Genome-wide association studies of brain imaging phenotypes in UK Biobank
Open accessAbstract
The genetic architecture of brain structure and function is largely unknown. To investigate this, we carried out genome-wide association studies of 3,144 functional and structural brain imaging phenotypes from UK Biobank (discovery dataset 8,428 subjects). Here we show that many of these phenotypes are heritable. We identify 148 clusters of associations between single nucleotide polymorphisms and imaging phenotypes that replicate at P < 0.05, when we would expect 21 to replicate by chance. Notable significant, interpretable associations include: iron transport and storage genes, related to magnetic susceptibility of subcortical brain tissue; extracellular matrix and epidermal growth factor genes, associated with white matter micro-structure and lesions; genes that regulate mid-line axon development, associated with organization of the pontine crossing tract; and overall 17 genes involved in development, pathway signalling and plasticity. Our results provide insights into the genetic architecture of the brain that are relevant to neurological and psychiatric disorders, brain development and ageing.
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Genetic factors contributed moderately significantly to brain cortical area including the ROI superior temporal area (h2 = 0.261, 95% CI 0.220-0.301).
“genetic factors contributed moderately significantly to brain cortical area (also measured in FreeSurfer.aparc.2009s atlas) (Elliott et al., 2018) including the ROI superior temporal area ( h 2 : 0.261, 95% CI 0.220 -0.301)”
From Early-Initiated Childhood Reading for Pleasure: Associations with Better Cognitive Performance, Mental Well-being and Brain Structure in Young Adolescence (2024) · cites this paper as Elliott et al., 2018
The Methods section (page unavailable) says the study measured cortical parcel area using FreeSurfer’s a2009s atlas, and ‘Heritability and genetic correlations of IDPs’ reports significant SNP-heritability for many imaging phenotypes. Our copy does not substantiate the specific superior temporal area estimate of h² = 0.261 or its 95% confidence interval of 0.220–0.301. (LLM, conf=0.85)
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“…approaches, genetic factors contributed moderately significantly to brain cortical area (also measured in FreeSurfer.aparc.2009s atlas) (Elliott et al., 2018) including the ROI superior temporal area ( h 2 : 0.261, 95% CI 0.220 – 0.301), revealing the significant roles of environmental…”
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“The confound set included variables for head size, brain position within the scanner, age, sex and imaging site 38 , as well as 20 population genetic principal components (see Table S9 in Supplementary Tables).”
- Authors
- Elliott, L. T., Sharp, K., Alfaro-Almagro, F., Shi, S., Miller, K. L., Douaud, G., Marchini, J., & Smith, S. M.
- Affiliations
- University of Oxford (GB)
- Centre for Human Genetics (GB)
- Corresponding author
- Marchini, Jonathan
- Smith, Stephen M.
- ORCID
- Venue
- Nature
- Published
- 2018-10-10
- Volume
- 562
- Issue
- 7726
- Pages
- 210-216
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6786974
- OpenAlex
- W2895693082
- Cited by
- 834
- References
- 11
- Citations by year
- 2026: 95 · 2025: 123 · 2024: 135 · 2023: 113 · 2022: 88 · 2021: 100 · 2020: 90 · 2019: 77 · 2018: 10 · 2017: 1
- FWCI
- 42.38
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Explorer (The University of Manchester) (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Wellcome Trust (202788/Z/16/Z)
- University of Oxford
- Medical Research Council (MR/K02213X/1, MC_PC_17228, MR/K006673/1)
- Engineering and Physical Sciences Research Council (EP/J005444/1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Neurology › Cerebrovascular and genetic disorders
- Keywords
- brain imaging phenotypes, heritability, single nucleotide polymorphisms, brain structure, brain function, iron transport genes, magnetic susceptibility, white matter microstructure, extracellular matrix genes, epidermal growth factor, brain development, brain aging, neuroimaging genetics
- MeSH terms
- Aging, Brain, Epidermal Growth Factor, Extracellular Matrix, Female, United Kingdom, Humans, Iron, Male, Neuronal Plasticity, Phenotype, Putamen, Signal Transduction, Biological Specimen Banks, Polymorphism, Single Nucleotide, Heredity, Genome-Wide Association Study, Neuroimaging, White Matter, Datasets as Topic
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