title: Individual-specific principal component analysis of circulating inflammatory mediators predicts early organ dysfunction in trauma patients.
abstract: We hypothesized that early inflammation can drive, or impact, later multiple organ dysfunction syndrome (MODS), that patient-specific principal component analysis (PCA) of circulating inflammatory mediators could reveal conserved dynamic responses which would not be apparent from the unprocessed data, and that this computational approach could segregate trauma patients with regard to subsequent MODS.
  
  
  
  From a cohort of 472 blunt trauma survivors, 2 separate subcohorts of moderately/severely injured patients were studied. Multiple inflammatory mediators were assessed in serial blood samples in the first 24 hours postinjury. PCA of these time course data was used to derive patient-specific "inflammation barcodes," followed by hierarchical clustering to define patient subgroups. To define the generalizability of this approach, 2 different but overlapping Luminex kits were used.
  
  
  
  PCA/hierarchical clustering of 24-hour Luminex data segregated the patients into 2 groups that differed significantly in their Marshall multiple organ dysfunction score on subsequent days, independently of the specific set of inflammatory mediators analyzed. Multiple inflammatory mediators and their dynamic networks were significantly different in the 2 groups in both patient cohorts, demonstrating that the groups were defined based on "core" early responses exhibit truly different dynamic inflammatory trajectories.
  
  
  
  Identification of patient-specific "core responses" can lead to early segregation of diverse trauma patients with regard to later MODS. Hence, we suggest that a focus on dynamic inflammatory networks rather than individual biomarkers is warranted.
authors.affiliation: Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213; Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219.
authors.forename: Rami A
authors.initials: RA
authors.lastname: Namas
authors.affiliation: Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213.
authors.forename: Khalid
authors.initials: K
authors.lastname: Almahmoud
authors.affiliation: Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, PA 15260.
authors.forename: Qi
authors.initials: Q
authors.lastname: Mi
authors.affiliation: Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213.
authors.forename: Ali
authors.initials: A
authors.lastname: Ghuma
authors.affiliation: Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213.
authors.forename: Rajaie
authors.initials: R
authors.lastname: Namas
authors.affiliation: Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA 15213.
authors.forename: Akram
authors.initials: A
authors.lastname: Zaaqoq
authors.affiliation: Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213.
authors.forename: Xiaoguang
authors.initials: X
authors.lastname: Zhu
authors.affiliation: Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213.
authors.forename: Othman
authors.initials: O
authors.lastname: Abdul-Malak
authors.affiliation: Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213.
authors.forename: Jason
authors.initials: J
authors.lastname: Sperry
authors.affiliation: Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213.
authors.forename: Ruben
authors.initials: R
authors.lastname: Zamora
authors.affiliation: Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213; Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219.
authors.forename: Timothy R
authors.initials: TR
authors.lastname: Billiar
authors.affiliation: Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213; Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15213; Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219. Electronic address: vodovotzy@upmc.edu.
authors.forename: Yoram
authors.initials: Y
authors.lastname: Vodovotz
mesh_terms: D000058:Accidental Falls; D000063:Accidents, Traffic; D000328:Adult; D015415:Biomarkers / Q000097:blood; D016000:Cluster Analysis; D016207:Cytokines / Q000097:blood*; D005260:Female; D006801:Humans; D007249:Inflammation / Q000097:blood; D018836:Inflammation Mediators / Q000097:blood; D015601:Injury Severity Score; D007902:Length of Stay; D008297:Male; D008875:Middle Aged; D009102:Multiple Organ Failure / Q000097:blood* / Q000453:epidemiology; D025341:Principal Component Analysis; D012121:Respiration, Artificial; D017741:Survivors; D014949:Wounds, Nonpenetrating / Q000097:blood* / Q000453:epidemiology
chemical_list: D015415:Biomarkers; D016207:Cytokines; D018836:Inflammation Mediators
keywords: Blunt trauma; Dynamic network analysis; Inflammation biomarkers; Multiple organ dysfunction syndrome; Principal component analysis; Systemic inflammatory response