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Deep neural networks and genome-wide associations reveal the polygenic architecture of local brain aging
Nicholas J. Kim, Ayati Mishra, Nahian F. Chowdhury, Samuel D. Anderson, Owen M. Vega, Nikhil N. Chaudhari, Kenneth H. Buetow, Paul M. Thompson et al.. GeroScience, 2025-12-11
Topic: Risk, prevention and care in population studies
Plain-language summary
-weighted magnetic resonance images of 41,708 cognitively normal adults in the UK Biobank. We identified 1,212 single-nucleotide polymorphisms (SNPs) significantly associated with LBA in at least one brain region. Genes mapped to these SNPs are involved in developmental, metabolic, immune, and cytoskeletal pathways. Dimensionality reduction of SNP association profiles uncovered three clusters linked to morphogenetic, cytoskeletal, and immuno-epigenetic processes, helping to relate neuroanatomic, immunosenescent and epigenetic mechanisms of brain aging. Top variants are mapped to KCNK2, NUAK1, GMNC, MSL2, and to other genes implicated in neurodevelopment and neurodegeneration. Spatial clustering of LBA-associated variants in default mode, limbic, and motor network regions parallel regional vulnerability to Alzheimer's disease and frontotemporal dementia. These findings establish a polygenic architecture for regional brain aging and support LBA as a genetically informed phenotype for studying aging-related neurodegeneration. Our results suggest that cortical aging is not governed by isolated loci but by coordinated genetic programs-rooted in development, metabolism, and cellular structure-that confer lifelong patterns of regional brain vulnerability and resilience. This first genetic dissection of spatially specific brain aging reveals a polygenic landscape of coordinated genetic programs, developmentally encoded and metabolically maintained during senescence. This study reframes aging as an anatomically specific genetic process reflecting the varying structural vulnerabilities observed across neurodegenerative diseases.
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APA 7th
Kim, N. J., Mishra, A., Chowdhury, N. F., Anderson, S. D., Vega, O. M., Chaudhari, N. N., et al. (2025). Deep neural networks and genome-wide associations reveal the polygenic architecture of local brain aging. GeroScience. https://doi.org/10.1007/s11357-025-02046-1
Vancouver
Kim NJ, Mishra A, Chowdhury NF, Anderson SD, Vega OM, Chaudhari NN, et al. Deep neural networks and genome-wide associations reveal the polygenic architecture of local brain aging. GeroScience. 2025. doi:10.1007/s11357-025-02046-1. PMID: 41381974.
BibTeX
@article{kim2025-41381974,
author = {Kim, Nicholas J. and Mishra, Ayati and Chowdhury, Nahian F. and Anderson, Samuel D. and Vega, Owen M. and Chaudhari, Nikhil N. and Buetow, Kenneth H. and Thompson, Paul M. and others},
title = {{Deep neural networks and genome-wide associations reveal the polygenic architecture of local brain aging}},
journal = {GeroScience},
year = {2025},
doi = {10.1007/s11357-025-02046-1},
pmid = {41381974},
url = {https://doi.org/10.1007/s11357-025-02046-1}
}
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Key findings
- We identified 1,212 single-nucleotide polymorphisms (SNPs) significantly associated with LBA in at least one brain region.
- These findings establish a polygenic architecture for regional brain aging and support LBA as a genetically informed phenotype for studying aging-related neurodegeneration.
- Our results suggest that cortical aging is not governed by isolated loci but by coordinated genetic programs-rooted in development, metabolism, and cellular structure-that confer lifelong patterns of regional brain vulnerability and resilience.
Why it matters
This genetic analysis of 41,708 cognitively normal adults identified 1,212 single-nucleotide polymorphisms associated with local brain aging and mapped top variants to genes including KCNK2, NUAK1, GMNC, and MSL2. The findings establish a polygenic architecture for regional brain aging and suggest local brain aging as a phenotype for studying neurodegeneration, but they do not test any treatment, cure, or prevention.
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Study details
- Evidence strengthLow
How this study scored 37/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomized / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (GeroScience) |
| Journal's citation record | 1 / 4 | GeroScience: journal h-index 83 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomized / blinded | 0 / 2 | No randomization or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 3 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.0 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 2 / 6 | Cited 1.7× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 3 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Andrei Irimia: h-index 38 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | University of Southern California: institution h-index 1,521 (OpenAlex) |
| Multicenter collaboration | 1 / 3 | OpenAlex lists 3 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41381974) |
| Free to read | 2 / 2 | Free to read |
| Total | 37 / 100 | — |
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