4
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Latent patterns of task-related functional connectivity in relation to regions of hyperactivation in individuals at risk of Alzheimer’s disease

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Highlights

          • Hyperactivation relates to memory-related network dysfunction in SCD + and MCI.

          • Hippocampal hyperactivation and connectivity relate to worst memory performance.

          • In contrast, neocortical hyperactivation and connectivity may reflect compensation.

          Abstract

          The goal of this study was to assess how task-related hyperactivation relates to brain network dysfunction and memory performance in individuals at risk of Alzheimer’s disease (AD). Eighty participants from the CIMA-Q cohort were included, of which 28 had subjective cognitive decline plus (SCD +), as they had memory complaints and worries in addition to a smaller hippocampal volume and/or an APOE4 allele, 26 had amnestic mild cognitive impairment (MCI) and 26 were healthy controls without memory complaints. Functional magnetic resonance imaging (fMRI) activation was measured during an object-location memory task. Seed-partial least square analyses (seed-PLS) were conducted in controls and in the SCD +/MCI groups to yield sets of orthogonal latent variables (LVs) assessing the triple association between: i) seed activity in brain regions found to be hyperactive in individuals at risk of AD (left hippocampus, left superior parietal lobule, right inferior temporal lobe), ii) latent patterns of whole-brain task-related activation, and iii) associative memory performance. Three LVs in the SCD + and MCI groups (67.88% of total covariance explained) and two LVs in the controls (77.85% of total covariance explained) were significant. While controls and SCD +/MCI groups shared a common pattern of memory-related connectivity, patterns of hyperactivation-networks interactions were unique to the clinical groups. Interestingly, higher hippocampal connectivity was associated with poorer memory performance whereas higher neocortical connectivity predicted better memory performance in SCD + and MCI groups. Our data provides empirical evidence that early dysfunction in brain activation and connectivity is present in the very early stages of AD and offers new insights on the relationship between functional brain alterations and memory performance.

          Related collections

          Most cited references72

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease

          In 2011, the National Institute on Aging and Alzheimer’s Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer’s Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer’s Association Research Framework, Alzheimer’s disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found

            The diagnosis of mild cognitive impairment due to Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease

            The National Institute on Aging and the Alzheimer's Association charged a workgroup with the task of developing criteria for the symptomatic predementia phase of Alzheimer's disease (AD), referred to in this article as mild cognitive impairment due to AD. The workgroup developed the following two sets of criteria: (1) core clinical criteria that could be used by healthcare providers without access to advanced imaging techniques or cerebrospinal fluid analysis, and (2) research criteria that could be used in clinical research settings, including clinical trials. The second set of criteria incorporate the use of biomarkers based on imaging and cerebrospinal fluid measures. The final set of criteria for mild cognitive impairment due to AD has four levels of certainty, depending on the presence and nature of the biomarker findings. Considerable work is needed to validate the criteria that use biomarkers and to standardize biomarker analysis for use in community settings. Copyright © 2011 The Alzheimer's Association. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Cortical surface-based analysis. I. Segmentation and surface reconstruction.

              Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging. Copyright 1999 Academic Press.
                Bookmark

                Author and article information

                Contributors
                Journal
                Neuroimage Clin
                Neuroimage Clin
                NeuroImage : Clinical
                Elsevier
                2213-1582
                26 March 2021
                2021
                26 March 2021
                : 30
                : 102643
                Affiliations
                [a ]Research Center, Institut universitaire de gériatrie de Montréal, Montreal, Canada
                [b ]Department of Psychology, Université de Montréal, Montreal, Canada
                [c ]Department of Psychiatry, McGill University, Montreal, Canada
                [d ]Douglas Research Centre, Montreal, Canada
                Author notes
                [* ]Corresponding author at: Research Centre, Institut universitaire de gériatrie de Montréal, 4565 Queen-Mary Rd, Montreal, Quebec H3W 1W5, Canada. sylvie.belleville@ 123456umontreal.ca
                Article
                S2213-1582(21)00087-5 102643
                10.1016/j.nicl.2021.102643
                8050799
                33813263
                3964aafe-a026-4bc0-bb04-a3d8ba38a3f3
                Crown Copyright © 2021 Published by Elsevier Inc.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 13 October 2020
                : 18 March 2021
                : 19 March 2021
                Categories
                Regular Article

                functional connectivity,hyperactivation,mild cognitive impairment,subjective cognitive decline,task-related fmri

                Comments

                Comment on this article