Your browser doesn't support javascript.
loading
A Multidimensional Bioinformatic Platform for the Study of Human Response to Surgery.
Eckhoff, Austin M; Connor, Ashton A; Thacker, Julie K M; Blazer, Dan G; Moore, Harvey G; Scheri, Randall P; Lagoo-Deenadayalan, Sandhya A; Harpole, David H; Seymour, Keri A; Purves, J Todd; Ravindra, Kadiyala V; Southerland, Kevin W; Rocke, Daniel J; Gilner, Jennifer B; Parker, Daniel C; Bain, James R; Muehlbauer, Michael J; Ilkayeva, Olga R; Corcoran, David L; Modliszewski, Jennifer L; Devos, Nicolas; Foster, Matthew W; Moseley, M Arthur; Dressman, Holly K; Chan, Cliburn; Huebner, Janet L; Chasse, Scott; Stempora, Linda; Aschenbrenner, Mary E; Joshi, Mary-Beth; Hollister, Beth; Henao, Ricardo; Barfield, Richard T; Ellison, Mark A; Bailey, Sean; Woody, Stephen; Huang, Erich S; Kirk, Allan; Hwang, E Shelley.
Affiliation
  • Eckhoff AM; Department of Surgery, Duke University; Durham, NC.
  • Connor AA; Department of Surgery, Duke University; Durham, NC.
  • Thacker JKM; Department of Surgery, Duke University; Durham, NC.
  • Blazer DG; Department of Surgery, Duke University; Durham, NC.
  • Moore HG; Department of Surgery, Duke University; Durham, NC.
  • Scheri RP; Department of Surgery, Duke University; Durham, NC.
  • Lagoo-Deenadayalan SA; Department of Surgery, Duke University; Durham, NC.
  • Harpole DH; Department of Surgery, Duke University; Durham, NC.
  • Seymour KA; Department of Surgery, Duke University; Durham, NC.
  • Purves JT; Department of Surgery, Duke University; Durham, NC.
  • Ravindra KV; Department of Surgery, Duke University; Durham, NC.
  • Southerland KW; Department of Surgery, Duke University; Durham, NC.
  • Rocke DJ; Department of Head and Neck Surgery & Communication Sciences, Duke University; Durham, NC.
  • Gilner JB; Department of Obstetrics and Gynecology, Duke University; Durham, NC.
  • Parker DC; Department of Medicine, Duke University; Durham, NC.
  • Bain JR; Department of Medicine, Duke University; Durham, NC.
  • Muehlbauer MJ; Duke Molecular Physiology Institute, Duke University; Durham, NC.
  • Ilkayeva OR; Duke Molecular Physiology Institute, Duke University; Durham, NC.
  • Corcoran DL; Department of Medicine, Duke University; Durham, NC.
  • Modliszewski JL; Duke Molecular Physiology Institute, Duke University; Durham, NC.
  • Devos N; Duke Center for Genomic and Computational Biology, Duke University; Durham, NC.
  • Foster MW; Duke Center for Genomic and Computational Biology, Duke University; Durham, NC.
  • Moseley MA; Duke Center for Genomic and Computational Biology, Duke University; Durham, NC.
  • Dressman HK; Department of Medicine, Duke University; Durham, NC.
  • Chan C; Duke Center for Genomic and Computational Biology, Duke University; Durham, NC.
  • Huebner JL; Duke Center for Genomic and Computational Biology, Duke University; Durham, NC.
  • Chasse S; Department of Molecular Genetics and Microbiology, Duke University; Durham, NC.
  • Stempora L; Duke Center for Genomic and Computational Biology, Duke University; Durham, NC.
  • Aschenbrenner ME; Department of Medicine, Duke University; Durham, NC.
  • Joshi MB; Department of Surgery, Duke University; Durham, NC.
  • Hollister B; Department of Surgery, Duke University; Durham, NC.
  • Henao R; Department of Surgery, Duke University; Durham, NC.
  • Barfield RT; Department of Surgery, Duke University; Durham, NC.
  • Ellison MA; Department of Surgery, Duke University; Durham, NC.
  • Bailey S; Department of Electrical and Computer Engineering, Duke University; Durham, NC.
  • Woody S; Department of Biostatistics and Bioinformatics, Duke University; Durham, NC.
  • Huang ES; Department of Surgery, Duke University; Durham, NC.
  • Kirk A; Department of Surgery, Duke University; Durham, NC.
  • Hwang ES; Department of Medicine, Duke University; Durham, NC.
Ann Surg ; 275(6): 1094-1102, 2022 06 01.
Article in En | MEDLINE | ID: mdl-35258509
OBJECTIVE: To design and establish a prospective biospecimen repository that integrates multi-omics assays with clinical data to study mechanisms of controlled injury and healing. BACKGROUND: Elective surgery is an opportunity to understand both the systemic and focal responses accompanying controlled and well-characterized injury to the human body. The overarching goal of this ongoing project is to define stereotypical responses to surgical injury, with the translational purpose of identifying targetable pathways involved in healing and resilience, and variations indicative of aberrant peri-operative outcomes. METHODS: Clinical data from the electronic medical record combined with large-scale biological data sets derived from blood, urine, fecal matter, and tissue samples are collected prospectively through the peri-operative period on patients undergoing 14 surgeries chosen to represent a range of injury locations and intensities. Specimens are subjected to genomic, transcriptomic, proteomic, and metabolomic assays to describe their genetic, metabolic, immunologic, and microbiome profiles, providing a multidimensional landscape of the human response to injury. RESULTS: The highly multiplexed data generated includes changes in over 28,000 mRNA transcripts, 100 plasma metabolites, 200 urine metabolites, and 400 proteins over the longitudinal course of surgery and recovery. In our initial pilot dataset, we demonstrate the feasibility of collecting high quality multi-omic data at pre- and postoperative time points and are already seeing evidence of physiologic perturbation between timepoints. CONCLUSIONS: This repository allows for longitudinal, state-of-the-art geno-mic, transcriptomic, proteomic, metabolomic, immunologic, and clinical data collection and provides a rich and stable infrastructure on which to fuel further biomedical discovery.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computational Biology / Proteomics Type of study: Observational_studies Limits: Humans Language: En Journal: Ann Surg Year: 2022 Document type: Article Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computational Biology / Proteomics Type of study: Observational_studies Limits: Humans Language: En Journal: Ann Surg Year: 2022 Document type: Article Country of publication: