Neuropsychological Signature of Mild Cognitive Impairment
Poster No:
191
Submission Type:
Abstract Submission
Authors:
Damien Marie1, Dimitra Kokkinou2, Chantal Junker-Tschopp3, Gilles Allali4, Matthias Kliegel5, Andrea Brioschi Guevara4, Giovanni Frisoni6, Clara James2
Institutions:
1Center for Biomedical Imaging, Cognitive and Affective Neuroimaging section, University of Geneva, Geneva, Switzerland, 2Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland, Geneva, Switzerland, 3Geneva School of Social Work, University of Applied Sciences and Arts Western Switzerland, Geneva, Switzerland, 4Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, 5Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland, 6Geneva University Hospitals and University of Geneva, Geneva, Switzerland
First Author:
Damien Marie
Center for Biomedical Imaging, Cognitive and Affective Neuroimaging section, University of Geneva
Geneva, Switzerland
Center for Biomedical Imaging, Cognitive and Affective Neuroimaging section, University of Geneva
Geneva, Switzerland
Co-Author(s):
Dimitra Kokkinou
Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland
Geneva, Switzerland
Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland
Geneva, Switzerland
Chantal Junker-Tschopp
Geneva School of Social Work, University of Applied Sciences and Arts Western Switzerland
Geneva, Switzerland
Geneva School of Social Work, University of Applied Sciences and Arts Western Switzerland
Geneva, Switzerland
Matthias Kliegel
Faculty of Psychology and Educational Sciences, University of Geneva
Geneva, Switzerland
Faculty of Psychology and Educational Sciences, University of Geneva
Geneva, Switzerland
Andrea Brioschi Guevara
Lausanne University Hospital and University of Lausanne
Lausanne, Switzerland
Lausanne University Hospital and University of Lausanne
Lausanne, Switzerland
Clara James
Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland
Geneva, Switzerland
Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland
Geneva, Switzerland
Introduction:
Mild Cognitive Impairment (MCI) represents a cognitive state between normal aging and dementia [1, 2]. MCI does not impact daily life functioning, but impairments occur in various cognitive domains (memory, executive functions, etc. [3]). In addition, increased grey matter atrophy in particular in the hippocampus (HIP) [4], and functional connectivity alterations [5], are prominent features of MCI. Yet, functional connectivity changes associated with atrophy remain underinvestigated [6]. No studies evaluated the degree of independent association between such brain features and performance in various domains. Finally, no studies evaluated the network of relationships between grey matter atrophy, associated functional connectivity and cognitive performance in MCI and healthy aging.
Methods:
26 MCI patients (71.5 ± 7.5 years old, 69% ♀) and 15 healthy controls (HC) were recruited (70.3 ± 4.6 years old, 87% ♀, no difference between groups). Diagnosis was performed by hospital memory clinics. We evaluated group differences in cognition, including the COGTEL [7], a global measure of cognitive function with a linear mixed model with the standardized performance score, z(performance), as the dependent variable (random effect: subject; fixed effects: Age, Site, Group (2 levels: MCI, HC), Psychometric Test (9 levels corresponding to different tests, see Figure 1), Group * Psychometric Test interaction). 3T Siemens Magnetic Resonance Imaging (MRI) data acquisition included structural imaging (MP2RAGE, 1 mm isotropic voxel size) and resting-state functional MRI (EPI, 2.5 mm isotropic voxel size, repetition time = 1.35s, 440 volumes). Grey matter (GM) volume atrophy was evaluated using whole-brain voxel-based morphometry (CAT12). Functional connectivity associated with atrophy was computed with CONN toolbox, following a seed-based approach using the 3 significant clusters of atrophy extracted from the VBM analysis. We used a partial correlation matrix analysis to evaluate independent relationships between behavior and brain features in the full population, and a network-based analysis independently in MCI and HC).
Results:
We report lower performances in MCI compared to HC [F(1, 36.13) = 28.8, p < 0.0001] at the level of each test (Figure 1). A significant GM atrophy in MCI compared to HC in the left, right HIP and an antero-medial region of the cerebellum (p < 0.05 FWE at cluster-level). Significant differences in functional connectivity based on the left HIP atrophy cluster were also present, with an hypoconnectivity in left and right cortico-subcortical sensorimotor and executive function networks in MCI compared to HC (p < 0.05 FDR at cluster-level). In the full population, the partial correlation matrix analysis shows strong positive independent associations between brain features (rho > 0.65), and weak to strong positive associations between independent brain features and cognitive performance (Figure 2). The network-based analysis shows high sparsity in the MCI network (0.90 vs. 0.41 in HC). While the MCI network includes a few associations (8 non-zero edges out of 78), the healthy control network is well connected, presenting a large number of strong associations between features (46 non-zero edges out of 78).
·Figure1
·Figure 2
Conclusions:
We reproduce the MCI hippocampus atrophy, a prominent feature of this disorder. We confirm that atrophy relates partly to decreased functional connectivity- Hippocampus altered structure/function is associated with poor performance in various domains, in line with previous independent reports relating hippocampus atrophy, hypoconnectivity, and cognitive deficits to MCI-to-dementia conversion [8]. Yet, disconnection occurs between brain features and cognitive performance in MCI, which may be a manifestation of cognitive reserve decline.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making
Learning and Memory:
Learning and Memory Other
Lifespan Development:
Aging 2
Modeling and Analysis Methods:
Multivariate Approaches
Keywords:
Aging
Degenerative Disease
Other - mild cognitive impairment; MCI; voxel-based morphometry; grey matter; seed-based functional connectivity; network-based analysis
1|2Indicates the priority used for review
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Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
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