Blood Protein Tests Could Identify Distinct Molecular Fingerprints of Multiple Diseases
Posted on 20 Oct 2025
Accurately distinguishing disease-related molecular changes from common biological variations has long been a challenge in clinical diagnostics, often leading to false alarms in blood test results. Many biomarkers linked to cancer, cardiovascular, or autoimmune diseases also fluctuate during infections or inflammation, making it difficult to isolate disease-specific signals. Now, a new large-scale analysis has mapped how thousands of blood proteins change across multiple diseases and life stages, offering a clearer molecular fingerprint for health, disease, and aging. The mapping of molecular fingerprints of disease paves the way for the development of diagnostic blood tests for clinical use.
The research, conducted by an international team led by KTH Royal Institute of Technology (Stockholm, Sweden) and SciLifeLab (Stockholm, Sweden), produced a comprehensive resource called the Human Disease Blood Atlas. This pan-disease atlas maps protein changes linked to 59 diseases and tracks how an individual’s blood profile evolves from childhood to adulthood. Using machine learning, the team identified molecular signatures unique to specific diseases while separating universal inflammation-related signals to build reliable blood panels.

The study, published in Science, revealed that blood protein profiles contain highly individualized molecular patterns that stabilize in adulthood but change markedly during disease progression. The analysis revealed that many proteins elevated in cancer or autoimmune conditions also increase in infections, indicating shared inflammatory pathways. However, the side-by-side comparison allowed researchers to focus on truly disease-specific markers, clustering conditions like liver-related diseases by organ system.
The atlas helps resolve a major reproducibility issue in biomarker research, where most studies compare disease samples against generic healthy controls. By analyzing multiple diseases side by side, the researchers pinpointed truly disease-specific markers and common molecular patterns that could serve as universal diagnostic, prognostic or therapeutic targets. The findings also suggest that shifts in specific protein profiles may precede a cancer diagnosis, supporting future research on proteomics-based early detection.
“By comparing these diseases side by side, we can separate universal false alarm bells of inflammation from truly disease-specific signals,” said Mathias Uhlén, Professor at Stockholm’s KTH Royal Institute of Technology and the director of the Human Protein Atlas project. “The mapping of molecular fingerprints of disease is a crucial step for building blood tests that work in the clinic.”
Related Links:
KTH Royal Institute of Technology
SciLifeLab