Abstract

The need for precision medicine approaches to monitor health and disease makes it important to develop sensitive and accurate assays for proteome profiles in blood. Here, we describe an approach for plasma profiling based on proximity extension assay combined with next generation sequencing. First, we analyze the variability of plasma profiles between and within healthy individuals in a longitudinal wellness study, including the influence of genetic variations on plasma levels. Second, we follow patients newly diagnosed with type 2 diabetes before and during therapeutic intervention using plasma proteome profiling. The studies show that healthy individuals have a unique and stable proteome profile and indicate that a panel of proteins could potentially be used for early diagnosis of diabetes, including stratification of patients with regards to response to metformin treatment. Although validation in larger cohorts is needed, the analysis demonstrates the usefulness of comprehensive plasma profiling for precision medicine efforts.

The proximity extension assay (PEA) is a popular tool to measure plasma protein levels. Here, the authors extend the proteome coverage of PEA by combining it with next-generation sequencing, enabling the analysis of nearly 1500 proteins from minute amounts of plasma.

Details

Title
Next generation plasma proteome profiling to monitor health and disease
Author
Zhong Wen 1   VIAFID ORCID Logo  ; Edfors Fredrik 1   VIAFID ORCID Logo  ; Gummesson Anders 2   VIAFID ORCID Logo  ; Bergström Göran 3 ; Fagerberg Linn 1   VIAFID ORCID Logo  ; Uhlén Mathias 4   VIAFID ORCID Logo 

 KTH-Royal Institute of Technology, Science for Life Laboratory, Department of Protein Science, Stockholm, Sweden (GRID:grid.5037.1) (ISNI:0000000121581746) 
 Gothenburg University, Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Gothenburg, Sweden (GRID:grid.8761.8) (ISNI:0000 0000 9919 9582); Sahlgrenska University Hospital, Region Västra Götaland, Department of Clinical Genetics and Genomics, Gothenburg, Sweden (GRID:grid.1649.a) (ISNI:000000009445082X) 
 Gothenburg University, Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Gothenburg, Sweden (GRID:grid.8761.8) (ISNI:0000 0000 9919 9582); Sahlgrenska University Hospital, Region Västra Götaland, Department of Clinical Physiology, Gothenburg, Sweden (GRID:grid.1649.a) (ISNI:000000009445082X) 
 KTH-Royal Institute of Technology, Science for Life Laboratory, Department of Protein Science, Stockholm, Sweden (GRID:grid.5037.1) (ISNI:0000000121581746); Karolinska Institutet, Department of Neuroscience, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2521266066
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.