Biological insights revealed by integrating genomics and proteomics data
New approaches to investigate proteomics at population scale are empowering genomics research. In this blog post, learn how novel drug targets and new insight into disease pathways are being revealed by integrating genomics and proteomics data.
Amid a rich history of Genome-Wide Association Studies (GWAS) and a wealth of genetic information, new approaches to investigate proteomics at population scale are empowering researchers to identify proteins and pathways that are likely to be causal in disease.1 One such effort is the UK Biobank, which began in 2006 as a long-term, large-scale biomedical research resource and database collecting in-depth genetic and health information from half a million participants. In 2020, the UK Biobank Pharma Proteomics Project (UKB-PPP) was formed, with the intention to measure proteins in tens of thousands of plasma samples. The project used the Olink® Explore 1536 platform to measure ~1500 proteins.
In a 2022 pre-print, the UKB-PPP identified over 8,000 novel proteogenomic associations between genetic variants and circulating protein levels in 54,306 participants.2 They also identified over 2,000 previously reported proteogenomic associations.
These proteogenomic associations are also known as protein quantitative loci or pQTLs, where a cis-pQTL refers to the association between a variant proximal to the gene encoding the protein being measured. Cis-pQTLs were identified for 85% of the proteins evaluated in the study.2 Considered a surrogate measure of specificity, cis-pQTLs provide strong genetic evidence that the right protein is being measured and highlights the exceptional specificity of Olink® technology.
A trans-pQTL refers to the regulation of a protein-of-interest by a genetic variant that is distal to the gene encoding the protein. Trans-pQTLs are of great potential importance to identify novel regulatory pathways linked to proteins associated with specific phenotypes. Interestingly, the number of trans-pQTLs continued to increase with increasing sample size (Figure 1). 2 The UKB-PPP is now measuring an additional ~1500 plasma proteins with the expanded Explore library (i.e., Olink® Explore 3072).
Figure 1. Number of primary cis- and trans-pQTL associations as a function of sample size. Adapted from reference 2, Figure 2e.
Integration of genomics with proteomics was also performed by Koprulu et al. at the University of Cambridge.3 Nearly 3000 serological proteins were measured with Olink Explore 3072, with most of the cis-pQTLs (96.9%) identified in Cohort #1 (n = 1,180) validated in Cohort #2 (n = 1707). Moreover, 256 of the cis-pQTLs were novel. The study also demonstrated the genetic regulation of 575 specific health outcomes via 224 cis-pQTLs. It is noteworthy that many of the cis-pQTLs identified with Olink Explore were not detected in earlier studies with other proteomic technologies, even when those studies had significantly larger sample sets.
Data from the UKB-PPP and the study by Koprulu et al. offer opportunities to accelerate the development of more effective therapeutics and elucidate biological mechanisms that underlie disease. Indeed, the SCALLOP (Systematic and Combined AnaLysis of Olink Proteins) Consortium has collected genetic and proteomic data and clinical phenotypes from 70,000 patients representing 45 cohort studies.4 Seminal work by the SCALLOP Consortium, which includes 35 investigators from 28 institutions, revealed 451 primary genetic associations, discovered 25 causal proteins representing novel drug targets, and suggested 18 drug repurposing opportunities.1 These 25 links to causal proteins bridge the gap between genetic associations and tangible disease pathology. This milestone paper from SCALLOP provides confidence in a systematic approach to therapeutic target discovery by integrating genomics and proteomics data.
To learn more, download the white paper, “Empower genomics with proteomics,” using the button below, or contact us today at info@olink.com.
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