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Researchers led by Queen Mary University of London and the Berlin Institute of Health at Charité have analysed blood protein regulation in more than 78,000 people, offering novel insight into disease mechanisms, drug targets and potential treatment repurposing
Researchers from Queen Mary University of London and the Berlin Institute of Health at Charité have led the largest study to date of how human genetics regulates blood proteins, in work that could sharpen scientific understanding of disease mechanisms and improve the search for precision medicine treatments.
The study involved 118 investigators from 89 institutions. It brought together data from more than 78,000 participants across 38 international cohorts making it the largest analysis of its kind.
Proteins are central to human biology being described frequently as the building blocks of life because they form tissues, drive metabolism, support immune defence and regulate many of the molecular processes that sustain health. The genetic code provides the instructions to make proteins but the way in which genes influence protein levels and function can vary substantially between individuals. This variation can help to explain why some people have increased susceptibility to disease and why patients may respond differently to the same treatment.
Large-scale genetic studies have transformed biomedical research during the past two decades, with hundreds of thousands of people contributing data to studies of both common and rare diseases. However, to translate genetic associations into patient benefit has remained difficult. One persistent challenge has been to identify the specific genes, proteins and biological pathways that cause or drive disease, rather than simply mark an increased risk.
Blood proteins offer a particularly valuable route into this problem because they provide a dynamic molecular readout of health, disease and physiological response. By studying how genetic variation affects blood proteins – and by linking those findings to evidence on genetic causes of disease – the researchers were able to identify biological mechanisms that could inform drug discovery and drug repurposing.
The authors said the findings could help to connect genetic risk more directly with disease-relevant proteins and treatment opportunities. One example highlighted in the study concerned tyrosine kinase 2 (TYK2) inhibitors. These drugs are currently used to treat psoriasis but the study identified evidence to suggest that they could also have potential to be repurposed for rheumatoid arthritis.
“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 the rate of discovery for novel drug targets or drug repurposing opportunities,” said Dr Mine Koprulu, senior postdoctoral researcher in multiomics at Queen Mary University of London’s Precision Healthcare University Research Institute and a lead author of the study.
“Our study is a powerful demonstration of how human molecular data can deliver novel opportunities for precision medicine when generated at scale and integrated with clinical knowledge,” said Professor Claudia Langenberg, senior study lead and director of the Precision Healthcare University Research Institute at Queen Mary University of London and chair of Computational Medicine at the Berlin Institute of Health at Charité.
“There are two achievements I am particularly excited about, as they open novel avenues to close important gaps in research.
“First, to combine our genetic work with machine learning enabled us to better understand how human biology works.
“Second, it provided evidence to help to get the right drug to the right patient,” said Professor Maik Pietzner, senior co-lead and professor of health data modelling at the Berlin Institute of Health at Charité.
For further reading please visit: 10.1016/j.cell.2026.03.049
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