Medicine

Genetic analysis of 13,445 people reveals hidden disease links in blood proteins

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This study analyzed 7,144 protein measurements from 13,445 Europeans using an expanded proteomics platform to map genetic variants that influence plasma protein levels. The researchers identified 7,870 significant protein quantitative trait loci (pQTLs), with 34% being newly discovered associations not found in five previous large studies. Through Mendelian randomization analysis across over 1.2 million individuals, they identified 6,340 genetically supported protein-disease associations, revealing new potential therapeutic targets beyond proteins currently in circulation.


The findings expand our understanding of how genetics influences the plasma proteome and identifies thousands of new protein-disease connections that could guide drug development. However, the study also reveals limitations when measuring low-abundance intracellular proteins in blood, which are less likely to show strong genetic signals compared to traditionally secreted proteins.


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Genome-wide association study Concept coming soon Proteomics Concept coming soon Quantitative trait loci Concept coming soon

⚠️ Preprint – Noch nicht peer-reviewed

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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.

Source: Beyond the classical plasma secretome: genetic architecture and disease associations of the expanded human plasma proteome in 13,445 Europeans