Background
A team from the MRC Epidemiology Unit at the University of Cambridge, led by Prof. Claudia Langenberg has carried out a cis-focused proteogenomics analysis of 2,923 plasma proteins measured in 1,180 individuals using the Olink® Explore high-throughput platform for protein biomarker discovery. The intention with this study was to leverage plasma proteomics as the intermediate layer between the genome and disease phenome in order to identify new disease processes and potential new targets for therapeutic interventions.
Outcome
Analysis of the discovery cohort of 1,180 samples identified a total of 1,553 independent genetic associations for 914 unique proteins, representing the discovery of 256 previously unreported cis-pQTLs (where the sequence variant associated with differential protein levels maps within or close to the gene encoding the protein in question). When the cis-pQTLs identified were examined in a second cohort of >1,700 subjects 96.9% could be replicated. Phenotypic analysis demonstrated shared genetic regulation of 224 cis-pQTLs with 575 specific health outcomes, revealing several notable examples for metabolic disease – with gastrin-releasing peptide as a potential therapeutic target for type 2 diabetes as one highlighted example.
It was also of interest that 125 of the 256 newly reported cis-pQTLs were for 101 proteins previously targeted in similar proteogenomic studies using other high-multiplex proteomic technologies, which failed to identify these cis-associations despite being based on much larger sample sets (up to 30 times larger that the current study). This is significant because the identification of cis-pQTLs is a strong indicator that the proteomics assay being used is targeting the correct protein. It also suggests that reinvestigations of proteins examined in previous proteogenomic studies may be worth pursuing using orthogonal proteomics technologies.
Overall, these findings demonstrate the value of integrating proteomic technologies with genomics, even at moderate scale, to identify new mediators of metabolic diseases with the potential for therapeutic interventions.
