Grey-Matter Structure Markers of Alzheimer's Disease, Alzheimer's Conversion, Functioning and Cognition: A Meta-Analysis Across 11 Cohorts

Alzheimer's disease (AD) brain markers are needed to select people with early-stage AD for clinical trials and as quantitative endpoint measures in trials. Using 10 clinical cohorts (N = 9140) and the community volunteer UK Biobank (N = 37,664) we performed region of interest (ROI) and vertex-wise analyses of grey-matter structure (thickness, surface area and volume). We identified 94 trait-ROI significant associations, and 307 distinct cluster of vertex-associations, which partly overlap the ROI associations. For AD versus controls, smaller hippocampus, amygdala and of the medial temporal lobe (fusiform and parahippocampal gyri) was confirmed and the vertex-wise results provided unprecedented localisation of some of the associated region. We replicated AD associated differences in several subcortical (putamen, accumbens) and cortical regions (inferior parietal, postcentral, middle temporal, transverse temporal, inferior temporal, paracentral, superior frontal). These grey-matter regions and their relative effect sizes can help refine our understanding of the brain regions that may drive or precede the widespread brain atrophy observed in AD. An AD grey-matter score evaluated in independent cohorts was significantly associated with cognition, MCI status, AD conversion (progression from cognitively normal or MCI to AD), genetic risk, and tau concentration in individuals with none or mild cognitive impairments (AUC in 0.54–0.70, p-value < 5e-4). In addition, some of the grey-matter regions associated with cognitive impairment, progression to AD (‘conversion’), and cognition/functional scores were also associated with AD, which sheds light on the grey-matter markers of disease stages, and their relationship with cognitive or functional impairment. Our multi-cohort approach provides robust and fine-grained maps the grey-matter structures associated with AD, symptoms, and progression, and calls for even larger initiatives to unveil the full complexity of grey-matter structure in AD.

Publication Details

Journal
UCL Discovery (University College London)
Published
2025-01-01
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
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article

Grey-Matter Structure Markers of Alzheimer's Disease, Alzheimer's Conversion, Functioning and Cognition: A Meta-Analysis Across 11 Cohorts

UCL Discovery (University College London)
Cell Image Analysis Techniques
article

Grey-Matter Structure Markers of Alzheimer's Disease, Alzheimer's Conversion, Functioning and Cognition: A Meta-Analysis Across 11 Cohorts

article en

Abstract

Alzheimer's disease (AD) brain markers are needed to select people with early-stage AD for clinical trials and as quantitative endpoint measures in trials. Using 10 clinical cohorts (N = 9140) and the community volunteer UK Biobank (N = 37,664) we performed region of interest (ROI) and vertex-wise analyses of grey-matter structure (thickness, surface area and volume). We identified 94 trait-ROI significant associations, and 307 distinct cluster of vertex-associations, which partly overlap the ROI associations. For AD versus controls, smaller hippocampus, amygdala and of the medial temporal lobe (fusiform and parahippocampal gyri) was confirmed and the vertex-wise results provided unprecedented localisation of some of the associated region. We replicated AD associated differences in several subcortical (putamen, accumbens) and cortical regions (inferior parietal, postcentral, middle temporal, transverse temporal, inferior temporal, paracentral, superior frontal). These grey-matter regions and their relative effect sizes can help refine our understanding of the brain regions that may drive or precede the widespread brain atrophy observed in AD. An AD grey-matter score evaluated in independent cohorts was significantly associated with cognition, MCI status, AD conversion (progression from cognitively normal or MCI to AD), genetic risk, and tau concentration in individuals with none or mild cognitive impairments (AUC in 0.54–0.70, p-value < 5e-4). In addition, some of the grey-matter regions associated with cognitive impairment, progression to AD (‘conversion’), and cognition/functional scores were also associated with AD, which sheds light on the grey-matter markers of disease stages, and their relationship with cognitive or functional impairment. Our multi-cohort approach provides robust and fine-grained maps the grey-matter structures associated with AD, symptoms, and progression, and calls for even larger initiatives to unveil the full complexity of grey-matter structure in AD.

UCL Discovery (University College London)
National Science Foundation, U.S. Department of Defense, University of Southern California, Alzheimer's Disease Neuroimaging Initiative, Northern California Institute for Research and Education, Neuroscience Research Australia, Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation, European Federation of Pharmaceutical Industries and Associations, National Institute for Health and Care Research, European Commission, Commonwealth Scientific and Industrial Research Organisation, Swansea University, Agence Nationale de la Recherche, Institut National de la Santé et de la Recherche Médicale, University of Melbourne, University of Queensland, Fondazione Cariplo, Dementia Collaborative Research Centres, Australia, Ministero della Salute, Université de Bordeaux, Université de Genève, University College London Hospitals NHS Foundation Trust, National Institutes of Health, Horizon 2020 Framework Programme, Canadian Institutes of Health Research, Medical Research Council, National Health and Medical Research Council
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Cell Image Analysis Techniques
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