title: Metabolic phenotype-microRNA data fusion analysis of the systemic consequences of Roux-en-Y gastric bypass surgery.
abstract: OBJECTIVE
  Bariatric surgery offers sustained marked weight loss and often remission of type 2 diabetes, yet the mechanisms of establishment of these health benefits are not clear.
  
  
  METHODS
  We mapped the coordinated systemic responses of gut hormones, the circulating miRNAome and the metabolome in a rat model of Roux-en-Y gastric bypass (RYGB) surgery.
  
  
  RESULTS
  The response of circulating microRNAs (miRNAs) to RYGB was striking and selective. Analysis of 14 significantly altered circulating miRNAs within a pathway context was suggestive of modulation of signaling pathways including G protein signaling, neurodegeneration, inflammation, and growth and apoptosis responses. Concomitant alterations in the metabolome indicated increased glucose transport, accelerated glycolysis and inhibited gluconeogenesis in the liver. Of particular significance, we show significantly decreased circulating miRNA-122 levels and a more modest decline in hepatic levels, following surgery. In mechanistic studies, manipulation of miRNA-122 levels in a cell model induced changes in the activity of key enzymes involved in hepatic energy metabolism, glucose transport, glycolysis, tricarboxylic acid cycle, pentose phosphate shunt, fatty-acid oxidation and gluconeogenesis, consistent with the findings of the in vivo surgery-mediated responses, indicating the powerful homeostatic activity of the miRNAs.
  
  
  CONCLUSIONS
  The close association between energy metabolism, neuronal signaling and gut microbial metabolites derived from the circulating miRNA, plasma, urine and liver metabolite and gut hormone correlations further supports an enhanced gut-brain signaling, which we suggest is hormonally mediated by both traditional gut hormones and miRNAs. This transomic approach to map the crosstalk between the circulating miRNAome and metabolome offers opportunities to understand complex systems biology within a disease and interventional treatment setting.
authors.affiliation: Division of Computational and Systems Medicine, Department of Surgery and Cancer Imperial College London, South Kensington, London, UK.
authors.forename: Q
authors.initials: Q
authors.lastname: Wu
authors.affiliation: 1] Division of Computational and Systems Medicine, Department of Surgery and Cancer Imperial College London, South Kensington, London, UK [2] Center for Digestive and Gut Health, Institute of Global Health Innovation, Imperial College London, London, UK.
authors.forename: J V
authors.initials: JV
authors.lastname: Li
authors.affiliation: Department of General and Visceral, Vascular and Pediatric Surgery, University Hospital of Würzburg, Würzburg, Germany.
authors.forename: F
authors.initials: F
authors.lastname: Seyfried
authors.affiliation: 1] Diabetes Complications Research Centre, Pathology, Conway Institute, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland [2] Investigative Science, Imperial College London, London, UK.
authors.forename: C W
authors.initials: CW
authors.lastname: le Roux
authors.affiliation: Division of Computational and Systems Medicine, Department of Surgery and Cancer Imperial College London, South Kensington, London, UK.
authors.forename: H
authors.initials: H
authors.lastname: Ashrafian
authors.affiliation: Division of Computational and Systems Medicine, Department of Surgery and Cancer Imperial College London, South Kensington, London, UK.
authors.forename: T
authors.initials: T
authors.lastname: Athanasiou
authors.affiliation: Department of General and Visceral, Vascular and Pediatric Surgery, University Hospital of Würzburg, Würzburg, Germany.
authors.forename: W
authors.initials: W
authors.lastname: Fenske
authors.affiliation: Division of Computational and Systems Medicine, Department of Surgery and Cancer Imperial College London, South Kensington, London, UK.
authors.forename: A
authors.initials: A
authors.lastname: Darzi
authors.affiliation: 1] Division of Computational and Systems Medicine, Department of Surgery and Cancer Imperial College London, South Kensington, London, UK [2] Center for Digestive and Gut Health, Institute of Global Health Innovation, Imperial College London, London, UK.
authors.forename: J K
authors.initials: JK
authors.lastname: Nicholson
authors.affiliation: 1] Division of Computational and Systems Medicine, Department of Surgery and Cancer Imperial College London, South Kensington, London, UK [2] Center for Digestive and Gut Health, Institute of Global Health Innovation, Imperial College London, London, UK.
authors.forename: E
authors.initials: E
authors.lastname: Holmes
authors.affiliation: Division of Computational and Systems Medicine, Department of Surgery and Cancer Imperial College London, South Kensington, London, UK.
authors.forename: N J
authors.initials: NJ
authors.lastname: Gooderham
mesh_terms: D000713:Anastomosis, Roux-en-Y / Q000379:methods*; D000818:Animals; D001786:Blood Glucose; D004195:Disease Models, Animal; D004734:Energy Metabolism; D005768:Gastrointestinal Hormones / Q000378:metabolism*; D008297:Male; D035683:MicroRNAs / Q000378:metabolism*; D009479:Neuropeptides / Q000378:metabolism*; D009765:Obesity / Q000378:metabolism*; D010641:Phenotype; D051381:Rats; D017207:Rats, Sprague-Dawley; D015398:Signal Transduction; D015431:Weight Loss
chemical_list: D001786:Blood Glucose; D005768:Gastrointestinal Hormones; D035683:MicroRNAs; D009479:Neuropeptides