EBioMedicine (Feb 2018)

Systems Signatures Reveal Unique Remission-path of Type 2 Diabetes Following Roux-en-Y Gastric Bypass Surgery

  • Qing-Run Li,
  • Zi-Ming Wang,
  • Nicolai J. Wewer Albrechtsen,
  • Dan-Dan Wang,
  • Zhi-Duan Su,
  • Xian-Fu Gao,
  • Qing-Qing Wu,
  • Hui-Ping Zhang,
  • Li Zhu,
  • Rong-Xia Li,
  • SivHesse Jacobsen,
  • Nils Bruun Jørgensen,
  • Carsten Dirksen,
  • Kirstine N. Bojsen-Møller,
  • Jacob S. Petersen,
  • Sten Madsbad,
  • Trine R. Clausen,
  • Børge Diderichsen,
  • Luo-Nan Chen,
  • Jens J. Holst,
  • Rong Zeng,
  • Jia-Rui Wu

DOI
https://doi.org/10.1016/j.ebiom.2018.01.018
Journal volume & issue
Vol. 28, no. C
pp. 234 – 240

Abstract

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Roux-en-Y Gastric bypass surgery (RYGB) is emerging as a powerful tool for treatment of obesity and may also cause remission of type 2 diabetes. However, the molecular mechanism of RYGB leading to diabetes remission independent of weight loss remains elusive. In this study, we profiled plasma metabolites and proteins of 10 normal glucose-tolerant obese (NO) and 9 diabetic obese (DO) patients before and 1-week, 3-months, 1-year after RYGB. 146 proteins and 128 metabolites from both NO and DO groups at all four stages were selected for further analysis. By analyzing a set of bi-molecular associations among the corresponding network of the subjects with our newly developed computational method, we defined the represented physiological states (called the edge-states that reflect the interactions among the bio-molecules), and the related molecular networks of NO and DO patients, respectively. The principal component analyses (PCA) revealed that the edge states of the post-RYGB NO subjects were significantly different from those of the post-RYGB DO patients. Particularly, the time-dependent changes of the molecular hub-networks differed between DO and NO groups after RYGB. In conclusion, by developing molecular network-based systems signatures, we for the first time reveal that RYGB generates a unique path for diabetes remission independent of weight loss.

Keywords