Integrated Network Analysis Reveals an Association between Plasma Mannose Levels and Insulin Resistance
Artikel i vetenskaplig tidskrift, 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.
Cell Biology
network
liver
n-glycosylation
protein interaction networks
amino-acid
Endocrinology & Metabolism
glucose-tolerance
models
adipose-tissue
sensitivity
metabolic
genome-scale
Författare
SangWook Lee
Kungliga Tekniska Högskolan (KTH)
C. Zhang
Kungliga Tekniska Högskolan (KTH)
M. Kilicarslan
Universiteit Van Amsterdam
B. D. Piening
Stanford University
Elias Björnson
Göteborgs universitet
Chalmers, Biologi och bioteknik, Systembiologi
B. M. Hallstrom
Kungliga Tekniska Högskolan (KTH)
A. K. Groen
Rijksuniversiteit Groningen
E. Ferrannini
Consiglio Nazionale delle Ricerche (CNR)
M. Laakso
Itä-Suomen Yliopisto
M. Snyder
Stanford University
M. Bluher
Universität Leipzig
M. Uhlen
Kungliga Tekniska Högskolan (KTH)
Jens B Nielsen
Chalmers, Biologi och bioteknik, Systembiologi
Ulf Smith
Göteborgs universitet
M. J. Serlie
Universiteit Van Amsterdam
Jan Borén
Göteborgs universitet
Adil Mardinoglu
Chalmers, Biologi och bioteknik, Systembiologi
Cell Metabolism
1550-4131 (ISSN) 19327420 (eISSN)
Vol. 24 1 172-184Ämneskategorier (SSIF 2011)
Endokrinologi och diabetes
Cellbiologi
Styrkeområden
Livsvetenskaper och teknik (2010-2018)
DOI
10.1016/j.cmet.2016.05.026
PubMed
27345421