| Title: | Genome-wide analysis of subcortical aging identifies a spatially structured pattern of genetic associations |
| Journal: | GeroScience |
| Published: | 1 Aug 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42541656/ |
| DOI: | https://doi.org/10.1007/s11357-026-02453-y |
| URL: | https://link.springer.com/content/pdf/10.1007/s11357-026-02453-y.pdf |
Publication 21248
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Abstract
Local brain age (LBA) is a spatially resolved biomarker of brain aging that captures regional deviations from chronological age, yet its genetic architecture in the subcortex remains unexplored. Here, we present the first genome-wide association study (GWAS) of subcortical LBA, estimated using a deep neural network applied to T1-weighted MRI scans from 41,957 cognitively normal participants in the UK Biobank. We computed LBA across 14 subcortical structures and identified 14 significant single-nucleotide polymorphisms (SNPs) across nine independent loci. These variants map to genes involved in cellular homeostasis, gene regulation, and synaptic and developmental signaling. A prominent signal emerged at the 17q21.31 haplotype, encompassing MAPT-related regulatory architecture, with significant associations across all subcortical regions. Across loci, we observed a recurring spatial pattern in which effect sizes are relatively larger in metabolically central structures such as the pallidum and thalamus compared to limbic regions. Together, these findings support a spatially structured pattern of genetic associations in subcortical brain aging. This work supports subcortical LBA as a genetically informed phenotype and provides a framework for linking common genetic variation to region-specific vulnerability and resilience in neurodegenerative disease.</p>
7 Authors
- Nicholas J. Kim
- Ayati Mishra
- Jeremy S. Yu
- Owen M. Vega
- Nikhil N. Chaudhari
- Fangyun C. Liu
- Andrei Irimia
1 Application
| Application ID | Title |
|---|---|
| 47656 | Mild traumatic brain injury, neurodegenerative disease and genetics in humans |
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