ArticleBiological psychiatry global open science2024
Distinct Longitudinal Brain White Matter Microstructure Changes and Associated Polygenic Risk of Common Psychiatric Disorders and Alzheimer's Disease in the UK Biobank.
Article in Biological psychiatry global open science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- White matter microstructure differences between 15q11.2 copy number variation carriers and non-carriers in mid-to-late life.Translational psychiatry · 2026Article
- Plasma complex lipids in relation to cortical thickness and brain volumes: results from the population-based Rhineland study.Lipids in health and disease · 2026Article
- White matter microstructure changes across the lifespan: a meta-analysis of longitudinal diffusion MRI studies.bioRxiv : the preprint server for biology · 2025Article
- Cross-Sectional Brain Age Assessments Are Limited in Predicting Future Brain Change.Human brain mapping · 2025Article
- Predicting brain age for veterans with traumatic brain injuries and healthy controls: an exploratory analysis.Frontiers in aging neuroscience · 2025Article
- Brain asymmetries from mid- to late life and hemispheric brain age.Nature communications · 2024Article
- Brain patterns linked to neuropsychiatric genetic risk mirror those seen in disease.Imaging neuroscience (Cambridge, Mass.)Article
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Authors and funding
9 authors.
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Abstract
Background: During the course of adulthood and aging, white matter (WM) structure and organization are characterized by slow degradation processes such as demyelination and shrinkage. An acceleration of such aging processes has been linked to the development of a range of diseases. Thus, an accurate description of healthy brain maturation, particularly in terms of WM features, is fundamental to the understanding of aging. Methods: We used longitudinal diffusion magnetic resonance imaging to provide an overview of WM changes at different spatial and temporal scales in the UK Biobank (UKB) ( Results: Our findings indicate spatially distributed WM changes across the brain, as well as distributed associations of polygenic risk scores with WM. Importantly, brain longitudinal changes reflected genetic risk for disorder development better than the utilized cross-sectional measures, with regional differences giving more specific insights into gene-brain change associations than global averages. Conclusions: We extend recent findings by providing a detailed overview of WM microstructure degeneration on different spatial levels, helping to understand fundamental brain aging processes. Further longitudinal research is warranted to examine aging-related gene-brain associations.
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