Language

English

Publication Date

11-28-2025

Journal

Nature Communications

DOI

10.1038/s41467-025-65818-5

PMID

41315269

PMCID

PMC12663470

PubMedCentral® Posted Date

11-28-2025

PubMedCentral® Full Text Version

Post-print

Abstract

Genetic variants influencing gene expression have been extensively studied at the transcriptional level. How these variants affect downstream processes remains unclear. We quantitated ribosome occupancy in prefrontal cortex samples from the BrainGVEX cohort and integrated these data with transcriptomic and proteomic profiles from the same individuals. Through cis-QTL mapping, we identified genetic variants associated with transcript level (eQTLs), ribosome occupancy (rQTLs), and protein level (pQTLs). Notably, only 34% of eQTLs have their effects propagated to the protein levels, suggesting widespread post-transcriptional attenuation. Using both a gene-based approach and a variant-based approach we identified omics-specific QTLs that associated with brain disorder GWAS signals and found the majority of them to be driven predominantly by transcriptional regulation. Consistently, using a TWAS approach, we identified 74 SCZ risk genes across the three omics layers, 52 were discovered using transcriptome with 68% showing limited impact on protein expression. Our findings indicated that many disease-associated variants act through regulatory mechanisms that do not lead to an observable impact on the protein level.

Keywords

Schizophrenia, Humans, Quantitative Trait Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Transcriptome, Brain, Ribosomes, Male, Prefrontal Cortex, Female, Polymorphism, Single Nucleotide, Proteomics, Gene Expression Regulation, Gene regulation, Quantitative trait, Gene expression

Published Open-Access

yes

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