Integrated Network Analysis Reveals an Association between Plasma Mannose Levels and Insulin Resistance
Journal article, 2016

To investigate the biological processes that are altered in obese subjects, we generated cell-specific integrated networks (INs) by merging genome-scale metabolic, transcriptional regulatory and protein-protein interaction networks. We performed genome-wide transcriptomics analysis to determine the global gene expression changes in the liver and three adipose tissues from obese subjects undergoing bariatric surgery and integrated these data into the cell-specific INs. We found dysregulations in mannose metabolism in obese subjects and validated our predictions by detecting mannose levels in the plasma of the lean and obese subjects. We observed significant correlations between plasma mannose levels, BMI, and insulin resistance (IR). We also measured plasma mannose levels of the subjects in two additional different cohorts and observed that an increased plasma mannose level was associated with IR and insulin secretion. We finally identified mannose as one of the best plasma metabolites in explaining the variance in obesity-independent IR.

protein interaction networks

liver

amino-acid

glucose-tolerance

n-glycosylation

Cell Biology

sensitivity

metabolic

Endocrinology & Metabolism

models

network

adipose-tissue

genome-scale

Author

SangWook Lee

Royal Institute of Technology (KTH)

C. Zhang

Royal Institute of Technology (KTH)

M. Kilicarslan

University of Amsterdam

B. D. Piening

Stanford University

Elias Björnson

University of Gothenburg

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

B. M. Hallstrom

Royal Institute of Technology (KTH)

A. K. Groen

University of Groningen

E. Ferrannini

Istituto di Fisiologia Clinica del CNR

M. Laakso

University of Eastern Finland

M. Snyder

Stanford University

M. Bluher

Leipzig University

M. Uhlen

Royal Institute of Technology (KTH)

Jens B Nielsen

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Ulf Smith

University of Gothenburg

M. J. Serlie

University of Amsterdam

Jan Borén

University of Gothenburg

Adil Mardinoglu

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Cell Metabolism

1550-4131 (ISSN)

Vol. 24 1 172-184

Subject Categories

Endocrinology and Diabetes

Cell Biology

Areas of Advance

Life Science Engineering

DOI

10.1016/j.cmet.2016.05.026

PubMed

27345421

More information

Latest update

5/4/2018 1