Mode
Text Size
Log in / Sign up

Expanded proteomics platform identifies 7,870 pQTLs, 34% novel, in European populationsNew data reveals thousands of links between genes and proteins

AI-generated summary of the cited source, checked by automated accuracy review. How we work

Key Takeaway
Consider the expanded proteome pQTL map as a resource for prioritizing therapeutic targets, but validate findings in diverse populations.

This meta-analysis, based on data from two European cohorts totaling 13,445 participants (INTERVAL: 9,251; CHRIS: 4,194), used the SomaScan 7k platform to investigate the genetic architecture of the expanded plasma proteome. The primary outcome was pQTL discovery, with secondary outcomes including causal inference and therapeutic target prioritisation.

The analysis identified 7,870 significant pQTLs (P-value < 1.26 x 10E-11), comprising 1,784 cis and 6,086 trans associations. Of these, 2,704 (34%) associations were not reported in five prior large-scale pQTL studies, with 1,422 of these novel associations coming from newly assessed proteins. Notably, newly assessed proteins were less likely to harbor cis-pQTLs (15%) compared to the previous platform version (28%).

The study also found 22 pleiotropic trans-regulatory hotspots that accounted for 68% of all trans-pQTLs. Using two-sample Mendelian randomization, the authors identified 6,340 genetically supported protein-trait associations from 2,003 phenotypes, suggesting potential disease mechanisms and therapeutic opportunities beyond currently drug-targeted circulating proteins.

Limitations acknowledged by the authors include biological and technical constraints of studying low-abundance intracellular proteins in circulation. The findings should be interpreted cautiously, as the causal inference relies on Mendelian randomization assumptions, and the potential therapeutic opportunities are preliminary.

Understanding how our bodies work often starts with looking at proteins in our blood. These proteins act as messengers, but the link between our genes and these proteins is complex. A large-scale analysis of over 13,000 people revealed 7,870 significant genetic links to the plasma proteome. This means researchers found specific spots where genetics directly influence protein levels.

Of these findings, about 2,704 were not reported in previous large studies. Many of these are new proteins that have never been fully mapped before. The study also identified over 6,000 trans-pQTLs, which are genetic links that affect multiple different proteins at once. These clusters suggest specific areas where genetics and biology overlap heavily.

While the results offer a clearer map of how our bodies function, there are still hurdles. It is currently difficult to study low-abundance proteins that stay inside cells rather than circulating in the blood. However, by finding over 6,000 genetically supported associations between proteins and physical traits, this work helps scientists pinpoint where new treatments might be most effective.

What this means for you:
Researchers found over 7,800 genetic links to blood proteins, helping map out how our bodies function.

Common questions

How many genetic links were found?

The analysis identified 7,870 significant pQTLs. These are specific locations where genetics influence the amount of proteins in a person's blood. This includes both local links and broader ones that affect multiple different proteins at once.

Were any of these findings new?

Yes, 2,704 associations were not reported in five previous large-scale studies. Of those, 1,422 came from proteins that were only just being assessed in this specific study.

What does this mean for future treatments?

By identifying over 6,340 genetically supported associations between proteins and traits, the research helps scientists find new targets for medicine. This can help identify disease mechanisms beyond what is currently targeted by drugs.

Study Details

Study typeMeta analysis
Sample sizen = 9,251
EvidenceLevel 1
PublishedJul 2026
View Original Abstract ↓
Circulating plasma proteins are key biomarkers and therapeutic targets, now measurable at scale through high-throughput technologies, yet whether expanding proteomics platforms beyond the classical plasma secretome enhances genetic discovery and causal inference remains poorly understood. Here, we use an expanded SomaScan 7k platform to map the genetic architecture of a broader segment of the plasma proteome and to evaluate how proteome expansion affects pQTL discovery, causal inference and therapeutic target prioritisation. After quality control, we analysed 7,144 aptamers targeting 6,267 proteins in the harmonised dataset of two European cohorts: INTERVAL (n = 9,251 participants) and CHRIS (n = 4,194), and conducted genome-wide pQTL association analyses followed by meta-analysis. We identified 7,870 significant pQTLs (P-value < 1.26 x 10E-11; 1,784 cis, 6,086 trans), of which 2,704 (34%) associations were not reported in five prior large-scale pQTL studies. Newly assessed proteins, which accounted for 53% (1,422/2,704) of the novel associations, were less likely to harbour cis-pQTLs associations (15%) than those in the previous platform version (28%), consistent with their lower expected plasma concentrations and predominantly intracellular localisation. Colocalization analyses revealed widespread sharing of genetic signals across proteins and characterised 22 pleiotropic trans-regulatory hotspots accounting for 68% of all trans-pQTLs. Through two-sample Mendelian randomization analyses on 2,003 phenotypes from the Million Veteran Program, UK Biobank, and FinnGen (combined N > 1.2 million), we identified 6,340 genetically supported protein-trait associations, highlighting disease mechanisms and potential therapeutic opportunities beyond currently drug-targeted circulating proteins. Together, these findings provide a systematic view of the genetic architecture of the expanded plasma proteome and demonstrate that plasma proteome expansion reveals genetically anchored disease biology beyond the classical secretome, while exposing inherent biological and technical constraints of studying low-abundance intracellular proteins in circulation.
Free Newsletter

Clinical research that matters. Delivered to your inbox.

Join thousands of clinicians and researchers. No spam, unsubscribe anytime.