Resting State Abnormalities of the Default Mode Network in Mild Cognitive Impairment: A Systematic Review and Meta-Analysis
Year: 2019
Type: review
Study designs: Systematic Review, Meta-Analysis
Abstract: BACKGROUND: Large-scale brain networks such as the default mode network (DMN) are often disrupted in Alzheimer's disease (AD). Numerous studies have examined DMN functional connectivity in those with mild cognitive impairment (MCI), a presumed AD precursor, to discover a biomarker of AD risk. Prior reviews were qualitative or limited in scope or approach. OBJECTIVE: We aimed to systematically and quantitatively review DMN resting state fMRI studies comparing MCI and healthy comparison (HC) groups. METHODS: PubMed was searched for relevant articles. Study characteristics were abstracted and the number of studies showing no group difference or hyper- versus hypo-connnectivity in MCI was tallied. A voxel-wise (ES-SDM) meta-analysis was conducted to identify regional group differences. RESULTS: Qualitatively, our review of 57 MCI versus HC comparisons suggests substantial inconsistency; 9 showed no group difference, 8 showed MCI > HC and 22 showed HC > MCI across the brain, and 18 showed regionally-mixed directions of effect. The meta-analysis of 31 studies revealed areas of significant hypo- and hyper-connectivity in MCI, including hypoconnectivity in the posterior cingulate cortex/precuneus (z = -3.1, p < 0.0001). Very few individual studies, however, showed patterns resembling the meta-analytic results. Methodological differences did not appear to explain inconsistencies. CONCLUSIONS: The pattern of altered resting DMN function or connectivity in MCI is complex and variable across studies. To date, no index of DMN connectivity qualifies as a useful biomarker of MCI or risk for AD. Refinements to MCI diagnosis, including other biological markers, or longitudinal studies of progression to AD, might identify DMN alterations predictive of AD risk.
Source: Journal of Alzheimer s Disease
DOI: 10.3233/jad-180847
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
Funders: U.S. Department of Veterans Affairs, Ellison Medical Foundation, Center of Excellence for Stress and Mental Health, National Institutes of Health, University of California, San Diego, National Institute on Aging, National Institute of Mental Health, National Institute on Drug Abuse, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering, National Center for Research Resources, NIH Clinical Center
Awards: G1067601299, G1077478456, G162442450, G1712482974, G1719905995, G1758707147, G1865263550, G1870985794, G1923530831, G1947016736, G2240379263, G2570321972, G286115173, Morphometry Biomedical Informatics Research Network, G3059684269, The VETSA Longitudinal Twin Study of Cortisol and Aging, Inferring in Vivo Cytoarchitectural Borders in the Medial Temporal Lobe, G4824552871, G5032770946, G5458268010, G551696275, G6766361133, G775070230, Psychometric and Genetic Assessments of Substance Use, G821076974, G8304064054, Tools for Analyzing Cortical Structure and Connectivity, G9000074708, G9000085026, G9000162060, G9000219367, ResearchTraining: Psychiatric and Statistical Genetics
OpenAlex ID: W2948560263