Recent advancements in proteomics technologies have made it possible to analyze thousands of blood proteins across thousands of samples, significantly enhancing expectations for breakthroughs in precision medicine. However, despite the influx of new molecular health data, distinguishing observational associations from actionable links remains crucial for translating this new knowledge into clinically relevant information about human biology.
This presentation details our research approaches to the dynamic architecture of circulating proteins as they can be associated with various human phenotypes, health status, and disease risks. The talk will also present our work studying the impact of medication use on these data. Beyond the established biobanks of liquids, we will discuss the innovative approach of self-sampling blood, enabling the exploration of population health beyond traditional hospital environments. This "new" sample type can simplify continuous blood collection at home, offering new immune and health monitoring opportunities.
For proteomics-informed precision medicine to be realized, future efforts must prioritize improved management of pre-analytical factors, a deeper understanding of technology-centric insights, and greater emphasis on the conditions of donors at the time of sampling. As multi-modal data from novel study designs and diverse sample types emerge, there is a pressing need for data-driven approaches to learn from the community data and effectively address the heterogeneity present at baseline and throughout the longitudinal monitoring of phenotypes.