A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are nonexistent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the responses in corresponding mouse models correlate poorly with the human conditions and also, one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g., R 2 between 0.0 and 0.1). In addition to improvements in the current animal model systems, our study supports higher priority for translational medical research to focus on the more complex human conditions rather than relying on mouse models to study human inflammatory diseases.human disease | translational medicine | inflammation | immune response | injury M urine models have been extensively used in recent decades to identify and test drug candidates for subsequent human trials (1-3). However, few of these human trials have shown success (4-7). The success rate is even worse for those trials in the field of inflammation, a condition present in many human diseases. To date, there have been nearly 150 clinical trials testing candidate agents intended to block the inflammatory response in critically ill patients, and every one of these trials failed (8-11). Despite commentaries that question the merit of an overreliance of animal systems to model human immunology (3,12,13), in the absence of systematic evidence, investigators and public regulators assume that results from animal research reflect human disease. To date, there have been no studies to systematically evaluate, on a molecular basis, how well the murine clinical models mimic human inflammatory diseases in patients.The Inflammation and Host Response to Injury, Large Scale Collaborative Research Program has completed multiple studies on the genomic responses to systemic inflammation in patients and human volunteers as well as murine models (14-18). These datasets include genome-wide expression analysis on white blood cells obtained from serial blood draws in 167 patients up to 28 d after severe blunt trauma (15), 244 patients up to 1 y after burn injury, and 4 healthy humans for 24 h after administration of low-dose bacterial endotoxin (14) and expression analysis on analogous samples from well-established mouse models of trauma, burns, and endotoxemia (16 treated and 16 controls per model) (16-18). In humans, severe inflammatory stress produces a genomic storm affecting all major cellular functions and pathways (15) and therefore, provided sufficient perturbations to allow comparisons between the genes in the human conditions and their orthologs in the murine models.In this article, we report on a systematic comparison of the genomic respo...

Critical injury in humans induces a genomic storm with simultaneous changes in expression of innate and adaptive immunity genes.

Objective Many patients following severe trauma have complicated recoveries due to the development of organ injury. Physiological and anatomical prognosticators have had limited success in predicting clinical trajectories. We report on the development and retrospective validation of a simple genomic composite score that can be rapidly used to predict clinical outcomes. Design Retrospective cohort study Setting Multi-institution level 1 trauma centers Patients Data was collected from 167 severely traumatized (ISS >15) adult (18–55 yo) patients Methods Microarray-derived genomic data obtained from 167 severely traumatized patients over 28 days were assessed for differences in mRNA abundance between individuals with different clinical trajectories. Once a set of genes was identified based on differences in expression over the entire study period, mRNA abundance from these subjects obtained in the first 24 hours was analyzed in a blinded fashion using a rapid multiplex platform, and genomic data reduced to a single metric. Results From the existing genomic data set, we identified 63 genes whose leukocyte expression differed between an uncomplicated and complicated clinical outcome over 28 days. Using a multiplex approach that can quantitate mRNA abundance in less than 12 hours (nanoString™), we reassessed total mRNA abundance from the first 24 hours after trauma, and reduced the genomic data to a single composite score using the difference from reference (DFR). This composite score showed good discriminatory capacity to distinguish patients with a complicated outcome (area under a receiver-operator curve, 0.811, p < 0.001). This was significantly better than the predictive power of either APACHE II or NISS scoring systems. Conclusions A rapid genomic composite score obtained in the first 24 hours after trauma can retrospectively identify trauma patients who are likely to develop a complicated clinical trajectories. A novel platform is described in which this genomic score can be obtained within 12 hours of blood collection, making it available for clinical decision making. (300 words; limit 300)

A 6.9 million-feature oligonucleotide array of the human transcriptome [Glue Grant human transcriptome (GG-H array)] has been developed for high-throughput and cost-effective analyses in clinical studies. This array allows comprehensive examination of gene expression and genome-wide identification of alternative splicing as well as detection of coding SNPs and noncoding transcripts. The performance of the array was examined and compared with mRNA sequencing (RNA-Seq) results over multiple independent replicates of liver and muscle samples. Compared with RNA-Seq of 46 million uniquely mappable reads per replicate, the GG-H array is highly reproducible in estimating gene and exon abundance. Although both platforms detect similar expression changes at the gene level, the GG-H array is more sensitive at the exon level. Deeper sequencing is required to adequately cover lowabundance transcripts. The array has been implemented in a multicenter clinical program and has generated high-quality, reproducible data. Considering the clinical trial requirements of cost, sample availability, and throughput, the GG-H array has a wide range of applications. An emerging approach for large-scale clinical genomic studies is to first use RNA-Seq to the sufficient depth for the discovery of transcriptome elements relevant to the disease process followed by high-throughput and reliable screening of these elements on thousands of patient samples using customdesigned arrays.gene isoform | next-generation sequencing | exon junction | blood leukocyte

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