Addressing one of the largest remaining knowledge gaps in biomedical science, researchers from Novartis, SomaLogic, and the Icelandic Heart Association have found a way to tie genetic variations to complex disorders, such as heart disease and diabetes. Their findings, published online today in the journal Science, demonstrate that communication between networks of proteins can explain the connections between genes and diseases.
The researchers began with an established Icelandic study of aging (AGES-Reykjavik), which initially focused on understanding the role of genetic variations in late-onset, age-related diseases. Participants in AGES-Reykjavik were over 65 and included both healthy adults and those diagnosed with various conditions of old age. However, linking individual gene variants to disease proved almost impossible since common chronic conditions of aging are not caused by defects in a single gene.
In the Science study, the research teams used a custom version of SomaLogic’s proprietary SOMAscan® technology to measure the levels of over 4,000 different human proteins in 5,457 blood samples from individuals in the AGES-Reykjavik study. Using advanced computational tools to mine approximately 27 million protein measurements, the researchers found that the examined proteins clustered into 27 different groups or “networks” composed of 20 to 921 proteins.
Each network contained a few central players that were highly connected, and these “hub proteins” seemed to organize interactions and information flow within the network. When investigators incorporated genetic data on AGES participants, they found that the hub proteins were often regulated by genetic variations that had been previously linked to cardiovascular and metabolic diseases, but for which the biological underpinnings were unknown.
In short, these findings show how the thousands of proteins detectable in the blood can facilitate communication between the various cells, tissues and organs of the body. Using the SOMAscan assay to “listen into” these communication networks may reveal new ways to detect, predict, monitor and even treat common age-related disorders.