Life course, genetic, and neuropathological associations with brain age in the 1946 British Birth Cohort: a population-based study

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

doi:10.1016/S2666-7568(22)00167-2

Life course, genetic, and neuropathological associations with brain age in the 1946 British Birth Cohort: a population-based study

Lancet Healthy Longev. 2022 Sep;3(9):e607-e616. doi: 10.1016/S2666-7568(22)00167-2. Epub 2022 Aug 22.

Authors

Aaron Z Wagen¹, William Coath², Ashvini Keshavan², Sarah-Naomi James³, Thomas D Parker⁴, Christopher A Lane², Sarah M Buchanan², Sarah E Keuss², Mathew Storey², Kirsty Lu², Amy Macdougall⁵, Heidi Murray-Smith², Tamar Freiberger², David M Cash⁶, Ian B Malone², Josephine Barnes², Carole H Sudre⁷, Andrew Wong³, Ivanna M Pavisic², Rebecca Street², Sebastian J Crutch², Valentina Escott-Price⁸, Ganna Leonenko⁹, Henrik Zetterberg¹⁰, Henrietta Wellington¹¹, Amanda Heslegrave¹¹, Frederik Barkhof¹², Marcus Richards³, Nick C Fox⁶, James H Cole¹³, Jonathan M Schott¹⁴

Affiliations

¹ Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK; Neurodegeneration Biology Laboratory, The Francis Crick Institute, London, UK.
² Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK.
³ Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK.
⁴ Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Brain Sciences, Imperial College London, London, UK; UK Dementia Research Institute Centre for Care Research and Technology, Imperial College London, London, UK.
⁵ Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK.
⁶ Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK.
⁷ Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK; Department of Computer Science, Centre for Medical Imaging Computing, University College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
⁸ Division of Neuroscience and Mental Health, Cardiff University, Cardiff, UK.
⁹ Dementia Research Institute, Cardiff University, Cardiff, UK.
¹⁰ Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK; Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.
¹¹ Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK; Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK.
¹² Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK; Department of Computer Science, Centre for Medical Imaging Computing, University College London, London, UK; Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Vrije Universiteit, Amsterdam, Netherlands.
¹³ Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Computer Science, Centre for Medical Imaging Computing, University College London, London, UK.
¹⁴ Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK. Electronic address: [email protected].

Abstract

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, 2015, and Jan 10, 2018, 502 individuals were assessed as part of Insight 46. We included 456 participants (225 female), with a mean chronological age of 70·7 years (SD 0·7; range 69·2 to 71·9). The mean brain-predicted age was 67·9 years (8·2, 46·3 to 94·3). Female sex was associated with a 5·4-year (95% CI 4·1 to 6·8) younger brain-PAD than male sex. An increase in brain-PAD was associated with increased cardiovascular risk at age 36 years (β=2·3 [95% CI 1·5 to 3·0]) and 69 years (β=2·6 [1·9 to 3·3]); increased cerebrovascular disease burden (1·9 [1·3 to 2·6]); lower cognitive performance (-1·3 [-2·4 to -0·2]); and increased serum neurofilament light concentration (1·2 [0·6 to 1·9]). Higher brain-PAD was associated with future hippocampal atrophy over the subsequent 2 years (0·003 mL/year [0·000 to 0·006] per 5-year increment in brain-PAD). Early-life factors did not relate to brain-PAD. Combining 12 metrics in a hierarchical partitioning model explained 33% of the variance in brain-PAD.

Interpretation: Brain-PAD was associated with cardiovascular risk, and imaging and biochemical markers of neurodegeneration. These findings support brain-PAD as an integrative summary metric of brain health, reflecting multiple contributions to pathological brain ageing, and which might have prognostic utility.

Funding: Alzheimer's Research UK, Medical Research Council Dementia Platforms UK, Selfridges Group Foundation, Wolfson Foundation, Wellcome Trust, Brain Research UK, Alzheimer's Association.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Aged
Alzheimer Disease* / pathology
Atrophy / pathology
Brain / diagnostic imaging
Female
Humans
Life Change Events*
Male
Prospective Studies

Abstract

Publication types

MeSH terms

Grants and funding