A study examining thousands of proteins from a mere droplet of blood has illustrated their potential to foretell the advent of numerous diverse illnesses. This groundbreaking research, detailed in an article released today, 22 July 2024, in Nature Medicine, is a collaborative effort involving significant institutions such as GSK, Queen Mary University of London, University College London, Cambridge University, and the Berlin Institute of Health at Charité Universitätsmedizin in Germany.
This extensive proteomics investigation, the largest of its kind, utilised data from the UK Biobank Pharma Proteomics Project (UKB-PPP). It analysed around 3,000 plasma proteins from over 40,000 randomly selected participants of the UK Biobank. These protein measurements are linked to the participants’ electronic health records. Employing sophisticated analytical techniques, the researchers identified a ‘signature’ of 5 to 20 critical proteins for predicting each disease studied.
The findings highlighted the efficacy of protein ‘signatures’ in predicting the emergence of 67 diseases, including multiple myeloma, non-Hodgkin lymphoma, motor neurone disease, pulmonary fibrosis, and dilated cardiomyopathy. These protein-based prediction models surpassed traditional models that rely on routinely recorded clinical data, such as blood cell counts, cholesterol levels, kidney function, and diabetes tests (glycated haemoglobin), in most cases examined.
Moreover, the implications of this research are profound, especially in the context of well-established cardiovascular risk scores, which have been used to predict and mitigate the risk of future cardiovascular events such as heart attacks and strokes. This new approach offers fresh predictive possibilities for a myriad of diseases, including those that are rare and often take a lengthy period to diagnose, thereby opening up opportunities for timely and accurate diagnoses.
However, the research calls for further validation across different populations, including those with and without symptoms of diseases and among various ethnic groups, to ensure its broad applicability and reliability.
The lead author, Professor Claudia Langenberg, who is the Director of the Precision Healthcare University Research Institute (PHURI) at Queen Mary University of London and Professor of Computational Medicine at the Berlin Institute of Health at Charité Universitätsmedizin, emphasised the novelty and potential of these findings. She pointed out that while measuring specific proteins like troponin for diagnosing heart attacks is standard, the vast array of proteins now measurable in human blood presents new markers that could revolutionise screening and diagnostic processes. She highlighted the critical need for proteomic studies across different populations to validate these findings and the development of cost-effective, clinically standard tests to measure disease-relevant proteins.
Dr Julia Carrasco Zanini Sanchez, the first author and a research student at GSK and the University of Cambridge at the time of the study, now a postdoctoral researcher at PHURI, shared her excitement about the performance of several protein signatures. These signatures, which were comparable or even superior to existing proteins used in screening tests, such as the prostate-specific antigen for prostate cancer, underscore the potential of these signatures for early detection. This could lead to improved prognosis for a range of severe diseases, identifying numerous promising leads for further clinical evaluation.
Dr Robert Scott, co-lead author and Vice President and Head of Human Genetics and Genomics at GSK, reflected on the significance of this work for drug development. Identifying patients most likely to benefit from new medicines is a perennial challenge, and this study showcases the potential of large-scale proteomic technologies in pinpointing individuals at high risk for various diseases. This aligns with GSK’s strategy to leverage technology to deepen understanding of human biology and disease, aiming to enhance success rates and efficiency in drug discovery and development.
More information: Julia Carrasco-Zanini et al, Proteomic signatures improve risk prediction for common and rare diseases, Nature Medicine. DOI: 10.1038/s41591-024-03142-z
Journal information: Nature Medicine Provided by Queen Mary University of London
