Introduction
Human genetic research is increasingly utilized as a tool for drug discovery and development, aiding in the identification and validation of potential therapeutic targets, predicting long-term effects of drugs, improving patient selection for clinical trials, and repurposing existing medications. Several biopharmaceutical consortia have recently invested in population biobanks, such as the UK Biobank, to facilitate large-scale phenotype-to-genotype studies with comprehensive multi-omics profiling of biological samples. These investments, supported by both private and public funds, are encouraged by analyses showing that drugs backed by human genetic evidence are significantly more likely to gain approval. However, human genetics remains an imprecise tool for biopharmaceutical R&D, as genome-wide association studies often identify genetic variants that affect diseases but do not specify the genes involved or clarify the underlying biological mechanisms. Integrating human genetics with large-scale proteomics could help bridge this gap, connecting genetic data more directly to human health conditions, while proteins in the bloodstream might also reveal insights into the current state of health and the effects of lifestyle and environment on disease development.
In a recent article published in Nature, Sun et al. (2024) from the UK Biobank Pharma Proteomics Project (UKB-PPP) have unveiled an extensive map of human plasma proteomic profiles. This initiative, involving the collaboration of 13 biopharmaceutical companies, has provided an extensive and detailed characterization of plasma proteomic profiles from over 54,000 participants in the UK Biobank. This study presents a wealth of new data with the possibility to accelerate drug discovery and enhance our understanding of genetic influences on health and disease.
The Power of Proteomics
Proteomics, the large-scale study of proteins, offers a unique window into the functional dynamics of the human body. Unlike genomics, which focuses on the static blueprint of DNA, proteomics captures the real-time state of the body’s cells and tissues.The UKB-PPP is one of the largest proteomics studies ever conducted, involving a large cohort of participants. Researchers conducted proteomic profiling on blood plasma samples from 54,219 UKB participants using the antibody-based Olink Explore 3072 proximity extension assay. This assay measures the plasma protein levels of ~3000 proteins, offering a comprehensive view of the human plasma proteome.
In the UKB-PPP study, Protein Quantitative Trait Loci (pQTL) mapping made significant strides by identifying 14,287 primary genetic associations with 2,923 proteins, uncovering that a substantial 81% of these associations were previously unknown. This expansive mapping effort included both cis (local) and trans (distant) genetic associations, effectively illustrating how genetic variants can influence plasma protein levels. Such detailed mapping provides crucial insights into the genetic mechanisms controlling protein expression, which are vital for understanding various physiological and pathological processes. Further enhancing the study’s impact, the researchers conducted ancestry-specific pQTL mapping, which revealed significant genetic associations unique to non-European populations. This approach is particularly important as it addresses the underrepresentation of diverse populations in genetic research, ensuring that the findings are more inclusive and applicable to a wider range of genetic backgrounds. By doing so, the study helps to pave the way for more personalized and equitable healthcare solutions.
In addition to genetic insights, the study also made contributions to understanding proteomic links to disease. It validated several known proteomic associations with diseases, such as the correlation between elevated levels of N-terminal pro-brain natriuretic peptide (NT-proBNP) and ischemic heart disease. Furthermore, it identified novel protein markers that are linked to demographic factors and key health indicators such as age, sex, body mass index (BMI), and renal and liver function. These findings enhance our understanding of how proteins interact with various biological and demographic factors, leading to better predictive tools for health outcomes.
A central focus of the project was on drug discovery and therapeutics, especially through the identification of novel drug targets and the creation of a detailed proteomic map. One significant finding was how elevated levels of the plasma protein PCSK9 correlate with increased lipid levels and a heightened risk of cardiovascular diseases and stroke. This specific insight not only underscores the potential of PCSK9 as a therapeutic target but also highlights the broader implications of proteomic research in identifying biomarkers for complex diseases. The study’s comprehensive approach to mapping protein levels and their genetic determinants opens up new avenues for targeted therapies, potentially leading to more effective and tailored treatments for a variety of conditions.
Implications for Future Proteomic-Genomic Research
The UKB-PPP’s open-access resource paves the way for future studies, enabling scientists to explore the biological mechanisms underlying proteo-genomic discoveries. Through studying this data, and integrating it with other ‘omics technologies, researchers can create predictive models, identify biomarkers, and support drug development.
Conclusion
The UKB-PPP study marks a significant leap forward in our understanding of the human plasma proteome. By mapping the complex interactions between genetics and protein expression on a population-level scale, this research has provided us with an updated “genetic atlas” that can offer significant insights into health and disease. As the scientific community continues to mine this open-access resource, the potential for new discoveries and therapeutic advancements is immense. This collaboration between public and private sectors underscores the power of shared scientific endeavors in advancing health and medicine.
For those interested in diving deeper into the data, the UKB-PPP has made its findings available through an interactive web portal, offering a unique opportunity to explore and utilize this vast proteomic resource.
Outsourcing Bioinformatics Analysis: How Bridge Informatics (BI) Can Help
We are passionate about empowering life science companies with cutting-edge technologies. BI’s data scientists prioritize studying, understanding, and reporting on the latest developments so we can advise our clients confidently. Our bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis.
From pipeline development and software engineering to deploying your existing bioinformatic tools, BI can help you on every step of your research journey. As experts across data types from leading sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing and interpreting genomic and transcriptomic data. Click here to schedule a free introductory call with a member of our team.
Tyler Kolisnik, PhD, Data Scientist, Bridge Informatics
In his role as Data Scientist, Tyler helps clients transform complex data into actionable insights. A specialist in bioinformatics, his expertise includes high-throughput sequencing, data analytics, pipeline development, SQL databasing, and R and Python programming.
Tyler previously worked as a Bioinformatician at Imagia-Canexia Health, Rancho Biosciences, and GenomeDx Biosciences. He completed his PhD at Massey University in Auckland, New Zealand in collaboration with the Genome Sciences Centre in Vancouver. His research focused on the development of machine learning models and tools for improving cancer prognosis and treatment. If you’re interested in reaching out, please email [email protected] or [email protected]
