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Population clustering of structural brain aging and its association with brain development.

ABSTRACT: Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the "last in, first out" mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

SUBMITTER: Duan H

PROVIDER: S-EPMC10802651 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Population clustering of structural brain aging and its association with brain development.

Duan Haojing H Shi Runye R Kang Jujiao J Banaschewski Tobias T Bokde Arun L W ALW Büchel Christian C Desrivières Sylvane S Flor Herta H Grigis Antoine A Garavan Hugh H Gowland Penny A PA Heinz Andreas A Brühl Rüdiger R Martinot Jean-Luc JL Martinot Marie-Laure Paillère MP Artiges Eric E Nees Frauke F Papadopoulos Orfanos Dimitri D Poustka Luise L Hohmann Sarah S Holz Nathalie N Fröhner Juliane H JH Smolka Michael N MN Vaidya Nilakshi N Walter Henrik H Whelan Robert R Whelan Robert R Schumann Gunter G Lin Xiaolei X Feng Jianfeng J

medRxiv : the preprint server for health sciences 20240626

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 hea ...[more]

PMID: 38260410

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Project description:PurposeOne of the central features of brain aging is the accumulation of multiple age-related structural changes, which occur heterogeneously in individuals and can have immediate or potential clinical consequences. Each of these deficits can coexist and interact, producing both independent and additive impacts on brain health. Many of the changes can be visualized using MRI. To collectively assess whole-brain structural changes, the MRI-based Brain Atrophy and Lesion Index (BALI) has been developed. In this study, we validate this whole-brain health assessment approach using several clinical MRI examinations.Materials and methodsData came from three independent studies: the Alzheimer's Disease Neuroimaging Initiative Phase II (n=950; women =47.9%; age =72.7±7.4 years); the National Alzheimer's Coordinating Center (n=722; women =55.1%; age =72.7±9.9 years); and the Tianjin Medical University General Hospital Research database on older adults (n=170; women =60.0%; age =62.9±9.3 years). The 3.0-Tesla MRI scans were evaluated using the BALI rating scheme on the basis of T1-weighted (T1WI), T2-weighted (T2WI), T2-weighted fluid-attenuated inversion recovery (T2-FLAIR), and T2*-weighted gradient-recalled echo (T2*GRE) images.ResultsAtrophy and lesion changes were commonly seen in each MRI test. The BALI scores based on different sequences were highly correlated (Spearman r2>0.69; P<0.00001). They were associated with age (r2>0.29; P<0.00001) and differed by cognitive status (χ2>26.48, P<0.00001). T2-FLAIR revealed a greater level of periventricular (χ2=29.09) and deep white matter (χ2=26.65, P<0.001) lesions than others, but missed revealing certain dilated perivascular spaces that were seen in T2WI (P<0.001). Microhemorrhages occurred in 15.3% of the sample examined and were detected using only T2*GRE.ConclusionThe T1WI- and T2WI-based BALI evaluations consistently identified the burden of aging and dementia-related decline of structural brain health. Inclusion of additional MRI tests increased lesion differentiation. Further research is to integrate MRI tests for a clinical tool to aid the diagnosis and intervention of brain aging.

Dataset Information

Population clustering of structural brain aging and its association with brain development.

Publications

Population clustering of structural brain aging and its association with brain development.

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