Longitudinal plasma protein profiling of newly diagnosed type 2 diabetes.

Gummesson A, Björnson E, Fagerberg L, Zhong W, Tebani A, Edfors F, Schmidt C, Lundqvist A, Adiels M, Bäckhed F, Schwenk JM, Jansson P, Uhlén M, Bergström G

EBioMedicine 63 (-) 103147 [2020-12-03; online 2020-12-03]

Comprehensive proteomics profiling may offer new insights into the dysregulated metabolic milieu of type 2 diabetes, and in the future, serve as a useful tool for personalized medicine. This calls for a better understanding of circulating protein patterns at the early stage of type 2 diabetes as well as the dynamics of protein patterns during changes in metabolic status. To elucidate the systemic alterations in early-stage diabetes and to investigate the effects on the proteome during metabolic improvement, we measured 974 circulating proteins in 52 newly diagnosed, treatment-naïve type 2 diabetes subjects at baseline and after 1 and 3 months of guideline-based diabetes treatment, while comparing their protein profiles to that of 94 subjects without diabetes. Early stage type 2 diabetes was associated with distinct protein patterns, reflecting key metabolic syndrome features including insulin resistance, adiposity, hyperglycemia and liver steatosis. The protein profiles at baseline were attenuated during guideline-based diabetes treatment and several plasma proteins associated with metformin medication independently of metabolic variables, such as circulating EPCAM. The results advance our knowledge about the biochemical manifestations of type 2 diabetes and suggest that comprehensive protein profiling may serve as a useful tool for metabolic phenotyping and for elucidating the biological effects of diabetes treatments. This work was supported by the Swedish Heart and Lung Foundation, the Swedish Research Council, the Erling Persson Foundation, the Knut and Alice Wallenberg Foundation, and the Swedish state under the agreement between the Swedish government and the county councils (ALF-agreement).

Affinity Proteomics Stockholm [Collaborative]

Bioinformatics Compute and Storage [Service]

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PubMed 33279861

DOI 10.1016/j.ebiom.2020.103147

Crossref 10.1016/j.ebiom.2020.103147

pii: S2352-3964(20)30523-5