Identification of expression patterns associated with hemorrhage and resuscitation: Integrated approach to data analysis

Background: Although transcriptional profiling is a well-established technique, its application to systematic studying of various biological phenomena is still limited because of problems with highvolume data analysis and interpretation. This research project's objective was to create a comprehensive summary of changes in gene expression after hemorrhagic shock (HS), reliant and impartial of multiple variables, such as resuscitation treatments, organ analyzed, and time after impact. Methods: Rat model of severe (40% total blood loss) HS was employed. Hemorrhagic shock was treated with 6 different resuscitation strategies: (1) racemic lactated Ringer's (DL-LR); (2) L-lactated Ringer's (L-LR); (3) ketone Ringer's (KR); (4) pyruvate Ringer's (PR); (5) 6% hetastarch (Hex); (6) 7.5% hypertonic saline (HTS). Nonresuscitated and nonhemorrhaged rats served as controls. Ketone and pyruvate Ringer solutions were identical to the lactated Ringer's solution except for equimolar substitution of lactate with beta 3-hydroxybutyrate and sodium pyruvate, respectively. Total RNA from liver, lung, and spleen was isolated immediately (0 hour) and 24 hour postresuscitation. Each organ, time point and treatment was profiled using individual cDNA array (1,200 genes), to produce 183 separate data riles. Methods of analysis included one-way and unbalanced factorial ANOVA, Sokal-Michener average linkage clustering and contextual mapping. Results. Unresuscitated HS produced the highest number (56) of upregulated expressions in spleen and lungs. HEX and HTS affected mostly pulmonary genes (22 and 9). Fourteen genes changed in response to combination of all three factors: treatment, organ, and time. Eighteen genes were identified as treatment-specific. Fifteen genes adjusted expression 24 hour post-treatment. The largest number of genes with altered expression (168) responded differently in all three organs. In this study 15 gene clusters were pinpointed. Contextual mapping identified novel and confirmed known pathways contributing to hemorrhage/resuscitation. Conclusions. We have reliably identified genes and pathways that are affected by HS and are responsive to resuscitation. Gene expression in various organs is affected differentially by HS, which can be further modulated by the choice of resuscitation strategy.