Evidence map›Paper›PMID 42679042›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

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

Huisheng Zhu, Yuval B Simons, Jeffrey P Spence, Guy Sella, Jonathan K Pritchard

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Huisheng ZhuDepartment of Biology, Stanford University, Stanford, CA 94305.ORCID 0009-0003-0639-7002
Yuval B SimonsDepartment of Genetics, Stanford University, Stanford, CA 94305.ORCID 0000-0002-0037-4673
Jeffrey P SpenceDepartment of Genetics, Stanford University, Stanford, CA 94305.
Guy SellaDepartment of Biological Sciences, Columbia University, New York City, NY 10027.
Jonathan K PritchardDepartment of Biology, Stanford University, Stanford, CA 94305.

Funding

Integration of genetic association mapping and functional data to elucidate genetic mechanisms of diseaseR01HG008140 · NHGRI · STANFORD UNIVERSITY · PI JONATHAN K PRITCHARD · 2016 to 2026
$7.3M
The population genetics of disease risk and other quantitative traitsR01GM115889 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI SELLA, GUY · 2015 to 2025
$2.9M
Genetic ancestry effects on molecular and complex traits in TOPMedR01HL175076 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Ryan D. Hernandez, Dara Torgerson · 2025 to 2026
$1.6M
Bayesian estimation of gene effects on traits from coding variantsR01HG014005 · NHGRI · STANFORD UNIVERSITY · PI JONATHAN K PRITCHARD · 2025 to 2026
$1.3M
HHS | National Institutes of Health (NIH) R01GM115889HHS | National Institutes of Health (NIH) R01HG008140HHS | National Institutes of Health (NIH) R01HG014005HHS | National Institutes of Health (NIH) R01HL175076National Science Foundation (NSF) DMS-2235451NHGRI NIH HHS R01 HG008140NHGRI NIH HHS R01 HG014005NHLBI NIH HHS R01 HL175076NIGMS NIH HHS R01 GM115889Simons Foundation (SF) MPS-NITMB-00005320
6 · The paper itself

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.

Indexed as

BrainMental DisordersSelection, GeneticGene FrequencyGenome-Wide Association StudyHumansModels, GeneticPhenotypePolymorphism, Single NucleotideQuantitative Trait Locibrain-related traitsgenetic architectureGWASpsychiatric disordersselection

Identifiers

PMID42679042
PMCPMC13552918

What Socratic holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.