bioRxivGeneticsPreprint
Colocalization and discordance between plasma and brain protein quantitative trait loci
- Citations
- 0
Abstract
Studies of protein quantitative trait loci (pQTLs) provide opportunities to interpret complex trait genetics and identify potential biomarkers and therapeutic targets. Circulating proteins are commonly used in pQTL studies due to the accessibility of blood-based measurements, but their levels may not always reflect regulation in disease-relevant tissues. We assessed colocalization and discordance between plasma and dorsal prefrontal cortex cis-pQTLs using data from four large-scale studies and investigated their implications for downstream analyses. Across the proteins examined, at most 80% of the cis-pQTLs showed evidence of colocalization. Among the colocalized loci, approximately 20% exhibited opposite directions of genetic effects. We characterized tissue-specific gene expression profiles based on data from the Genotype-Tissue Expression project. Proteins with colocalized cis-pQTLs were more likely to have high gene expression levels in systemic tissues and immune cells, whereas the remaining proteins were more likely to have high expression in brain tissues. We conducted Mendelian randomization (MR) analyses using neuroticism as an illustrative outcome to compare effect estimates derived using instruments from different pQTL studies. MR analyses identified 13 proteins significantly associated with neuroticism, including six with opposite effect directions between plasma and dorsal prefrontal cortex, highlighting the importance of tissue context. Overall, circulating pQTLs remain informative for proteins from systemic and immune pathways, while incorporating tissue-specific data may provide additional insight for proteins with more localized expression. Considering multiple tissue contexts may refine the interpretation of protein-trait associations and may improve the prioritization of candidate targets.
- organism: human
- assay: proteomics
- research focus: GWAS / association mapping
- approach: statistical model
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Genomic and multi-tissue proteomic integration for understanding the biology of disease and other complex traits
Chengran Yang, Fabiana Geraldo Farias, … Carlos Cruchaga·medRxiv·Jun 25, 2020
- Characterizing the impact of plasma protein levels on human brain structure and disorders leveraging integrative multi-omics analysis
Cyrus Ayubcha, Evan Dennis, … Chia‐Yen Chen·medRxiv·Jul 15, 2026
- Multi-Tissue Profiling Reveals tissue-specific protein regulation and relationships Between Protein Quantitative Trait Loci (pQTLs) and Cardiometabolic Disease
April E. Hartley, Katyayani Sukhavasi, … Yalda Jamshidi·bioRxiv·Jun 30, 2025
- Genetic mechanisms of 184 neuro-related proteins in human plasma
Linda Repetto, Jiantao Chen, … Xia Shen·Nature Human BehaviourPeer-reviewed·Aug 29, 2024
- A fully joint Bayesian quantitative trait locus mapping of human protein abundance in plasma
Hélène Ruffieux, Jérôme Carayol, … Armand Valsesia·bioRxiv·May 23, 2020
- Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood
Ting Qi, Yang Wu, … Jian Yang·Nature CommunicationsPeer-reviewed·Jun 5, 2018