In a study published today in Nature genetics, scientists at deCODE genetics , 
a subsidiary of the pharmaceutical company Amgen, demonstrate how measuring the 
levels of a large number of proteins in plasma at population scale when 
combined with data on sequence diversity and RNA expression dramatically 
increases insights into human diseases and other phenotypes.

Scientists at deCODE genetics have used levels of five thousand proteins in 
plasma targeted on a multiplex platform at population scale to unravel their 
genetic determinants and their relationship with human disease and other 
traits. Previous studies of the genetics of protein levels either consisted of 
much fewer individuals or tested far fewer proteins than the one published 
today.

Using protein levels in plasma measured with the Somascan proteomics assay, 
scientists at deCODE genetics tested the association of 27 million sequence 
variants with plasma levels of 4,719  proteins in 35,559 Icelanders. They found 
18,084 associations between variants in the sequence and levels of proteins, 
where 19% are with rare variants identified with whole-genome sequencing. 
Overall, 93% of the associations are novel. Additionally, they replicated 83% 
and 64% of the reported associations from the largest existing plasma proteomic 
studies, based on the Somascan method and the antibody-based Olink assay, 
respectively.

The levels of proteins in plasma were tested for associations with 373 diseases 
and other traits and yielded 257,490 such associations. They integrated 
associations of sequence variants with protein levels and diseases and other 
traits, and found that 12% of around fifty thousand variants reported to 
associate with diseases and other traits  also associate with protein levels. 

"Proteomics can assist in solving one of the major challenges in genetic 
studies: to determine what gene is responsible for the effect of a sequence 
variant on a disease. In addition the proteome provides some measure of time 
because levels of proteins in blood rise and they fall as a function of time to 
and from events," said Kari Stefansson CEO of deCODE genetics and one of the 
senior authors on the paper. 


source: deCODE genetics