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Clinical Trial
. 2013 Feb 26;110(9):3507-12.
doi: 10.1073/pnas.1222878110. Epub 2013 Feb 11.

Genomic Responses in Mouse Models Poorly Mimic Human Inflammatory Diseases

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Clinical Trial

Genomic Responses in Mouse Models Poorly Mimic Human Inflammatory Diseases

Junhee Seok et al. Proc Natl Acad Sci U S A. .
Free PMC article

Abstract

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.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Correlations of the gene changes among human burns, trauma, and endotoxin and the corresponding mouse models. Scatter plots and Pearson correlations (R2) of the log twofold changes of 4,918 human genes responsive to trauma, burns, or endotoxemia (FDR < 0.001; fold change ≥ 2) and their murine orthologs in the murine models. As shown in the upper left, the genomic responses to human trauma and burns are highly correlated (R2 = 0.91). In contrast, as shown in the lower right, the murine models correlate poorly with each other (R2 = 0.00–0.13) and almost randomly with the corresponding human conditions (R2 = 0.00–0.09). Similar results were seen with rank correlation (SI Appendix, Fig. S1).
Fig. 2.
Fig. 2.
Comparisons of the time-course gene changes for human burns, trauma, and endotoxin and the murine models. (A) K-means clustering of 4,918 genes responsive to human systemic inflammation over time. Time intervals for the human conditions: up to 1 y (burns), 1 mo (trauma), and 1 d (endotoxemia); time intervals for mouse models: 1 wk (trauma and burns) and 1 d (endotoxemia). (B) Box plots of recovery times of gene changes in the human and mouse conditions. (C) Log2 expression changes vs. time of HLA-DRA as an example where genes changed significantly over a long time in human injuries but minimally in the murine models.
Fig. 3.
Fig. 3.
Pathway comparisons between the human burns, trauma, and endotoxin and mouse models. Shown are bar graphs of Pearson correlations (R2) for the five most activated and suppressed pathways between the four model systems (human endotoxemia and the three murine models) vs. human trauma and burns. Negative correlations are shown as negative numbers (−R2). Human burn is shown as the reference. In every pathway, human endotoxemia had much higher similarity to human injury than mouse models.
Fig. 4.
Fig. 4.
Comparison of the genomic response to severe acute inflammation from different etiologies in human and murine models. GEO was queried for studies in the white blood cells of additional severe acute inflammatory diseases (sepsis, ARDS, and infections) in human and mouse. The resulting datasets are listed in Table 1. Shown are correlations (R2; x axis) and directionality (%; y axis) of gene response from the resulting multiple published datasets in GEO compared with human burn injury.

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