The landscape of drug development is constantly evolving, fueled by groundbreaking scientific advancements. While genetics has played a central role in understanding diseases, proteomics – the study of proteins – provides a more comprehensive picture of disease phenotypes and mechanisms. Proteins act as intermediate phenotypes, bridging the gap between genetic associations and tangible disease pathology. Through proteomics at a population scale, scientists can identify causal proteins, uncover novel pathways, and discover potential therapeutic targets. This holistic approach has the potential to revolutionize drug development.
The integration of genetic and functional genomics data, along with clinical insights, has become a driving force behind successful FDA-approved drugs. Analysis of multiple biomarkers (e.g. SNP in DNA, known transcription factors, gene expression patterns, AND protein modulation) provides a holistic understanding of biological mechanism for specific drug targets and provides insights into the phenotypic state. Olink® Proteomics is a cutting-edge technology that is advancing the way we approach drug development. Let’s review a few key publications that describe how Olink proteomics reshaped the outcomes of a clinical study.
Leverage Existing Cohorts
Small studies can have a big impact. In a clinical study of 189 patients1, researchers identified changes in the proteome associated with onset and progression of hereditary transthyretin-mediated (hATTR) amyloidosis in drug versus placebo treated patients. Using Olink Target 96 panels for relative protein quantitation, scientists identified a set of 66 significantly different proteins between the treated and untreated groups. Most significant was neurofilament light chain (NfL), a novel biomarker associated with nerve damage and polyneuropathy from completed phase 3 samples. NfL is currently being validated for treatment justification, disease progression, and response to therapy. Novel biomarker detection through proteomics can improve patient outcomes.
Accelerate Breakthroughs and Reduce Cost
By analyzing thousands of proteins from a single sample, you can more efficiently test potential targets of interest. Progressive fibrosing interstitial lung disease (ILD) is characterized by parenchymal scar formation, leading to high morbidity and mortality. However, predictive phenotypic markers were relatively unknown. In a recent study2, doctors used the Olink Explore 384 panel to determine relative concentrations of a series of proteins from plasma in patients with different classifications of ILD. Using machine learning, a 12 protein biomarker signature was validated. This signature robustly identifies low- and high-risk ILD progression, thus enabling future clinical trials to enrich clinical trial cohorts and accelerate outcomes.
Improved Return on Investment
Proteomics can lead existing genomics investments into actionable targets, as large-scale studies can provide ample data. There are several publications describing how protein biomarkers have reshaped large studies3,4,5. These include a meta-analysis on over 30,000 individuals across 14 studies6 evaluating a series of 90 cardiovascular proteins. In addition to identifying 451 protein quantitative trait loci (pQTL) for 85 proteins, scientists evaluated known drug targets and suggested new target candidates or repositioning opportunities using Mendelian randomization. This included 11 proteins with causal evidence of involvement in human disease that have not previously been targeted.
Given that 95% of the current drugs on the market target proteins, have you considered adding proteomics to your current experimental plan? By profiling the proteins in your sample (48 to 5300 at a time), you can save the costs and time associated with lower throughput options. Learn more about how Olink stacks up against other proteomics methods: Comparing Mass Spectrometry, ELISA, and Olink for Proteomics.
Conclusion
Proteomics is revolutionizing drug development by enabling a more holistic approach for target discovery. Leveraging Olink Proteomics, scientists can perform high-throughput, simultaneous analysis of proteins with high specificity and sensitivity using minimal sample amounts to provide an in-depth understanding of disease and drug response.
While resources are often limited for comprehensive genomics and proteomics analysis to expand on existent workflows, Azenta Life Sciences recognizes this challenge and is here to support your discovery or clinical research experiments. With our extensive lab facilities and experienced scientific teams, we offer comprehensive assistance in designing and executing crucial next generation sequencing projects to help propel your research forward.
Learn more about how Azenta’s protein biomarker detection services can help accelerate your discovery of drug targets.d regulatory requirements. Our guide to automated cryogenic storage solutions provides detailed insights to help you navigate these crucial factors effectively.
References
1. Ticau, S., Sridharan, G., Tsour, S., et al. Neurofilament Light Chain as a Biomarker of Hereditary Transthyretin-Mediated Amyloidosis. Neurology, vol. 96, no. 3 (2021).
2. Bowman, W. S., Newton, C. A., Linderholm, A., et al. Proteomic biomarkers of progressive fibrosing interstitial lung disease: a multicentre cohort analysis. The Lancet Respiratory Medicine, vol. 10, no. 6, 593–602 (2022).
3. Xu, Y., Ritchie, S.C., Liang, Y. et al. An atlas of genetic scores to predict multi-omic traits. Nature, vol. 616, 123–131 (2023).
4. You, J., Guo, Y., Zhang, Y. et al. Plasma proteomic profiles predict individual future health risk. Nature Communications, vol. 14, no. 7817 (2023).
5. Gadd, D. A., Hillary, R. F., McCartney, D. L., et al. Epigenetic scores for the circulating proteome as tools for disease prediction. eLife, vol. 11 (2022).
6. Folkersen, L., Gustafsson, S., Wang, Q., et al. Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals. Nature Metabolism, vol. 2, no. 10, 1135–1148 (2020).