2019
DOI: 10.1101/652867
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Abstract: Brain-predicted age difference scores are calculated by subtracting chronological age from 'brain' age. Positive scores reflect accelerated ageing and are associated with increased mortality risk and poorer physical function. To date, however, the relationship between brainpredicted age difference scores and specific cognitive functions has not been systematically examined. First, applying machine learning to 1,359 T1-weighted MRI scans, we predicted the relationship between chronological age and voxel-wise gr… Show more

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Cited by 8 publications
(12 citation statements)
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“…Moreover, premorbid IQ was related to CAG independent of BAG, in line with established literature highlighting IQ as a potential proxy for cognitive reserve (Anthony & Lin, 2018). Our results are, however, in contradiction with other studies showing consistent links between BAG and cognitive performance (e.g., Boyle et al, 2020; Cole et al, 2018; Elliott et al, 2019). This discrepancy could potentially be attributed to disparities between the cognitive tests administered, or differences in sample characteristics.…”
Section: Discussioncontrasting
confidence: 99%
See 1 more Smart Citation
“…Moreover, premorbid IQ was related to CAG independent of BAG, in line with established literature highlighting IQ as a potential proxy for cognitive reserve (Anthony & Lin, 2018). Our results are, however, in contradiction with other studies showing consistent links between BAG and cognitive performance (e.g., Boyle et al, 2020; Cole et al, 2018; Elliott et al, 2019). This discrepancy could potentially be attributed to disparities between the cognitive tests administered, or differences in sample characteristics.…”
Section: Discussioncontrasting
confidence: 99%
“…The application of machine learning to neuroimaging data has provided an avenue for estimating the apparent age of an individual's brain, and determining deviations from normative brain aging patterns (Cole, Marioni, Harris, & Deary, 2019). Studies in this area suggest that the difference between estimated “brain age” and chronological age (i.e., brain age gap [BAG]) varies between individuals, with positive BAG values (older brain age relative to chronological age) relating to poorer cognitive function (Boyle et al, 2020; Cole et al, 2018; Elliott et al, 2019). A recent multicohort study of 45,615 individuals further highlighted that BAG may be a sensitive marker of disease, with accelerated brain aging observed in a range of conditions including mild cognitive impairments, Alzheimer's disease, and depression (Kaufmann et al, 2019).…”
Section: Introductionmentioning
confidence: 99%
“…Contrary to our hypothesis, after corrections for multiple comparisons, linear models revealed no significant associations between BAGR and summary scores from the baseline assessment or performance gain. In line with a few previous studies (Boyle et al 2019;Høgestøl et al 2019b), region specific models revealed putative associations between summary scores for executive control and speed, working memory and the right cingulate BAGR, as well as, attentional control and speed and the right temporal BAGR, suggesting better cognitive performance with lower BAGR. In addition, region specific analysis revealed non-significant putative associations between performance gain and left frontal and left parietal BAGR, indicating more positive treatment response for patients with lower BAGR.…”
Section: Discussionsupporting
confidence: 89%
“…Briefly, combining a wide array of informative brain imaging features in a prediction model allows for an accurate prediction of the age of an unseen individual (Franke et al 2012;Franke et al 2010). The degree to which the model under-or over-estimate the individual's age has been shown to be sensitive to a variety of health-related characteristics, including cognitive function and mortality (Boyle et al 2019;Cole & Franke 2017;Cole et al 2018;Richard et al 2018), and brain age prediction using MRI data has recently been shown to be sensitive both to the clinical manifestation and polygenic risk of various brain disorders (Høgestøl et al 2019a;Kaufmann et al 2018).…”
Section: Introductionmentioning
confidence: 99%
“…In TILDA, a stress/anxiety-preventative and timesaving measure ( 78) was employed such that participants only completed the second half of the NART if they scored greater than 20 on the rst half. A correction procedure was employed whereby scores of 0-11 were retained as full scores, but scores of 12-20 in participants who did not complete the second half were corrected using a conversion table outlined by Beardsall and Brayne (79) (80). Possible scores on the NART, in TILDA, ranged from 0 to 50 and on the AMNART, in CR/RANN, from 0 to 45.…”
Section: Measures: Cr Proxiesmentioning
confidence: 99%