Making the MOSTest of imaging genetics
By
Dennis van der Meer,
Oleksandr Frei,
Tobias Kaufmann,
Alexey A Shadrin,
Anna Devor,
Olav B Smeland,
Wes Thompson,
Chun Chieh Fan,
Dominic Holland,
Lars T. Westlye,
Ole Andreassen,
Anders M Dale
Posted 14 Sep 2019
bioRxiv DOI: 10.1101/767905
(published DOI: 10.1038/s41467-020-17368-1)
Regional brain morphology has a complex genetic architecture, consisting of many common polymorphisms with small individual effects, which has proven challenging for genome-wide association studies to date, despite its high heritability[1][1],[2][2]. Given the distributed nature of the genetic signal across brain regions, joint analysis of regional morphology measures in a multivariate statistical framework provides a way to enhance discovery of genetic variants with current sample sizes. While several multivariate approaches to GWAS have been put forward over the past years[3][3]–[5][4], none are optimally suited for complex, large-scale data. Here, we applied the Multivariate Omnibus Statistical Test (MOSTest), with an efficient computational design enabling rapid and reliable permutation-based inference, to 171 subcortical and cortical brain morphology measures from 26,502 participants of the UK Biobank (mean age 55.5 years, 52.0% female). At the conventional genome-wide significance threshold of α=5×10−8, MOSTest identifies 347 genetic loci associated with regional brain morphology, more than any previous study, improving upon the discovery of established GWAS approaches more than threefold. Our findings implicate more than 5% of all protein-coding genes and provide evidence for gene sets involved in neuron development and differentiation. As such, MOSTest, which we have made publicly available, enhances our understanding of the genetic determinants of regional brain morphology. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-5
Download data
- Downloaded 686 times
- Download rankings, all-time:
- Site-wide: 35,479
- In neuroscience: 4,942
- Year to date:
- Site-wide: 76,388
- Since beginning of last month:
- Site-wide: 78,933
Altmetric data
Downloads over time
Distribution of downloads per paper, site-wide
PanLingua
News
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!