Brain connectivity in frailty: insights from The Irish Longitudinal Study on Ageing (TILDA)

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Journal ArticleDate:
2023Access:
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Gutiérrez Zúñiga R, Davis J.R., Boyle R, De Looze C, Meaney J, Whelan R, Kenny R.A., Knight S.P., Romero-Ortuño R, Brain connectivity in frailty: insights from The Irish Longitudinal Study on Ageing (TILDA), Neurobiology of Aging, 2023Download Item:
Abstract:
Frailty in older adults is associated with greater risk of cognitive decline. Brain connectivity insights could
help understand the association, but studies are lacking. We applied connectome-based predictive modelling to a 32-item self-reported Frailty Index (FI) using resting state functional MRI data from The Irish Longitudinal Study on Ageing. A total of 347 participants were included (48.9% male, mean age 68.2 years).
From connectome-based predictive modeling, we obtained 204 edges that positively correlated with the
FI and composed the “frailty network” characterised by connectivity of the visual network (right); and
188 edges that negatively correlated with the FI and formed the “robustness network” characterized by
connectivity in the basal ganglia. Both networks’ highest degree node was the caudate but with differ-
ent patterns: from caudate to visual network in the frailty network; and to default mode network in
the robustness network. The FI was correlated with walking speed but not with metrics of global cognition, reinforcing the matching between the FI and the brain connectivity pattern found (main predicted
connectivity in basal ganglia).
Sponsor
Grant Number
Science Foundation Ireland (SFI)
18/FRL/6188
Author's Homepage:
http://people.tcd.ie/rkennyhttp://people.tcd.ie/romeroor
http://people.tcd.ie/siknight
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Science Foundation Ireland (SFI)Type of material:
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Neurobiology of Aging;Availability:
Full text availableSubject:
Brain connectivity, Frailty, Connectome-based predictive modeling, Ageing, Magnetic resonance imagingSubject (TCD):
Ageing , Neuroscience , AGEING , NeuroscienceDOI:
https://doi.org/10.1016/j.neurobiolaging.2023.01.001Metadata
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