Aging-Sensitive Networks Within the Human Structural Connectome Are Implicated in Late-Life Cognitive Declines

James W. Madole; Stuart J Ritchie; Simon R. Cox; Colin R. Buchanan; Maria Valdés Hernández; Susana Muñoz Maniega; Joanna M. Wardlaw; Mathew A. Harris Harris; Mark E. Bastin; Ian J. Deary; Elliot M Tucker-Drob

doi:10.1016/j.biopsych.2020.06.010

Aging-Sensitive Networks Within the Human Structural Connectome Are Implicated in Late-Life Cognitive Declines

James W. Madole, Stuart J Ritchie, Simon R. Cox, Colin R. Buchanan, Maria Valdés Hernández, Susana Muñoz Maniega, Joanna M. Wardlaw, Mathew A. Harris Harris, Mark E. Bastin, Ian J. Deary, Elliot M Tucker-Drob

Research output: Contribution to journal › Article › peer-review

Abstract / Description of output

Background
Aging-related cognitive decline is a primary risk factor for Alzheimer’s disease and related dementias. More precise identification of the neurobiological bases of cognitive decline in aging populations may provide critical insights into the precursors of late-life dementias.

Methods
Using structural and diffusion brain MRI data from the UK Biobank (UKB; N = 8,185, ages 45-78 years), we examined aging of regional grey matter volumes (nodes) and white matter structural connectivity (edges) within nine well-characterized networks-of-interest in the human brain connectome. In the independent Lothian Birth Cohort 1936 (LBC1936; N = 534, all age 73 years), we tested whether aging-sensitive connectome elements are enriched for key domains of cognitive function, before and after controlling for early-life cognitive ability.

Results
In UKB, age-differences in individual connectome elements corresponded closely with principal component loadings reflecting connectome-wide integrity (|rnodes| = 0.420; |redges| = 0.583), suggesting that connectome aging occurs on broad dimensions of variation in brain architecture. In LBC1936, composite indices of node integrity were predictive of all domains of cognitive function, whereas composite indices of edge integrity were associated specifically with processing speed. Elements within the Central Executive network were disproportionately predictive of late-life cognitive function relative to the network’s small size. Associations with processing speed and visuospatial ability remained after controlling for childhood cognitive ability.

Conclusions
These results implicate global dimensions of variation in the human structural connectome in aging-related cognitive decline. The Central Executive network may demarcate a constellation of elements that are centrally important to age-related cognitive impairments.

Original language	English
Pages (from-to)	1-12
Journal	Biological Psychiatry
Volume	N/A
Early online date	15 Jun 2020
DOIs	https://doi.org/10.1016/j.biopsych.2020.06.010
Publication status	E-pub ahead of print - 15 Jun 2020

Keywords / Materials (for Non-textual outputs)

cognitive decline
structural MRI
diffusion MRI
connectomics
brain networks
brain age

Access to Document

10.1016/j.biopsych.2020.06.010Licence: Creative Commons: Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND)

MadoleEtalBP2020AgeSensitiveNetworksFinal published version, 1.2 MBLicence: Creative Commons: Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND)

The Disconnected Mind Phase 3
Cox, S. & Deary, I.
UK-based charities
1/04/16 → 31/03/23
Project: Research
Brain imaging and cognitive ageing in the Lothian Birth Cohort 1936: III
Wardlaw, J., Bastin, M. & Deary, I.
MRC
1/05/15 → 30/04/19
Project: Research
RA2662 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2.
Porteous, D.
1/09/13 → 31/08/19
Project: Research

Mark Bastin
- Deanery of Clinical Sciences - Personal Chair of Brain Imaging
- Centre for Clinical Brain Sciences
- Euan MacDonald Centre for Motor Neuron Disease Research
- Edinburgh Neuroscience
- Edinburgh Imaging
Person: Academic: Research Active

Cite this

Madole, J. W., Ritchie, S. J., Cox, S. R., Buchanan, C. R., Valdés Hernández, M., Muñoz Maniega, S., Wardlaw, J. M., Harris, M. A. H., Bastin, M. E., Deary, I. J., & Tucker-Drob, E. M. (2020). Aging-Sensitive Networks Within the Human Structural Connectome Are Implicated in Late-Life Cognitive Declines. Biological Psychiatry, N/A, 1-12. Advance online publication. https://doi.org/10.1016/j.biopsych.2020.06.010

@article{9438b2ca45714c84882faab16c1e8f87,

title = "Aging-Sensitive Networks Within the Human Structural Connectome Are Implicated in Late-Life Cognitive Declines",

abstract = "BackgroundAging-related cognitive decline is a primary risk factor for Alzheimer{\textquoteright}s disease and related dementias. More precise identification of the neurobiological bases of cognitive decline in aging populations may provide critical insights into the precursors of late-life dementias.MethodsUsing structural and diffusion brain MRI data from the UK Biobank (UKB; N = 8,185, ages 45-78 years), we examined aging of regional grey matter volumes (nodes) and white matter structural connectivity (edges) within nine well-characterized networks-of-interest in the human brain connectome. In the independent Lothian Birth Cohort 1936 (LBC1936; N = 534, all age 73 years), we tested whether aging-sensitive connectome elements are enriched for key domains of cognitive function, before and after controlling for early-life cognitive ability.ResultsIn UKB, age-differences in individual connectome elements corresponded closely with principal component loadings reflecting connectome-wide integrity (|rnodes| = 0.420; |redges| = 0.583), suggesting that connectome aging occurs on broad dimensions of variation in brain architecture. In LBC1936, composite indices of node integrity were predictive of all domains of cognitive function, whereas composite indices of edge integrity were associated specifically with processing speed. Elements within the Central Executive network were disproportionately predictive of late-life cognitive function relative to the network{\textquoteright}s small size. Associations with processing speed and visuospatial ability remained after controlling for childhood cognitive ability.Conclusions These results implicate global dimensions of variation in the human structural connectome in aging-related cognitive decline. The Central Executive network may demarcate a constellation of elements that are centrally important to age-related cognitive impairments. ",

