Genetic architectures of brain-related traits are shaped by strong selective constraints.

Overview

1. Department of Biology, Stanford University, Stanford, CA 94305
2. Department of Genetics, Stanford University, Stanford, CA 94305
3. Section of Genetic Medicine, University of Chicago, Chicago, IL 60637
4. Department of Human Genetics, University of Chicago, Chicago, IL 60637
5. Institute for Human Genetics, University of California, San Francisco, CA 94158
6. Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158
7. Department of Biological Sciences, Columbia University, New York City, NY 10027
8. Program for Mathematical Genomics, Columbia University, New York City, NY 10032

Abstract

Genome-wide association studies (GWAS) have identified hundreds of significant loci for psychiatric disorders, yet the strength of these associations remains modest compared to other human complex traits with similar numbers of hits. Whether this pattern reflects statistical artifacts or real biological differences—and, if the latter, what underlies it—remains unclear. In addition to psychiatric disorders, we find that other traits with functional enrichment in the central nervous system (CNS), whether binary or quantitative, also share similar genetic architectures, characterized by GWAS hits of limited statistical significance and generally higher allele frequencies. In comparing the architecture of binary and quantitative traits, we adjust for statistical power in their respective studies. After this adjustment, we fit an evolutionary model of architecture and show that CNS-enriched traits have large mutational target sizes, with contributing variants and genes experiencing stronger selection than those for other traits. Our findings reveal heterogeneity among complex traits and provide insights into traits that more effectively capture fitness-relevant processes. More broadly, our results suggest that the genetic architectures of complex traits are shaped by the tissues through which these traits are mediated.

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Data

Datasets cited

• ukbiobank.ac.uk/use-our-data/apply-for-access, at UK Biobank; found in “Data, Materials, and Software Availability”
• zenodo:19154957, at Zenodo; found in “Data, Materials, and Software Availability”

Data, Materials, and Software Availability

Codes used for this article are available at https://github.com/huishengz/cns-selection. Data and results are available at https://doi.org/10.5281/zenodo.19154957. To access UK Biobank data, eligible researchers can apply at https://www.ukbiobank.ac.uk/use-our-data/apply-for-access/ (99).

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 5 keywords, 10 MeSH terms, 6 funders, 93 references.

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This paper

Zhu, H., Simons, Y. B., Spence, J. P., Sella, G., & Pritchard, J. K. (2026). Genetic architectures of brain-related traits are shaped by strong selective constraints. Proceedings of the National Academy of Sciences of the United States of America, 123(36), e2609814123. https://doi.org/10.1073/pnas.2609814123

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