Measuring proteins reveals how genetic changes help give rise to complex traits and diseases
An article published today in the journal Nature brings us closer to understanding how differences in the genomes of individuals help contribute to common diseases and influence disease risk. Specifically, this study — by far the largest of its kind to date — revealed the effects of genetic variations on the levels of circulating blood proteins across thousands of individuals.
Proteins play essential roles throughout the body, and changes in their concentrations can reflect a person’s health status at any given time. Proteins are also the targets of most drugs, so the results of this study open the door to understanding individual responses to medical treatments, one of the goals of precision medicine.
Over the past decade, genome-wide association studies (GWAS) have identified of DNA variants that are linked to complex traits and diseases but have not explained exactly why they are important. The vast majority of DNA differences flagged by GWAS lie in regions of the genome with no known function and have small effect sizes. This makes establishing causal relationships or determining disease risk extremely difficult, even for conditions with a strong hereditary component such as obesity or cancer.
In the largest study of its kind to date, an international team led by researchers from the University of Cambridge and Merck tested 10.6 million DNA variants against the levels of 2,994 plasma proteins — measured using the SOMAscan® assay — in 3,301 healthy individuals of European heritage. They identified 1,927 genetic variants that impact the levels of 1,478 plasma proteins, of which ~90% had not been previously reported. Many of the variants act in “trans” (i.e., they lie far from the gene whose activity is altered, typically on different chromosomes). Trans associations are particularly interesting because they can highlight biological connections that are otherwise difficult to predict.
The authors cross-referenced their findings with known disease-associated GWAS variants to identify proteins that might cause disease. Some disease-associated proteins are targets of existing drugs, which suggests possible therapeutics for new indications. Connecting protein perturbations to disease endpoints also allows identification of new drug targets and potential safety concerns for drugs under development. These results also suggest that monitoring protein levels over time may suffice for regular health management.
See also the University of Cambridge news release.