Fredrik Edfors

DDLS Fellow, KTH

Key publications

Next generation plasma proteome profiling to monitor health and disease, Zhong, Wen and Edfors, Fredrik and Gummesson, Anders and Bergström, Göran and Fagerberg, Linn and Uhlén, Mathias}, Nature communications, volume 12, number 1, pages 1-12, year 2021, publisher Nature Publishing Group.

Rapid and sensitive detection of SARS-CoV-2 infection using quantitative peptide enrichment LC-MS analysis, Hober, Andreas and Tran-Minh, Khue Hua and Foley, Dominic and McDonald, Thomas and Vissers, Johannes PC and Pattison, Rebecca and Ferries, Samantha and Hermansson, Sigurd and Betner, Ingvar and Uhlen, Mathias and others, Elife, volume 10, 2021

Next generation plasma proteome profiling of COVID-19 patients with mild to moderate symptoms, Zhong, Wen and Altay, Ozlem and Arif, Muhammad and Edfors, Fredrik and Doganay, Levent and Mardinoglu, Adil and Uhlen, Mathias and Fagerberg, Linn, EBioMedicine, volume 74, 2021

Targeted proteomics analysis of plasma proteins using recombinant protein standards for addition only workflows, Kotol, David and Hober, Andreas and Strandberg, Linnéa and Svensson, Anne-Sophie and Uhlén, Mathias and Edfors, Fredrik, BioTechniques, volume 71, 2021

Proteomics in thrombosis research, Edfors, Fredrik and Iglesias, Maria Jesus and Butler, Lynn M and Odeberg, Jacob, Research and Practice in Thrombosis and Haemostasis, volume 6, 2022

Fredrik Edfors

My group is analyzing data from different proteomics technologies capable of characterizing the deep plasma proteome. The combination of data generated by data-independent mass spectrometry and affinity-based technologies enables us to annotate molecular signals and detect changes from a patient’s baseline.

This can be by integrating molecular and clinical data for translational research and diagnostic development, simplifying tailored patient treatment. The focus lies on liquid biopsies and how we may use this information to map the molecular landscape of health and disease. We can improve patient stratification by combining data from mass spectrometry and affinity-based approaches, which are often driven by longitudinal monitoring of an individual’s baseline. My research has focused on the dynamic proteome of individuals and how we might use blood indicators to develop improved prediction models. This data integration strategy and analysis can be utilized for patient stratification, diagnostic biomarker identification, and longitudinal monitoring and follow-up.


Last updated: 2024-07-03

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