Integrated Network Analysis Reveals an Association between Plasma Mannose Levels and Insulin Resistance.
Integrated Network Analysis Reveals an Association between Plasma Mannose Levels and Insulin Resistance.
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DOI：
10.1016/j.cmet.2016.05.026
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发表时间：
2016-07-12
期刊：
影响因子：
29
通讯作者：
Mardinoglu A
中科院分区：
文献类型：
--
作者：
Lee S;Zhang C;Kilicarslan M;Piening BD;Bjornson E;Hallström BM;Groen AK;Ferrannini E;Laakso M;Snyder M;Blüher M;Uhlen M;Nielsen J;Smith U;Serlie MJ;Boren J;Mardinoglu A
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. Lee et al. merged genome-scale metabolic models (GEMs), transcriptional regulatory networks (TRNs), and protein-protein interaction networks (PPINs) to generate cell-specific integrated networks for hepatocytes, myocytes, and adipocytes of lean and obese subjects undergoing bariatric surgery. They identified, and independently validated, plasma mannose as highly associated with insulin resistance, independent of BMI.
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影响因子：
16.6
作者：
Hyötyläinen T;Jerby L;Petäjä EM;Mattila I;Jäntti S;Auvinen P;Gastaldelli A;Yki-Järvinen H;Ruppin E;Orešič M
通讯作者：
Orešič M
影响因子：
3.4
作者：
Li, Xu;Wang, Wenqi;Chen, Junjie
通讯作者：
Chen, Junjie
影响因子：
30.8
作者：
John S;Sabo PJ;Thurman RE;Sung MH;Biddie SC;Johnson TA;Hager GL;Stamatoyannopoulos JA
通讯作者：
Stamatoyannopoulos JA
影响因子：
8.8
作者：
Bjornson, Elias;Mukhopadhyay, Bani;Mardinoglu, Adil
通讯作者：
Mardinoglu, Adil
影响因子：
3.9
作者：
MAGNANI, M;STOCCHI, V;FORNAINI, G
通讯作者：
FORNAINI, G