Project Summary
Murine models have been extensively used in recent decades to identify and test drug candidates for subsequent human trials. However, few of these human trials have shown success. 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. 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 accumulated datasets from the large multi-center consortium studying genomic responses to inflammation provide the opportunity to systematically compare the immune response between human conditions and murine models. Here we show that while 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 with one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g., R2 between 0.0–0.1). 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.
Significance
The use of mouse models developed to mimic human diseases has dominated scientific literature. Despite commentaries that question the merit of an overreliance of animal systems to model human immunology, in the absence of systematic evidence, investigators and public regulators assume that results from animal research reflect human disease. We conducted a systematic study to evaluate how well existing murine models mimic human inflammatory diseases. The study shows that molecular results from current models should be critically evaluated before accepted as findings relevant to the human diseases. New approaches need be explored to improve the ways human diseases are studied.
Approach
The datasets studied include expression analysis on white blood cells obtained from serial blood draws in 167 patients up to 28 days following severe trauma, 244 patients up to 1 year after burns, and 4 healthy humans for 24 hours after administration of endotoxin, and expression analysis on analogous samples from well-established mouse models of trauma, burns, and endotoxemia. In humans, severe inflammation produces a “genomic storm” affecting all major cellular functions and pathways and therefore provided sufficient pertubations to allow comparisons between the genes in the human conditions and their orthologs in the murine models.
We sought and evaluated additional patient and corresponding mouse model studies from Gene Expression Omnibus (GEO) for several other severe acute inflammatory diseases (sepsis, acute respiratory distress syndrome, and infections)
Results
Discussion
Our results in humans strongly support the hypothesis that the molecular mechanisms underlying Systemic Inflammatory Response Syndrome (SIRS) are similar regardless of initiating etiology, which is central to the pursuit of drug targets.
The evolution of the immune system is a direct consequence of the microbe-exerted selection pressure for a species. Relative to the human response, mice are highly resilient to inflammatory challenge. It is noteworthy that the muted response as seen in mouse is likely preferable to the massive response seen in human.
The prevailing assumption that molecular results from current mouse models developed to mimic human diseases translate directly to human conditions is challenged by our study.
New approaches should be explored to improve current models. The quality of the animal models should be determined by how well it reproduces the human disease on a molecular basis rather than by simply phenotype. An increased diversity of laboratory animal models (including primates) and the development of ‘synthetic’ human models can improve current disease models.
Personnel
Junhee Seok1,2, Weihong Xu1,2, Michael Mindrinos1,2, Lyle Moldawer2, Ronald Maier2, David Herndon2, Ronald Davis1,2, Ronald Tompkins2 and Wenzhong Xiao1,2
1Stanford Genome Technology Center, 2Inflamamtion and the Host Response to Injury Consortium