作者
Aaron Z Wagen, William Coath, Ashvini Keshavan, Sarah-Naomi James, Thomas D Parker, Christopher A Lane, Sarah M Buchanan, Sarah E Keuss, Mathew Storey, Kirsty Lu, Amy Macdougall, Heidi Murray-Smith, Tamar Freiberger, David M Cash, Ian B Malone, Josephine Barnes, Carole H Sudre, Andrew Wong, Ivanna M Pavisic, Rebecca Street, Sebastian J Crutch, Valentina Escott-Price, Ganna Leonenko, Henrik Zetterberg, Henrietta Wellington, Amanda Heslegrave, Frederik Barkhof, Marcus Richards, Nick C Fox, James H Cole, Jonathan M Schott
发表日期
2022/9/1
期刊
The Lancet Healthy Longevity
卷号
3
期号
9
页码范围
e607-e616
出版商
Elsevier
简介
Background
A neuroimaging-based biomarker termed the brain age is thought to reflect variability in the brain's ageing process and predict longevity. Using Insight 46, a unique narrow-age birth cohort, we aimed to examine potential drivers and correlates of brain age.
Methods
Participants, born in a single week in 1946 in mainland Britain, have had 24 prospective waves of data collection to date, including MRI and amyloid PET imaging at approximately 70 years old. Using MRI data from a previously defined selection of this cohort, we derived brain-predicted age from an established machine-learning model (trained on 2001 healthy adults aged 18–90 years); subtracting this from chronological age (at time of assessment) gave the brain-predicted age difference (brain-PAD). We tested associations with data from early life, midlife, and late life, as well as rates of MRI-derived brain atrophy.
Findings
Between May 28 …
学术搜索中的文章
AZ Wagen, W Coath, A Keshavan, SN James… - The Lancet Healthy Longevity, 2022