Morphometric network differences in ageing versus Alzheimer's disease dementia.
|Title||Morphometric network differences in ageing versus Alzheimer's disease dementia.|
|Publication Type||Journal Article|
|Year of Publication||2020|
|Authors||Binette APichet, Gonneaud J, Vogel JW, La Joie R, Rosa-Neto P, D Collins L, Poirier J, Breitner JCS, Villeneuve S, Vachon-Presseau E|
|Corporate Authors||Alzheimer’s Disease Neuroimaging Initiative, PREVENT-AD Research Group|
|Date Published||2020 02 01|
|Keywords||Adolescent, Adult, Aged, Aged, 80 and over, Aging, Alzheimer Disease, Brain, Cognition Disorders, Cognitive Dysfunction, Dementia, Disease Progression, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Young Adult|
Age being the main risk factor for Alzheimer's disease, it is particularly challenging to disentangle structural changes related to normal brain ageing from those specific to Alzheimer's disease. Most studies aiming to make this distinction focused on older adults only and on a priori anatomical regions. Drawing on a large, multi-cohort dataset ranging from young adults (n = 468; age range 18-35 years), to older adults with intact cognition (n = 431; age range 55-90 years) and with Alzheimer's disease (n = 50 with late mild cognitive impairment and 71 with Alzheimer's dementia, age range 56-88 years), we investigated grey matter organization and volume differences in ageing and Alzheimer's disease. Using independent component analysis on all participants' structural MRI, we first derived morphometric networks and extracted grey matter volume in each network. We also derived a measure of whole-brain grey matter pattern organization by correlating grey matter volume in all networks across all participants from the same cohort. We used logistic regressions and receiver operating characteristic analyses to evaluate how well grey matter volume in each network and whole-brain pattern could discriminate between ageing and Alzheimer's disease. Because increased heterogeneity is often reported as one of the main features characterizing brain ageing, we also evaluated interindividual heterogeneity within morphometric networks and across the whole-brain organization in ageing and Alzheimer's disease. Finally, to investigate the clinical validity of the different grey matter features, we evaluated whether grey matter volume or whole-brain pattern was related to clinical progression in cognitively normal older adults. Ageing and Alzheimer's disease contributed additive effects on grey matter volume in nearly all networks, except frontal lobe networks, where differences in grey matter were more specific to ageing. While no networks specifically discriminated Alzheimer's disease from ageing, heterogeneity in grey matter volumes across morphometric networks and in the whole-brain grey matter pattern characterized individuals with cognitive impairments. Preservation of the whole-brain grey matter pattern was also related to lower risk of developing cognitive impairment, more so than grey matter volume. These results suggest both ageing and Alzheimer's disease involve widespread atrophy, but that the clinical expression of Alzheimer's disease is uniquely associated with disruption of morphometric organization.
|PubMed Central ID||PMC7009528|
|Grant List||U01 AG024904 / AG / NIA NIH HHS / United States|