical diagnosis of AD. Neurology Alzheimer disease (AD) is associated with higher rates of brain tissue loss than normal aging, 1 with the rate in mild cognitive impairment (MCI) falling somewhere in between.2 This implies increases in the rate of tissue loss (i.e., acceleration) as the individual progresses from normal to MCI and then on to dementia due to AD.3,4 A sigmoidal model of tissue loss in AD 5 has been proposed that suggests the rate of tissue loss first accelerates, then remains constant, and finally decelerates; however, detailed data about how the rates of regional and global atrophy change over time are lacking. Assessing how rates of atrophy change in the transition from normal aging through early cognitive impairment and on to dementia due to AD is important for understanding the presymptomatic period of AD, which is increasingly considered as a potential therapeutic window for disease-modification trials.A number of studies have investigated acceleration in regional and global atrophy rates in normal aging, MCI, and clinically diagnosed AD, with most modeling tissue loss as a function of age or time from a particular clinical stage (e.g., at the time of AD dementia diagnosis or Mini-Mental State

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“…However, the different Aβ measurements were still highly correlated with each other in terms of their association with HAR, and showed a high level of consistency in terms of the percent of HAR attributable to Aβ status. Finally, because we calculated HAR using a linear model, we may have overestimated contributions of Aβ and age to the extent that accelerated and/or nonlinear HAR were present in the data (Schuff et al, 2012). …”

Section: Discussionmentioning

confidence: 99%

Variables associated with hippocampal atrophy rate in normal aging and mild cognitive impairment

Nosheny

Insel

Truran

et al. 2015

Neurobiology of Aging

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The goal of this study was to identify factors contributing to hippocampal atrophy rate (HAR) in clinically-normal older adults (NC) and participants with mild cognitive impairment (MCI). Longitudinal HAR was measured on T1-weighted MRI, and the contribution of age, gender, ApoE ε4 status, intracranial volume, white matter lesions, and β-amyloid (Aβ) levels to HAR was determined using linear regression. Age-related effects of HAR were compared in Aβ positive (Aβ+) and Aβ negative (Aβ−) participants. Age and Aβ levels had independent effects on HAR in NC, while gender, ApoE ε4 status, and Aβ levels were associated with HAR in MCI. In multivariable models, Aβ levels were associated with HAR in NC; ApoE ε4 and Aβ levels were associated with HAR in MCI. In MCI, age was a stronger predictor of HAR in Aβ− versus Aβ+ participants. HAR was higher in Aβ+ participants, but the majority of HAR was due to factors other than Aβ status. Age-related effects on HAR did not differ between NC versus MCI participants with the same Aβ status. Therefore we conclude that even when accounting for other covariates, Aβ status, and not age, is a significant predictor of HAR; and that the majority of HAR is not accounted for by Aβ status in either NC or MCI.

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Nonlinear time course of brain volume loss in cognitively normal and impaired elders

Cited by 72 publications

References 32 publications

Single time point high-dimensional morphometry in Alzheimer's disease: group statistics on longitudinally acquired data

Single time point high-dimensional morphometry in Alzheimer's disease: group statistics on longitudinally acquired data

Cerebral atrophy in mild cognitive impairment and Alzheimer disease

Variables associated with hippocampal atrophy rate in normal aging and mild cognitive impairment

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