keywords = "cognitive decline, structural MRI, diffusion MRI, connectomics, brain networks, brain age",

author = "Madole, {James W.} and Ritchie, {Stuart J} and Cox, {Simon R.} and Buchanan, {Colin R.} and {Vald{\'e}s Hern{\'a}ndez}, Maria and {Mu{\~n}oz Maniega}, Susana and Wardlaw, {Joanna M.} and Harris, {Mathew A. Harris} and Bastin, {Mark E.} and Deary, {Ian J.} and Tucker-Drob, {Elliot M}",

year = "2020",

month = jun,

day = "15",

doi = "10.1016/j.biopsych.2020.06.010",

language = "English",

volume = "N/A",

pages = "1--12",

journal = "Biological Psychiatry",

issn = "0006-3223",

publisher = "Elsevier",

}

TY - JOUR

T1 - Aging-Sensitive Networks Within the Human Structural Connectome Are Implicated in Late-Life Cognitive Declines

AU - Madole, James W.

AU - Ritchie, Stuart J

AU - Cox, Simon R.

AU - Buchanan, Colin R.

AU - Valdés Hernández, Maria

AU - Muñoz Maniega, Susana

AU - Wardlaw, Joanna M.

AU - Harris, Mathew A. Harris

AU - Bastin, Mark E.

AU - Deary, Ian J.

AU - Tucker-Drob, Elliot M

PY - 2020/6/15

Y1 - 2020/6/15

N2 - BackgroundAging-related cognitive decline is a primary risk factor for Alzheimer’s disease and related dementias. More precise identification of the neurobiological bases of cognitive decline in aging populations may provide critical insights into the precursors of late-life dementias.MethodsUsing structural and diffusion brain MRI data from the UK Biobank (UKB; N = 8,185, ages 45-78 years), we examined aging of regional grey matter volumes (nodes) and white matter structural connectivity (edges) within nine well-characterized networks-of-interest in the human brain connectome. In the independent Lothian Birth Cohort 1936 (LBC1936; N = 534, all age 73 years), we tested whether aging-sensitive connectome elements are enriched for key domains of cognitive function, before and after controlling for early-life cognitive ability.ResultsIn UKB, age-differences in individual connectome elements corresponded closely with principal component loadings reflecting connectome-wide integrity (|rnodes| = 0.420; |redges| = 0.583), suggesting that connectome aging occurs on broad dimensions of variation in brain architecture. In LBC1936, composite indices of node integrity were predictive of all domains of cognitive function, whereas composite indices of edge integrity were associated specifically with processing speed. Elements within the Central Executive network were disproportionately predictive of late-life cognitive function relative to the network’s small size. Associations with processing speed and visuospatial ability remained after controlling for childhood cognitive ability.Conclusions These results implicate global dimensions of variation in the human structural connectome in aging-related cognitive decline. The Central Executive network may demarcate a constellation of elements that are centrally important to age-related cognitive impairments.

AB - BackgroundAging-related cognitive decline is a primary risk factor for Alzheimer’s disease and related dementias. More precise identification of the neurobiological bases of cognitive decline in aging populations may provide critical insights into the precursors of late-life dementias.MethodsUsing structural and diffusion brain MRI data from the UK Biobank (UKB; N = 8,185, ages 45-78 years), we examined aging of regional grey matter volumes (nodes) and white matter structural connectivity (edges) within nine well-characterized networks-of-interest in the human brain connectome. In the independent Lothian Birth Cohort 1936 (LBC1936; N = 534, all age 73 years), we tested whether aging-sensitive connectome elements are enriched for key domains of cognitive function, before and after controlling for early-life cognitive ability.ResultsIn UKB, age-differences in individual connectome elements corresponded closely with principal component loadings reflecting connectome-wide integrity (|rnodes| = 0.420; |redges| = 0.583), suggesting that connectome aging occurs on broad dimensions of variation in brain architecture. In LBC1936, composite indices of node integrity were predictive of all domains of cognitive function, whereas composite indices of edge integrity were associated specifically with processing speed. Elements within the Central Executive network were disproportionately predictive of late-life cognitive function relative to the network’s small size. Associations with processing speed and visuospatial ability remained after controlling for childhood cognitive ability.Conclusions These results implicate global dimensions of variation in the human structural connectome in aging-related cognitive decline. The Central Executive network may demarcate a constellation of elements that are centrally important to age-related cognitive impairments.

KW - cognitive decline

KW - structural MRI

KW - diffusion MRI

KW - connectomics

KW - brain networks

KW - brain age

U2 - 10.1016/j.biopsych.2020.06.010

DO - 10.1016/j.biopsych.2020.06.010

M3 - Article

SN - 0006-3223

VL - N/A

SP - 1

EP - 12

JO - Biological Psychiatry

JF - Biological Psychiatry

ER -

Aging-Sensitive Networks Within the Human Structural Connectome Are Implicated in Late-Life Cognitive Declines

Abstract / Description of output

Keywords / Materials (for Non-textual outputs)

Access to Document

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Projects

The Disconnected Mind Phase 3

Brain imaging and cognitive ageing in the Lothian Birth Cohort 1936: III

RA2662 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2.

Profiles

Mark Bastin

Cite this