Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study

E. P. Tissink (), A. A. Shadrin, D. 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. Heuvel, D. Posthuma, T. Kaufmann, A. M. Dale and O. A. Andreassen ()
Additional contact information
E. P. Tissink: Amsterdam Neuroscience
A. A. Shadrin: Building 48
D. Meer: Building 48
N. Parker: Building 48
G. Hindley: Building 48
D. Roelfs: Building 48
O. Frei: Building 48
C. C. Fan: Laureate Institute for Brain Research
M. Nagel: Amsterdam Neuroscience
T. Nærland: Building 31
M. Budisteanu: Prof. Dr. Alex Obregia Clinical Hospital of Psychiatry
S. Djurovic: Building 48
L. T. Westlye: Building 48
M. P. Heuvel: Amsterdam Neuroscience
D. Posthuma: Amsterdam Neuroscience
T. Kaufmann: Building 48
A. M. Dale: University of California San Diego
O. A. Andreassen: Building 48

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41467-024-46817-4

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