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.
liver
protein interaction networks
models
genome-scale
Endocrinology & Metabolism
metabolic
sensitivity
glucose-tolerance
n-glycosylation
network
amino-acid
Cell Biology
adipose-tissue
Author
SangWook Lee
The Royal Institute of Technology (KTH)
C. Zhang
The Royal Institute of Technology (KTH)
M. Kilicarslan
Academic Medical Centre, University of Amsterdam
B. D. Piening
Stanford University
Elias Björnson
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
University of Gothenburg
B. M. Hallstrom
The Royal Institute of Technology (KTH)
A. K. Groen
University of Groningen, University Medical Center Groningen
E. Ferrannini
Istituto di Fisiologia Clinica del CNR
M. Laakso
Ita-Suomen yliopisto
M. Snyder
Stanford University
M. Bluher
Universitat Leipzig
M. Uhlen
The 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
Academic Medical Centre, 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 1 172-184Subject Categories (SSIF 2011)
Endocrinology and Diabetes
Cell Biology
Areas of Advance
Life Science Engineering (2010-2018)
DOI
10.1016/j.cmet.2016.05.026
PubMed
27345421