A low-dimensional cognitive-network space in Alzheimer's disease and frontotemporal dementia

Autor:	Lorenzo Pini, Siemon C de Lange, Francesca Benedetta Pizzini, Ilaria Boscolo Galazzo, Rosa Manenti, Maria Cotelli, Samantha Galluzzi, Maria Sofia Cotelli, Maurizio Corbetta, Martijn P van den Heuvel, Michela Pievani
Přispěvatelé:	Complex Trait Genetics, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Amsterdam Neuroscience - Complex Trait Genetics, Netherlands Institute for Neuroscience (NIN), Human genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	Aged 80 and over Brain network Cognitive-network association Functional imaging Low dimensionality Brain Mapping Alzheimer Disease/complications Settore M-PSI/02 - PSICOBIOLOGIA E PSICOLOGIA FISIOLOGICA Cognitive Neuroscience Middle Aged Frontotemporal Dementia/complications Magnetic Resonance Imaging/methods Cognition Neurology 80 and over Connectome Humans Brain/pathology Neurology (clinical) Aged
Zdroj:	Pini, L, de Lange, S C, Pizzini, F B, Boscolo Galazzo, I, Manenti, R, Cotelli, M, Galluzzi, S, Cotelli, M S, Corbetta, M, van den Heuvel, M P & Pievani, M 2022, ' A low-dimensional cognitive-network space in Alzheimer's disease and frontotemporal dementia ', Alzheimer's Research & Therapy, vol. 14, 199, pp. 1-14 . https://doi.org/10.1186/s13195-022-01145-x Alzheimer's Research & Therapy, 14:199, 1-14. BioMed Central Alzheimer's Research & Therapy, 14(1). BioMed Central Pini, L, de Lange, S C, Pizzini, F B, Boscolo Galazzo, I, Manenti, R, Cotelli, M, Galluzzi, S, Cotelli, M S, Corbetta, M, van den Heuvel, M P & Pievani, M 2022, ' A low-dimensional cognitive-network space in Alzheimer’s disease and frontotemporal dementia ', Alzheimer's Research and Therapy, vol. 14, no. 1, 199 . https://doi.org/10.1186/s13195-022-01145-x Alzheimer's Research and Therapy, 14(1):199. BioMed Central
ISSN:	1758-9193
DOI:	10.1186/s13195-022-01145-x
Popis:	Background Alzheimer’s disease (AD) and frontotemporal dementia (FTD) show network dysfunctions linked with cognitive deficits. Within this framework, network abnormalities between AD and FTD show both convergent and divergent patterns. However, these functional patterns are far from being established and their relevance to cognitive processes remains to be elucidated. Methods We investigated the relationship between cognition and functional connectivity of major cognitive networks in these diseases. Twenty-three bvFTD (age: 71±10), 22 AD (age: 72±6), and 20 controls (age: 72±6) underwent cognitive evaluation and resting-state functional MRI. Principal component analysis was used to describe cognitive variance across participants. Brain network connectivity was estimated with connectome analysis. Connectivity matrices were created assessing correlations between parcels within each functional network. The following cognitive networks were considered: default mode (DMN), dorsal attention (DAN), ventral attention (VAN), and frontoparietal (FPN) networks. The relationship between cognition and connectivity was assessed using a bootstrapping correlation and interaction analyses. Results Three principal cognitive components explained more than 80% of the cognitive variance: the first component (cogPC1) loaded on memory, the second component (cogPC2) loaded on emotion and language, and the third component (cogPC3) loaded on the visuo-spatial and attentional domains. Compared to HC, AD and bvFTD showed impairment in all cogPCs (pp=0.031). At the network level, the DMN showed a significant association in the whole group with cogPC1 and cogPC2 and the VAN with cogPC2. By contrast, DAN and FPN showed a divergent pattern between diagnosis and connectivity for cogPC2. We confirmed these results by means of a multivariate analysis (canonical correlation). Conclusions A low-dimensional representation can account for a large variance in cognitive scores in the continuum from normal to pathological aging. Moreover, cognitive components showed both convergent and divergent patterns with connectivity across AD and bvFTD. The convergent pattern was observed across the networks primarily involved in these diseases (i.e., the DMN and VAN), while a divergent FC-cognitive pattern was mainly observed between attention/executive networks and the language/emotion cognitive component, suggesting the co-existence of compensatory and detrimental mechanisms underlying these components.
Databáze:	OpenAIRE
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