The blood proteome as a window into human health and disease

QC 2026-04-28

Abstract

The circulating proteome is a dynamic and accessible window into the biological state of the human body, reflecting its physiological and pathological processes. Advances in technologies to measure the plasma proteome now enable the measurement of thousands of proteins at population scale, opening new opportunities for the discovery of clinically relevant and minimally invasive biomarkers. These approaches hold promise for improving disease detection, patient stratification, and disease monitoring, positioning plasma proteomics at the forefront of precision medicine. Key to these advances are bioinformatic methods that identify candidate proteins associated with specific health and disease states from high-dimensional datasets. Despite the efforts combining large-scale proteomics with computational analyses, relatively few biomarkers have translated into clinical practice. This highlights the need for investigations that incorporate diverse cohorts and expand on classic comparisons against healthy controls, alongside an increased focus on validation strategies.

This thesis contributes to biomarker discovery by broadening the biological contexts that are profiled and compared. The first studies focus on cancer, starting by predicting the presence of cancer in patients with non-specific symptoms in Paper I, and identifying a protein panel able to distinguish between twelve cancer types in Paper II. Building on these findings, Paper III provides a deeper perspective of the circulating proteome across healthy individuals, during development, adulthood and aging, and a wide range of diseases. This is followed by Paper IV, which focuses on comparing the two main affinity proteomics platforms by assessing their complementarity and applicability in biomarker studies. Finally, the analysis of these large-scale datasets led to the development of streamlined bioinformatics pipelines, which are presented as an open-access package in Paper V.

Together, this work illustrates the potential of combining affinity proteomics with bioinformatics pipelines to profile the circulating proteome and derive biological insights. This thesis focuses on pan-disease comparisons, evaluates the complementarity of affinity proteomics platforms, and highlights the importance of reproducible biomarker discovery workflows. Developed within the framework of the Human Disease Blood Resource, the resulting data and insights are integrated into the Human Protein Atlas (www.proteinatlas.org), providing a resource for precision medicine research.

Link to DiVA