Genetically supported targets and drug repurposing for brain aging: A systematic study in the UK Biobank

Brain age gap (BAG), the deviation between estimated brain age and chronological age, is a promising marker of brain health. However, the genetic architecture and reliable targets for brain aging remains poorly understood. In this study, we estimate magnetic resonance imaging (MRI)-based brain age using deep learning models trained on the UK Biobank and validated with three external datasets. A genome-wide association study for BAG identified two unreported loci and seven previously reported loci. By integrating Mendelian Randomization (MR) and colocalization analysis on eQTL and pQTL data, we prioritized seven genetically supported druggable genes, including <i>MAPT</i>, <i>TNFSF12</i>, <i>GZMB</i>, <i>SIRPB1</i>, <i>GNLY</i>, <i>NMB</i>, and <i>C1RL</i>, as promising targets for brain aging. We rediscovered 13 potential drugs with evidence from clinical trials of aging and prioritized several drugs with strong genetic support. Our study provides insights into the genetic basis of brain aging, potentially facilitating drug development for brain aging to extend the health span.

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Publication Details

Journal
Science Advances
Published
2025-03-12
DOI
https://doi.org/10.1126/sciadv.adr3757
Citations
22
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
17.73
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article

Genetically supported targets and drug repurposing for brain aging: A systematic study in the UK Biobank

Jing Yuan, Mor Peleg, Zhengxing Huang, Yi‐Cheng Zhu et al.
22 citations
Science Advances
Epigenetics and DNA Methylation
17.73
article

Genetically supported targets and drug repurposing for brain aging: A systematic study in the UK Biobank

Jing Yuan, Mor Peleg, Zhengxing Huang, Yi‐Cheng Zhu, Judith Somekh, Zhilong Jia, Yi Fan, Fei Wu
article en
22 citations

Abstract

Brain age gap (BAG), the deviation between estimated brain age and chronological age, is a promising marker of brain health. However, the genetic architecture and reliable targets for brain aging remains poorly understood. In this study, we estimate magnetic resonance imaging (MRI)-based brain age using deep learning models trained on the UK Biobank and validated with three external datasets. A genome-wide association study for BAG identified two unreported loci and seven previously reported loci. By integrating Mendelian Randomization (MR) and colocalization analysis on eQTL and pQTL data, we prioritized seven genetically supported druggable genes, including <i>MAPT</i>, <i>TNFSF12</i>, <i>GZMB</i>, <i>SIRPB1</i>, <i>GNLY</i>, <i>NMB</i>, and <i>C1RL</i>, as promising targets for brain aging. We rediscovered 13 potential drugs with evidence from clinical trials of aging and prioritized several drugs with strong genetic support. Our study provides insights into the genetic basis of brain aging, potentially facilitating drug development for brain aging to extend the health span.

Science AdvancesVol. 11(11)
Zhejiang University of Science and Technology (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Peking Union Medical College Hospital (CN), Chinese PLA General Hospital (CN), University of Haifa (IL)
Good health and well-being
Openalex Percentile: Top 1%
Epigenetics and DNA Methylation
17.73
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