1
|
Topiwala A, Nichols TE, Williams LZJ, Robinson EC, Alfaro-Almagro F, Taschler B, Wang C, Nelson CP, Miller KL, Codd V, Samani NJ, Smith SM. Telomere length and brain imaging phenotypes in UK Biobank. PLoS One 2023; 18:e0282363. [PMID: 36947528 PMCID: PMC10032499 DOI: 10.1371/journal.pone.0282363] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 02/13/2023] [Indexed: 03/23/2023] Open
Abstract
Telomeres form protective caps at the ends of chromosomes, and their attrition is a marker of biological aging. Short telomeres are associated with an increased risk of neurological and psychiatric disorders including dementia. The mechanism underlying this risk is unclear, and may involve brain structure and function. However, the relationship between telomere length and neuroimaging markers is poorly characterized. Here we show that leucocyte telomere length (LTL) is associated with multi-modal MRI phenotypes in 31,661 UK Biobank participants. Longer LTL is associated with: i) larger global and subcortical grey matter volumes including the hippocampus, ii) lower T1-weighted grey-white tissue contrast in sensory cortices, iii) white-matter microstructure measures in corpus callosum and association fibres, iv) lower volume of white matter hyperintensities, and v) lower basal ganglia iron. Longer LTL was protective against certain related clinical manifestations, namely all-cause dementia (HR 0.93, 95% CI: 0.91-0.96), but not stroke or Parkinson's disease. LTL is associated with multiple MRI endophenotypes of neurodegenerative disease, suggesting a pathway by which longer LTL may confer protective against dementia.
Collapse
Affiliation(s)
- Anya Topiwala
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Thomas E. Nichols
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, Oxford, United Kingdom
| | - Logan Z. J. Williams
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Emma C. Robinson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Fidel Alfaro-Almagro
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Bernd Taschler
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford University, Oxford, United Kingdom
| | - Christopher P. Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Karla L. Miller
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford University, Oxford, United Kingdom
| | - Veryan Codd
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Nilesh J. Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Stephen M. Smith
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford University, Oxford, United Kingdom
| |
Collapse
|