Literature DB >> 34775210

Brain-predicted age difference is associated with cognitive processing in later-life.

Jo Wrigglesworth1, Nurathifah Yaacob1, Phillip Ward2, Robyn L Woods1, John McNeil1, Elsdon Storey1, Gary Egan3, Anne Murray4, Raj C Shah5, Sharna D Jamadar2, Ruth Trevaks1, Stephanie Ward6, Ian H Harding7, Joanne Ryan8.   

Abstract

Brain age is a neuroimaging-based biomarker of aging. This study examined whether the difference between brain age and chronological age (brain-PAD) is associated with cognitive function at baseline and longitudinally. Participants were relatively healthy, predominantly white community-dwelling older adults (n = 531, aged ≥70 years), with high educational attainment (61% ≥12 years) and socioeconomic status (59% ≥75th percentile). Brain age was estimated from T1-weighted magnetic resonance images using an algorithm by Cole et al., 2018. After controlling for age, gender, education, depression and body mass index, brain-PAD was negatively associated with psychomotor speed (Symbol Digit Modalities Test) at baseline (Bonferroni p < 0.006), but was not associated with baseline verbal fluency (Controlled Oral Word Association Test), delayed recall (Hopkins Learning Test Revised), or general cognitive status (Mini-Mental State Examination). Baseline brain-PAD was not associated with 3-year change in cognition (Bonferroni p > 0.006). These findings indicate that even in relatively healthy older people, accelerated brain aging is associated with worse psychomotor speed, but future longitudinal research into changes in brain-PAD is needed.
Copyright © 2021. Published by Elsevier Inc.

Entities:  

Keywords:  Brain aging; Cognitive function; Estimated brain age; Magnetic resonance imaging; Neuroimaging; Predicted age difference

Mesh:

Year:  2021        PMID: 34775210      PMCID: PMC8832483          DOI: 10.1016/j.neurobiolaging.2021.10.007

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  46 in total

1.  A fast diffeomorphic image registration algorithm.

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Authors:  Maria Ly; Gary Z Yu; Helmet T Karim; Nishita R Muppidi; Akiko Mizuno; William E Klunk; Howard J Aizenstein
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4.  Estimating the age of healthy subjects from T1-weighted MRI scans using kernel methods: exploring the influence of various parameters.

Authors:  Katja Franke; Gabriel Ziegler; Stefan Klöppel; Christian Gaser
Journal:  Neuroimage       Date:  2010-01-11       Impact factor: 6.556

Review 5.  The hallmarks of aging.

Authors:  Carlos López-Otín; Maria A Blasco; Linda Partridge; Manuel Serrano; Guido Kroemer
Journal:  Cell       Date:  2013-06-06       Impact factor: 41.582

6.  Increased brain-predicted aging in treated HIV disease.

Authors:  James H Cole; Jonathan Underwood; Matthan W A Caan; Davide De Francesco; Rosan A van Zoest; Robert Leech; Ferdinand W N M Wit; Peter Portegies; Gert J Geurtsen; Ben A Schmand; Maarten F Schim van der Loeff; Claudio Franceschi; Caroline A Sabin; Charles B L M Majoie; Alan Winston; Peter Reiss; David J Sharp
Journal:  Neurology       Date:  2017-03-03       Impact factor: 9.910

Review 7.  Ten simple rules for predictive modeling of individual differences in neuroimaging.

Authors:  Dustin Scheinost; Stephanie Noble; Corey Horien; Abigail S Greene; Evelyn Mr Lake; Mehraveh Salehi; Siyuan Gao; Xilin Shen; David O'Connor; Daniel S Barron; Sarah W Yip; Monica D Rosenberg; R Todd Constable
Journal:  Neuroimage       Date:  2019-03-01       Impact factor: 6.556

8.  Signatures of white-matter microstructure degradation during aging and its association with cognitive status.

Authors:  Ana Coelho; Henrique M Fernandes; Ricardo Magalhães; Pedro Silva Moreira; Paulo Marques; José M Soares; Liliana Amorim; Carlos Portugal-Nunes; Teresa Castanho; Nadine Correia Santos; Nuno Sousa
Journal:  Sci Rep       Date:  2021-02-25       Impact factor: 4.379

9.  Brain volumetric changes and cognitive ageing during the eighth decade of life.

Authors:  Stuart J Ritchie; David Alexander Dickie; Simon R Cox; Maria Del C Valdes Hernandez; Janie Corley; Natalie A Royle; Alison Pattie; Benjamin S Aribisala; Paul Redmond; Susana Muñoz Maniega; Adele M Taylor; Ruth Sibbett; Alan J Gow; John M Starr; Mark E Bastin; Joanna M Wardlaw; Ian J Deary
Journal:  Hum Brain Mapp       Date:  2015-09-07       Impact factor: 5.038

10.  Normative Data for the Symbol Digit Modalities Test in Older White Australians and Americans, African-Americans, and Hispanic/Latinos.

Authors:  Joanne Ryan; Robyn L Woods; Carlene J Britt; Anne M Murray; Raj C Shah; Christopher M Reid; Rory Wolfe; Mark R Nelson; Suzanne G Orchard; Jessica E Lockery; Ruth E Trevaks; Elsdon Storey
Journal:  J Alzheimers Dis Rep       Date:  2020-08-04
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  1 in total

1.  Factors Influencing Change in Brain-Predicted Age Difference in a Cohort of Healthy Older Individuals.

Authors:  Jo Wrigglesworth; Ian H Harding; Phillip Ward; Robyn L Woods; Elsdon Storey; Bernadette Fitzgibbon; Gary Egan; Anne Murray; Raj C Shah; Ruth E Trevaks; Stephanie Ward; John J McNeil; Joanne Ryan
Journal:  J Alzheimers Dis Rep       Date:  2022-04-04
  1 in total

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