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.

liver

protein interaction networks

models

genome-scale

Endocrinology & Metabolism

metabolic

sensitivity

glucose-tolerance

n-glycosylation

network

amino-acid

Cell Biology

adipose-tissue

Författare

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, Biologi och bioteknik, Systembiologi

Göteborgs universitet

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, Biologi och bioteknik, Systembiologi

Ulf Smith

Göteborgs universitet

M. J. Serlie

Academic Medical Centre, University of Amsterdam

Jan Borén

Göteborgs universitet

Adil Mardinoglu

Chalmers, Biologi och bioteknik, Systembiologi

Cell Metabolism

1550-4131 (ISSN)

Vol. 24 1 172-184

Ämneskategorier (SSIF 2011)

Endokrinologi och diabetes

Cellbiologi

Styrkeområden

Livsvetenskaper och teknik (2010-2018)

DOI

10.1016/j.cmet.2016.05.026

PubMed

27345421

Mer information

Skapat

2017-10-07