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

• Published in: Nature communications Vol. 15; no. 1; pp. 2655 - 13
• Main Authors: Tissink, E. P., Shadrin, A. A., van der Meer, D., Parker, N., Hindley, G., Roelfs, D., Frei, O., Fan, C. C., Nagel, M., Nærland, T., Budisteanu, M., Djurovic, S., Westlye, L. T., van den Heuvel, M. P., Posthuma, D., Kaufmann, T., Dale, A. M., Andreassen, O. A.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 26.03.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 45/61; 59/36; 59/57; 631/208/205/2138; 631/378/2583; Biological activity; Brain; Brain - anatomy & histology; Composition; Functional magnetic resonance imaging; Genes; Genetic diversity; Genetic Pleiotropy; Genetic Predisposition to Disease; Genome-wide association studies; Genome-Wide Association Study - methods; Genomes; Humanities and Social Sciences; Humans; Macrostructure; Magnetic resonance imaging; Medical imaging; Mental disorders; multidisciplinary; Multivariate analysis; Neural networks; Neuroimaging; Phenotype; Phenotypes; Pleiotropy; Polymorphism, Single Nucleotide; Science; Science (multidisciplinary); Statistical tests; Structure-function relationships
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-024-46817-4

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. The authors uncover extensive genetic overlap across brain structure, functional connectivity, and brain tissue composition using multivariate methods. Insights gained enhance understanding of brain biology and prediction of psychiatric conditions.