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Amyloid involvement in subcortical regions predicts cognitive decline.

ABSTRACT: PURPOSE:We estimated whether amyloid involvement in subcortical regions may predict cognitive impairment, and established an amyloid staging scheme based on degree of subcortical amyloid involvement. METHODS:Data from 240 cognitively normal older individuals, 393 participants with mild cognitive impairment, and 126 participants with Alzheimer disease were acquired at Alzheimer's Disease Neuroimaging Initiative sites. To assess subcortical involvement, we analyzed amyloid deposition in amygdala, putamen, and caudate nucleus. We staged participants into a 3-stage model based on cortical and subcortical amyloid involvement: 382 with no cortical or subcortical involvement as stage 0, 165 with cortical but no subcortical involvement as stage 1, and 203 with both cortical and subcortical involvement as stage 2. RESULTS:Amyloid accumulation was first observed in cortical regions and spread down to the putamen, caudate nucleus, and amygdala. In longitudinal analysis, changes in MMSE, ADAS-cog 13, FDG PET SUVR, and hippocampal volumes were steepest in stage 2 followed by stage 1 then stage 0 (p value <0.001). Stage 2 showed steeper changes in MMSE score (? [SE]?=?-0.02 [0.004], p?

SUBMITTER: Cho SH

PROVIDER: S-EPMC6439472 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Amyloid involvement in subcortical regions predicts cognitive decline.

Cho Soo Hyun SH Shin Jeong-Hyeon JH Jang Hyemin H Park Seongbeom S Kim Hee Jin HJ Kim Si Eun SE Kim Seung Joo SJ Kim Yeshin Y Lee Jin San JS Na Duk L DL Lockhart Samuel N SN Rabinovici Gil D GD Seong Joon-Kyung JK Seo Sang Won SW

European journal of nuclear medicine and molecular imaging 20180706 13

<h4>Purpose</h4>We estimated whether amyloid involvement in subcortical regions may predict cognitive impairment, and established an amyloid staging scheme based on degree of subcortical amyloid involvement.<h4>Methods</h4>Data from 240 cognitively normal older individuals, 393 participants with mild cognitive impairment, and 126 participants with Alzheimer disease were acquired at Alzheimer's Disease Neuroimaging Initiative sites. To assess subcortical involvement, we analyzed amyloid depositio ...[more]

PMID: 29980831

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Project description:BackgroundStage 1 of the National Institute on Aging-Alzheimer's Association's proposed Alzheimer's disease continuum is defined as amyloid-β (Aβ) positive but cognitively normal. Identifying at-risk individuals before Aβ reaches pathological levels could have great benefits for early intervention. Although Aβ levels become abnormal long before severe cognitive impairments appear, increasing evidence suggests that subtle cognitive changes may begin early, potentially before Aβ surpasses the threshold for abnormality. We examined whether baseline cognitive performance would predict progression from normal to abnormal levels of Aβ.MethodsWe examined the association of baseline cognitive composites (Preclinical Alzheimer Cognitive Composite, Alzheimer's Disease Neuroimaging Initiative (ADNI) memory factor composite) with progression to Aβ positivity in 292 nondemented, Aβ-negative ADNI participants. Additional analyses included continuous cerebrospinal fluid biomarker levels to examine the effects of subthreshold pathology.ResultsForty participants progressed to Aβ positivity during follow-up. Poorer baseline performance on both cognitive measures was significantly associated with increased odds of progression. More abnormal levels of baseline cerebrospinal fluid phosphorylated tau and subthreshold Aβ were associated with increased odds of progression to Aβ positivity. Nevertheless, baseline ADNI memory factor composite performance predicted progression even after controlling for baseline biomarker levels and APOE genotype (Preclinical Alzheimer Cognitive Composite was trend level). Survival analyses were largely consistent: controlling for baseline biomarker levels, baseline Preclinical Alzheimer Cognitive Composite still significantly predicted progression time to Aβ positivity (ADNI memory factor composite was trend level).ConclusionsThe possibility of intervening before Aβ reaches pathological levels is of obvious benefit. Low-cost, noninvasive cognitive measures can be informative for determining who is likely to progress to Aβ positivity, even after accounting for baseline subthreshold biomarker levels.

