Heritability of Regional Brain Volumes in Large-Scale Neuroimaging and Genetic Studies
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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.
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Given the heritability of brain structure and function, family structure should be specifically accounted for in analysis pipelines.
“Given the heritability of brain structure and function32–34, family structure should be specifically accounted for in analysis pipelines, such as in permutation tests65.”
From Data leakage inflates prediction performance in connectome-based machine learning models (2024) · cites this paper as [34]
The Abstract reports that regional brain volumes are highly heritable in the study population, supporting the brain-structure part of the cited premise. The paper groups those volume measures into functional networks, but does not establish the heritability of brain function itself. The recommendation about accounting for family structure is attached to a different citation in the citing sentence. (LLM, conf=0.85)
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Zhao, B., Luo, T., Li, T., Li, Y., Zhang, J., Shan, Y., Wang, X., Yang, L., Zhou, F., Zhu, Z., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0516-6 · Cited by 295 · see citing works
Self-citationData leakage inflates prediction performance in connectome-based machine learning models
Rosenblatt, M., Tejavibulya, L., Jiang, R., Noble, S., & Scheinost, D. (2024) · Nature Communications · doi:10.1038/s41467-024-46150-w · Cited by 236 · see citing works
- Authors
- Zhao, B., Ibrahim, J. G., Li, Y., Li, T., Wang, Y., Shan, Y., Zhu, Z., Zhou, F., Zhang, J., Huang, C., Liao, H., Yang, L., Thompson, P. M., & Zhu, H.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- The University of Texas MD Anderson Cancer Center (US)
- Texas A&M University (US)
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- ORCID
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-07-12
- Volume
- 29
- Issue
- 7
- Pages
- 2904-2914
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- PMC
- PMC6611460
- OpenAlex
- W2952810115
- Cited by
- 58
- References
- 59
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 9 · 2023: 9 · 2022: 11 · 2021: 6 · 2020: 4 · 2019: 3 · 2018: 2
- FWCI
- 2.30
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Cerebral Cortex (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- National Institutes of Health (MH086633, MH092335)
- National Science Foundation (1357666, 1407655)
- Cancer Prevention Research Institute of Texas
- endowed Bao-Shan Jing Professorship in Diagnostic Imaging
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- heritability, regional brain volume, brain structure genetics, single nucleotide polymorphisms, functional brain networks, hemispheric lateralization, sex differences, UK Biobank, Alzheimer's Disease Neuroimaging Initiative, Philadelphia Neurodevelopmental Cohort
- MeSH terms
- Brain, Female, Humans, Male, Organ Size, Polymorphism, Single Nucleotide, Neuroimaging, Datasets as Topic
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