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

• Published in: EBioMedicine Vol. 28; no. C; pp. 234 - 240
• Main Authors: Li, Qing-Run, Wang, Zi-Ming, Wewer Albrechtsen, Nicolai J., Wang, Dan-Dan, Su, Zhi-Duan, Gao, Xian-Fu, Wu, Qing-Qing, Zhang, Hui-Ping, Zhu, Li, Li, Rong-Xia, Jacobsen, SivHesse, Jørgensen, Nils Bruun, Dirksen, Carsten, Bojsen-Møller, Kirstine N., Petersen, Jacob S., Madsbad, Sten, Clausen, Trine R., Diderichsen, Børge, Chen, Luo-Nan, Holst, Jens J., Zeng, Rong, Wu, Jia-Rui
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.02.2018; Elsevier
• Subjects: Advanced Basic Science; Blood Proteins - metabolism; Diabetes; Diabetes Mellitus, Type 2 - blood; Diabetes Mellitus, Type 2 - surgery; Gastric Bypass; Gastric bypass surgery; Gene Regulatory Networks; Humans; Internal Medicine; Metabolome; Network; Network biomarker; Obesity - genetics; Principal Component Analysis; Research Paper; Systems Biology; Weight Loss; Gastric bypass surgery; Network biomarker; Diabetes; Systems biology; Network
• ISSN: 2352-3964; 2352-3964
• DOI: 10.1016/j.ebiom.2018.01.018

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. •Plasma proteomic and metabolomic datasets were collected with time-series mode in patients treated with RYGB.•Workflow to define the physiological states based on associations between biomolecules•Systems signatures reveal unique path for diabetes remission independent of weight loss.