Heritability of Regional Brain Volumes in Large-Scale Neuroimaging and Genetic Studies

Author:

Zhao Bingxin1,Ibrahim Joseph G12,Li Yun134,Li Tengfei5,Wang Yue1,Shan Yue1,Zhu Ziliang1,Zhou Fan1,Zhang Jingwen1,Huang Chao1,Liao Huiling6,Yang Liuqing2,Thompson Paul M7,Zhu Hongtu15

Affiliation:

1. Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

2. Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

3. Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

4. Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

5. Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA

6. Department of Statistics, Texas A&M University, College Station, TX, USA

7. Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA

Abstract

Abstract Brain genetics is an active research area. The degree to which genetic variants impact variations in brain structure and function remains largely unknown. We examined the heritability of regional brain volumes (P ~ 100) captured by single-nucleotide polymorphisms (SNPs) in UK Biobank (n ~ 9000). We found that regional brain volumes are highly heritable in this study population and common genetic variants can explain up to 80% of their variabilities (median heritability 34.8%). We observed omnigenic impact across the genome and examined the enrichment of SNPs in active chromatin regions. Principal components derived from regional volume data are also highly heritable, but the amount of variance in brain volume explained by the component did not seem to be related to its heritability. Heritability estimates vary substantially across large-scale functional networks, exhibit a symmetric pattern across left and right hemispheres, and are consistent in females and males (correlation = 0.638). We repeated the main analysis in Alzheimer’s Disease Neuroimaging Initiative (n ~ 1100), Philadelphia Neurodevelopmental Cohort (n ~ 600), and Pediatric Imaging, Neurocognition, and Genetics (n ~ 500) datasets, which demonstrated that more stable estimates can be obtained from the UK Biobank.

Funder

National Institutes of Health

National Science Foundation

Cancer Prevention Research Institute of Texas

endowed Bao-Shan Jing Professorship in Diagnostic Imaging

Publisher

Oxford University Press (OUP)

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience

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