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The largest study of its kind maps how genes alter blood proteins to drive disease

Analysis of blood protein data from more than 78,000 people, enabled in part by Thermo Fisher’s Olink™ technology, reveals how genetic differences shape disease and point to new treatment opportunities.

Terri Somers
Senior Manager, Global PR and StoryLab

SCIENTISTS have long known that differences in our genes shape our risk of disease. But deciphering how those differences play out inside the body has remained a major challenge.

New technologies from Thermo Fisher Scientific and others are changing that. In the largest study to date linking genes to blood proteins, published in the journal Cell, researchers analyzed blood protein data from more than 78,000 people worldwide, a population large enough to uncover consistent patterns in how genetic differences influence the molecules that regulate the body and drive disease-related processes.

The Largest Study of its Kind Maps How Genes Alter Blood Proteins to Drive Disease

“By studying how genetic differences affect proteins in the blood and linking that to disease, we can better understand how the body works, and use that knowledge to inform drug development,” said Mine Koprulu, a senior postdoctoral researcher at Queen Mary University of London’s Precision Healthcare University Research Institute (PHURI) and one of the study’s lead authors. “We are at a point where scalable measurements are possible. This gives us an opportunity to gain a molecular view into diverse diseases, with the potential to accelerate the discovery of new drug targets or repurpose an already approved drug.”

These advances, including Thermo Fisher’s Olink™ technology, are giving scientists new ways to study proteins, the molecules that carry out much of the body’s work, from fighting infection to controlling inflammation and sending messages between cells. This field is known as proteomics. Though the human proteome – the full set of proteins in the body - is vast, until recently, scientists could only measure a limited number of proteins at a time. Olink’s Proximity Extension Assay (PEA) platform allows scientists to measure up to 5,000 proteins from a single blood sample, enabling studies at this scale.

The study authors noted that the scale of this project was possible because many of the contributing studies used the same proteomics platform, Olink, allowing researchers to combine and compare data across tens of thousands of samples.

Measuring proteins at scale is only part of the puzzle. It shows how protein levels differ from person to person, but not why those differences exist. To answer that, researchers also looked at genetic data, which acts like a set of instructions for how the body is built and functions. Proteins, by contrast, show what the body is doing in real time. Studying both together helps scientists see how genetic differences lead to changes in proteins and how those changes contribute to disease, pointing to new ways to treat it.

“Advances in technologies that measure proteins across the body, along with large international collaborations, made this study possible,” Mine said. “More than 118 scientists from 89 institutions contributed data from 38 studies worldwide, creating a dataset large enough to uncover patterns that could not be seen before.”

The study identified more than 24,000 genetic links that influence levels of over 1,100 circulating proteins, providing one of the most detailed views to date of how our biology is shaped and how it relates to disease. Many of these effects come from genetic changes far from the genes that directly produce those proteins, showing that genes can influence protein levels in complex and sometimes indirect ways.

Mine Koprulu, a senior postdoctoral researcher at Queen Mary University of London’s Precision Healthcare University Research Institute and one of the study’s lead authors.

Researchers also identified a kind of quality-control system that regulates many circulating proteins in which small sugar molecules are added to proteins to help shape them, guide where they go, and keep them stable. This process may play a role in regulating disease-relevant protein levels. Some of the disease signals uncovered by the study already point to new treatment opportunities, including proteins linked to inflammatory diseases such as rheumatoid arthritis.

The researchers found that changes in a gene called TYK2 affect the levels of several inflammation-linked proteins. Drugs that target TYK2 are already approved for inflammatory conditions such as psoriasis. The new findings suggest those same drugs could potentially be repurposed to treat additional inflammatory diseases, including rheumatoid arthritis, or help identify which patients are most likely to benefit from treatment with a TYK2 inhibitor.

As more of these proteogenomic connections are uncovered, a broader picture begins to emerge, one in which different diseases are linked through shared biological mechanisms. Claudia Langenberg, senior study lead and director of PHURI, said that she wants to develop this network across the entire “diseasome”, building a map that reveals how conditions that may seem unrelated are connected at a deeper level.

“This can be transformative for diagnoses that have received less attention than the big killers but affect the lives of many patients,” Claudia said.

Viewed in a wider context, the study signals an important shift for the field as a whole.

Claudia Langenberg, senior study lead and director of Queen Mary University of London’s Precision Healthcare University Research Institute

“This is the kind of study that signals a turning point,” said Yan Zhang, Ph.D., president of Thermo Fisher’s Proteomic Sciences business. “We’re beginning to see how large-scale human data can translate into real insights about disease and how to treat it.”

Yan Zhang, Ph.D., president of Thermo Fisher’s Proteomic Sciences business