• Austin M Eckhoff, Ashton A Connor, ThackerJulie K MJKMDepartment of Surgery, Duke University; Durham, NC., Dan G Blazer, Harvey G Moore, Randall P Scheri, Sandhya A Lagoo-Deenadayalan, David H Harpole, Keri A Seymour, J Todd Purves, Kadiyala V Ravindra, Kevin W Southerland, Daniel J Rocke, Jennifer B Gilner, Daniel C Parker, James R Bain, Michael J Muehlbauer, Olga R Ilkayeva, David L Corcoran, Jennifer L Modliszewski, Nicolas Devos, Matthew W Foster, M Arthur Moseley, Holly K Dressman, Cliburn Chan, Janet L Huebner, Scott Chasse, Linda Stempora, Mary E Aschenbrenner, Mary-Beth Joshi, Beth Hollister, Ricardo Henao, Richard T Barfield, Mark A Ellison, Sean Bailey, Stephen Woody, Erich S Huang, Allan Kirk, and E Shelley Hwang.
• Department of Surgery, Duke University; Durham, NC.
• Ann. Surg. 2022 Jun 1; 275 (6): 109411021094-1102.

ObjectiveTo design and establish a prospective biospecimen repository that integrates multi-omics assays with clinical data to study mechanisms of controlled injury and healing.BackgroundElective 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.MethodsClinical 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.ResultsThe 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.ConclusionsThis 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.Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.

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