Project description:ImportanceCerebrovascular disease (CVD) and Alzheimer disease are significant causes of cognitive impairment in the elderly. However, few studies have evaluated the relationship between CVD and β-amyloid burden in living humans or their synergistic effects on cognition. Thus, there is a need for better understanding of mild cognitive impairment (MCI) before clinical deterioration begins.ObjectiveTo determine the synergistic effects of β-amyloid burden and CVD on cognition in patients with subcortical vascular MCI (svMCI).Design, setting, and participantsA cross-sectional study was conducted using a hospital-based sample at a tertiary referral center. We prospectively recruited 95 patients with svMCI; 67 of these individuals participated in the study. Forty-five patients with amnestic MCI (aMCI) were group matched with those with svMCI by the Clinical Dementia Rating Scale Sum of Boxes.Main outcomes and measuresWe measured β-amyloid burden using positron emission tomography with carbon 11-labeled Pittsburgh Compound B (PiB). Cerebrovascular disease was quantified as white matter hyperintensity volume detected by magnetic resonance imaging fluid-attenuated inversion recovery. Detailed neuropsychological tests were performed to determine the level of patients' cognitive impairment.ResultsOn evaluation, 22 of the svMCI group (33%) and 28 of the aMCI group (62%) were found to be PiB positive. The mean PiB retention ratio was lower in patients with svMCI than in those with aMCI. In svMCI, the PiB retention ratio was associated with cognitive impairments in multiple domains, including language, visuospatial, memory, and frontal executive functions, but was associated only with memory dysfunction in aMCI. A significant interaction between PiB retention ratio and white matter hyperintensity volume was found to affect visuospatial function in patients with svMCI.Conclusions and relevanceMost patients with svMCI do not exhibit substantial amyloid burden, and CVD does not increase β-amyloid burden as measured by amyloid imaging. However, in patients with svMCI, amyloid burden and white matter hyperintensity act synergistically to impair visuospatial function. Therefore, our findings highlight the need for accurate biomarkers, including neuroimaging tools, for early diagnosis and the need to relate these biomarkers to cognitive measurements for effective use in the clinical setting.

Project description:Describing the trajectories of age-related change for different brain structures has been of interest in many recent studies. However, our knowledge regarding these trajectories and their associations is still limited due to small sample sizes and low numbers of repeated measures. For the present study, we used a large longitudinal dataset (four measurements over 4 years) comprising anatomical data from a sample of healthy older adults (N = 231 at baseline). This dataset enables us to gain new insights about volumetric cortical and subcortical changes and their associations in the context of healthy aging. Brain structure volumes were derived from T1-weighted MRI scans using FreeSurfer segmentation tools. Brain structure trajectories were fitted using mixed models and latent growth curve models to gain information about the mean extent and variability of decline trajectories for different brain structures as well as the associations between individual trajectories. On the group level, our analyses indicate similar linear changes for frontal and parietal brain regions, while medial temporal regions showed an accelerated decline with advancing age. Regarding subcortical regions, some structures showed strong declines (e.g., hippocampus), others showed little decline (e.g., pallidum). Our data provide little evidence for sex differences regarding the aforementioned trajectories. Between-person variability of the person-specific slopes (random slopes) was largest in subcortical and medial temporal brain structures. When looking at the associations between the random slopes from each brain structure, we found that the decline is largely homogenous across the majority of cortical brain structures. In subcortical and medial temporal brain structures, however, more heterogeneity of the decline was observed, meaning that the extent of the decline in one structure is less predictive of the decline in another structure. Taken together, our study contributes to enhancing our understanding of structural brain aging by demonstrating (1) that average volumetric change differs across the brain and (2) that there are regional differences with respect to between-person variability in the slopes. Moreover, our data suggest (3) that random slopes are highly correlated across large parts of the cerebral cortex but (4) that some brain regions (i.e., medial temporal regions) deviate from this homogeneity.

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Amyloid involvement in subcortical regions predicts cognitive decline.

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Amyloid involvement in subcortical regions predicts cognitive decline.

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