Genetics of blood proteins!
Involving a collaboration with 118 investigators contributing from 89 institutions, the researchers carried out a study on the genetic regulation of blood proteins.
The findings, published in Cell, hold the potential to transform our understanding of different diseases and their treatment opportunities.
Proteins are often described as the “building blocks of life”. Our genetic code’s main purpose is to produce instructions for making proteins, which play a vital role in every part of human health, ranging from building tissues to their role in metabolism or to fight infections.
Large-scale genetic studies have been conducted for various diseases in the past two decades, with hundreds of thousands of participants involved. Although these studies revealed fundamental insights, their translation into tangible improvements for how we treat patients have been limited for various reasons, including a longstanding challenge in human genetics: identifying disease-causing genes, proteins and mechanisms underlying diseases.
Blood proteins offer a fundamental and dynamic view into human health and its many determinants. By studying the genetic regulation of blood proteins and linking this to knowledge on genetic disease causes, the authors identified new insights into how human physiology works and how such knowledge can inform drug development.
In this study, published in Cell, scientists brought together data from over 78,000 participants collected through a collaboration across 38 cohorts from different countries, the largest study of its kind.
Using machine learning-guided effector gene assignment, they provide genetic evidence for pathways, cell types, and tissues that modulate circulating protein levels, highlighting N-linked glycosylation as an important regulatory pathway.
The researchers demonstrate that genetic instruments of protein production/function (“cis”) versus modulation (“trans”) reveal distinct phenotypic insights.
They also identify proteins as candidates for drug targets and engagement (e.g., plasma furin and cardiovascular diseases) by comparing cis-based genetic evidence with protein-disease associations.
The lead author of the study, said: “We are at a point where scalable measurements are possible at almost all layers of biology. This gives us an opportunity to gain a molecular view into diverse diseases, with the potential to significantly accelerate rate of discovery for new drug targets or drug repurposing opportunities”.
For example, the study reveals several lines of evidence and biomedical data to highlight that TYK2 inhibitors, which are currently used for psoriasis, can potentially be repurposed for the treatment of rheumatoid arthritis.
A senior study lead author said: “Our study is a powerful demonstration of how human molecular data can deliver new opportunities for precision medicine when generated at scale and integrated with clinical knowledge. This work would have not been possible without the dedication and collaboration of so many scientists around the world, and of course the many study participants who generously dedicated their time to research to benefit others.”
A senior co-lead author said: “There are two achievements I am particularly excited about as they open new avenues to close important gaps in research. Firstly, combining our genetic work with machine learning enabled us to better understand how human biology works, and secondly, provided evidence to help getting the right drug to the right patient.”
