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Cell Metab. 2016 Jul 12;24(1):172-84. doi: 10.1016/j.cmet.2016.05.026. Epub 2016 Jun 23.

Integrated Network Analysis Reveals an Association between Plasma Mannose Levels and Insulin Resistance.

Author information

1
Science for Life Laboratory, KTH-Royal Institute of Technology, 171 21 Stockholm, Sweden.
2
Department of Endocrinology and Metabolism, University of Amsterdam, Academic Medical Center, 1105 Amsterdam, the Netherlands.
3
Department of Genetics, Stanford University, 300 Pasteur Drive, M-344, Stanford, CA 94305, USA.
4
Department of Biology and Biological Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden; Department of Molecular and Clinical Medicine, University of Gothenburg, 405 30 Gothenburg, Sweden.
5
Department of Pediatrics, Center for Liver Digestive and Metabolic Diseases, University of Groningen, University Medical Center Groningen, 9713 Groningen, the Netherlands.
6
C.N.R. Institute of Clinical Physiology, 56124 Pisa, Italy.
7
Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, 70210 Kuopio, Finland.
8
Department of Medicine, University of Leipzig, 04109 Leipzig, Germany.
9
Science for Life Laboratory, KTH-Royal Institute of Technology, 171 21 Stockholm, Sweden; Department of Biology and Biological Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden.
10
Department of Molecular and Clinical Medicine, University of Gothenburg, 405 30 Gothenburg, Sweden; Lundberg Laboratory for Diabetes Research, Sahlgrenska Academy at the University of Gothenburg, 405 30 Gothenburg, Sweden.
11
Department of Molecular and Clinical Medicine, University of Gothenburg, 405 30 Gothenburg, Sweden.
12
Science for Life Laboratory, KTH-Royal Institute of Technology, 171 21 Stockholm, Sweden; Department of Biology and Biological Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden. Electronic address: adilm@scilifelab.se.

Abstract

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.

KEYWORDS:

genome-scale metabolic models; insulin resistance; mannose; obesity; protein-protein interaction networks; transcriptional regulatory networks

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PMID:
27345421
DOI:
10.1016/j.cmet.2016.05.026
[Indexed for MEDLINE]
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