A view from the inside – an author’s perspective from Anders Mälarstig
SCALLOP founder, Anders Mälarstig, talks about the consortium’s first major combined study, which was recently made available on bioRxiv
The SCALLOP consortium is a collaborative framework for discovery and follow-up of genetic associations with proteins measured on the Olink Proteomics platform. The aim of the SCALLOP consortium is to identify novel molecular connections and protein biomarkers that are causal in diseases.
Key to this is the identification of protein quantitative trait loci, pQTLs, which are robust connections between a gene variant and the levels of a protein. When evaluated together with clinical data in a Mendelian Randomization analysis, they provide strong instruments for determining if a protein biomarker for disease is causal, or is altered as a consequence of disease processes. Causality is a crucial factor for the identification and selection of actionable drug targets.
SCALLOP has recently completed a combined study that looks at protein quantitative trait loci (pQTL) for multiple cardiovascular proteins in an unprecedented number of individuals. The authors have made the pre-print available on-line at bioRxiv so that the scientific community can access the important findings from this study as soon as possible: Folkerson et al, “Genomic evaluation of circulating proteins for drug target characterisation and precision medicine“, bioRxiv 2020.04.03.023804.
A view of the study from the inside
Dr. Anders Mälarstig, SCALLOP founder and one of the principle investigators on the article, had the following to say about this landmark study:
“The work for this paper is what kicked off the SCALLOP consortium, almost 3 years ago now and it’s therefore a proud moment to release the findings to the scientific community.We studied 90 proteins measured with Olink PEA in almost 30,000 patients or controls by combining data from 15 study cohorts. It is, as far as we know, the largest study performed to date on genetics of circulating proteins.
The work led to the identification of 467 genetic loci (pQTLs) for 85 of the 90 proteins, which provided insights into protein-regulatory pathways and explained why protein levels are often very different between different individuals. We used the pQTLs in combination with genetic data on 38 common diseases to predict which of the proteins that were likely to be viable drug targets for pharmacological intervention. In total, 25 proteins were found to be causal in disease, including IL1RA and CD40 in rheumatoid arthritis, ST2 in inflammatory bowel disease, Dkk-1 in osteoporosis and RAGE in diabetes. However, IL1RA was also causal for increased cholesterol and CD40 with increased risk of stroke. Using open source information on drug targets we found that 14 of the 25 causal proteins were already targeted by drugs in phase-2 (or later) programs. Our data was concordant with the protein target and treatment indication for several of the drugs but we also identified drug repurposing opportunities such as a RAGE inhibitor for diabetes and completely novel target ideas.
In conclusion, we showed that large-scale mapping of pQTLs combined with causality assessment using Mendelian randomization is likely to be a successful approach to identify novel drug targets.”