Largest Blood Protein Genetics Study Reveals New Precision Medicine Opportunities, Including TYK2 Inhibitor Repurposing for Rheumatoid Arthritis
核心洞察
The world's largest genetic study of blood proteins, involving over 78,000 participants across 38 cohorts, has been published in Cell, revealing new insights into disease mechanisms and drug development opportunities.
Researchers identified evidence that TYK2 (搜索) inhibitors, currently used for psoriasis (搜索), could potentially be repurposed for treating rheumatoid arthritis (搜索) through multi-layered biomedical data analysis.
A complementary Nature Genetics study analyzing 1,400 volunteers from underrepresented British Bangladeshi and Pakistani communities identified over 1,200 genetic associations with blood protein levels, more than half previously unreported.
Scientists from Queen Mary University of London's Precision Healthcare University Research Institute (PHURI) and the Berlin Institute of Health (BIH) at Charité have led the world's largest study on the genetic regulation of blood proteins, published today in Cell. The research, involving 118 investigators from 89 institutions, analyzed data from over 78,000 participants collected across 38 cohorts from different countries, marking an unprecedented scale in proteogenomic research.
Proteins, often described as the "building blocks of life," serve as the primary functional output of the genetic code, playing essential roles in tissue formation, metabolism, and immune defense. Despite two decades of large-scale genetic studies involving hundreds of thousands of participants, translating genetic discoveries into tangible patient benefits has remained challenging, partly due to the difficulty of identifying disease-causing genes, proteins, and underlying mechanisms.
"We are at a point where scalable measurements are possible at almost all layers of biology," said Dr. Mine Koprulu, Senior Postdoctoral Researcher in Multiomics at Queen Mary's PHURI and lead author of the study. "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."
TYK2 (搜索) Inhibitors: From Psoriasis (搜索) to Rheumatoid Arthritis (搜索)
A key finding from the study highlights the potential for drug repurposing. The researchers presented several lines of evidence and biomedical data demonstrating that TYK2 (搜索) inhibitors, a class of drugs currently approved for treating psoriasis (搜索), could potentially be repurposed for the treatment of rheumatoid arthritis (搜索). This finding exemplifies how integrating molecular data at scale with clinical knowledge can yield actionable therapeutic insights.
Professor Claudia Langenberg, senior study lead and Director of PHURI at Queen Mary and Chair of Computational Medicine at BIH at Charité, emphasized the collaborative nature of the work: "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."
Complementary Technologies Reveal Hidden Biology
In a companion study published in Nature Genetics, researchers analyzed blood samples from approximately 1,400 volunteers participating in Genes & Health, a pioneering research program involving British Bangladeshi and British Pakistani communities—populations historically underrepresented in genetics research despite experiencing a disproportionate burden of several common diseases.
Using an advanced form of mass spectrometry to measure thousands of circulating proteins, the international team compared this approach with two widely used protein analysis technologies. They demonstrated that no single method captures the full complexity of the human plasma proteome and that newer approaches can reveal important biological information that other technologies may overlook.
The researchers identified more than 1,200 genetic associations with blood protein levels, with more than half not previously reported. By integrating these findings with evidence from large-scale genetic studies and other biological data, they identified 21 proteins linked to 44 diseases, providing new insights into disease mechanisms and highlighting potential opportunities—and possible safety considerations—for future drug development.
Professor Maik Pietzner, Professor of Health Data Modelling at Queen Mary University of London, who served as senior co-lead on the Cell study and lead author of the Nature Genetics study, noted two particularly exciting achievements: "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."
Regarding the complementary technologies finding, Pietzner added: "This study shows that no single technology can capture the full complexity of the proteins circulating in our blood. By combining next-generation mass spectrometry with genetic analyses, we've uncovered biological insights that other approaches can miss, providing new opportunities to better understand disease mechanisms, identify promising drug targets and anticipate potential safety signals much earlier in the drug development process."
Novel Disease Links and Underrepresented Populations
The Nature Genetics study also identified a previously unrecognized potential role for a protein called IGLV3-21 (搜索) in Graves' disease (搜索), an autoimmune condition affecting the thyroid, illustrating how combining genetic and protein data can generate new hypotheses about disease biology.
Professor David van Heel, Professor of Gastrointestinal Genetics at Queen Mary University of London and Co-Principal Investigator of Genes & Health, expressed gratitude to the study volunteers: "This research would not have been possible without the extraordinary commitment of the Genes & Health volunteers, who continue to make an invaluable contribution to improving our understanding of health and disease. It is exciting to see discoveries emerging that have the potential to benefit people far beyond the communities who made this work possible."
Professor Langenberg further underscored the value of diverse population inclusion: "This study demonstrates the tremendous scientific value of the unique research resource established by our colleagues at Queen Mary through Genes & Health. Bringing together cutting-edge proteomics with such a richly characterised and historically underrepresented population allows us to generate discoveries that simply would not be possible otherwise."
The researchers say the findings demonstrate the importance of using complementary technologies to build a more complete picture of human biology and reinforce the value of including diverse populations in genomic research. Genes & Health remains one of the world's largest community-based genetics studies, working closely with participating communities to help researchers better understand why diseases develop and how treatments can be improved for everyone.