The genetic architecture of multimodal human brain age

Junhao Wen; Bingxin Zhao; Zhijian Yang; Guray Erus; Ioanna Skampardoni; Elizabeth Mamourian; Yuhan Cui; Gyujoon Hwang; Jingxuan Bao; Aleix Boquet-Pujadas; Zhen Zhou; Yogasudha Veturi; Marylyn D Ritchie; Haochang Shou; Paul M Thompson; Li Shen; Arthur W Toga; Christos Davatzikos

doi:10.1038/s41467-024-46796-6

The genetic architecture of multimodal human brain age

Nat Commun. 2024 Mar 23;15(1):2604. doi: 10.1038/s41467-024-46796-6.

Authors

Junhao Wen¹, Bingxin Zhao², Zhijian Yang³, Guray Erus³, Ioanna Skampardoni³, Elizabeth Mamourian³, Yuhan Cui³, Gyujoon Hwang³, Jingxuan Bao⁴, Aleix Boquet-Pujadas⁵, Zhen Zhou³, Yogasudha Veturi⁶, Marylyn D Ritchie⁷, Haochang Shou³, Paul M Thompson⁸, Li Shen⁴, Arthur W Toga⁹, Christos Davatzikos³

Affiliations

¹ Laboratory of AI and Biomedical Science (LABS), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA. junhaowe@usc.edu.
² Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, USA.
³ Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
⁴ Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
⁵ Biomedical Imaging Group, EPFL, Lausanne, Switzerland.
⁶ Department of Biobehavioral Health and Statistics, Penn State University, University Park, PA, USA.
⁷ Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
⁸ Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA.
⁹ Laboratory of Neuro Imaging (LONI), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.

Abstract

The complex biological mechanisms underlying human brain aging remain incompletely understood. This study investigated the genetic architecture of three brain age gaps (BAG) derived from gray matter volume (GM-BAG), white matter microstructure (WM-BAG), and functional connectivity (FC-BAG). We identified sixteen genomic loci that reached genome-wide significance (P-value < 5×10^-8). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative and neuropsychiatric disorders and WM-BAG genes for cancer therapy. GM-BAG displayed the most pronounced heritability enrichment in genetic variants within conserved regions. Oligodendrocytes and astrocytes, but not neurons, exhibited notable heritability enrichment in WM and FC-BAG, respectively. Mendelian randomization identified potential causal effects of several chronic diseases on brain aging, such as type 2 diabetes on GM-BAG and AD on WM-BAG. Our results provide insights into the genetics of human brain aging, with clinical implications for potential lifestyle and therapeutic interventions. All results are publicly available at https://labs.loni.usc.edu/medicine .

MeSH terms

Brain
Diabetes Mellitus, Type 2*
Gray Matter
Humans
Magnetic Resonance Imaging / methods
Mendelian Randomization Analysis
White Matter* / physiology

Grants and funding

RF1 AG054409/AG/NIA NIH HHS/United States