Project Objective(s)

Inflammation is a central, modulating process in many complex diseases (e.g. sepsis, infectious disease, trauma, asthma, allergy, autoimmune disorders, transplant rejection, cancer, neurodegenerative diseases, obesity, and atherosclerosis), and is a central driver of the physiology of people with spinal cord injuries. However, inflammation is not an inherently detrimental process: properly regulated, inflammation is required for successful immune response and wound healing. Inflammation is also a complex biological process that has defied reductionist, linear approaches.

The investigative team on this project has previously created mathematical and agent-based models (ABM) of the integrated inflammatory and damage/healing responses. They have used these models to elucidate basic features of acute inflammation in sepsis, trauma/hemorrhage, and altered healing in diabetic foot ulcers. They have also accomplished translational objectives using these simulations, including both in silico clinical trials and patient-specific, predictive simulations of inflammation.

This track record of success in gaining both basic and translational insights into a highly complex process-inflammation and organ damage/dysfunction in sepsis and trauma-for the first time raises the possibility of deciphering the complexity of the integrated inflammatory/healing response in settings relevant to post-injury rehabilitation. As a first step, based on an analysis of the relevant literature, we propose a systems-based schematic of the interactions among inflammatory elements, anti-inflammatory elements, muscle damage, and neural damage (Figure 1).

Figure 1 - The process of acute inflammation and tissue damage/healing, distilled for mathematical modeling purposes. Solid arrow: induction; dashed line: suppression. ). In our model, an initiating stimulus (e.g. spinal cord injury) stimulates both pro- and anti-inflammatory pathways. Pro-inflammatory agents (e.g. TNF) cause tissue damage/dysfunction, which in turn stimulates further inflammation (e.g. through the release of "danger signals"). Anti-inflammatory agents (e.g. TGF-ß, PGE2) both suppress inflammation and stimulate healing.

We postulate that inflammation and its interrelations with tissue damage/healing are a central cause of pressure ulcers following spinal cord injury, with inflammation detected via circulating cytokines in the blood that exhibits inter-individual variability with regards to risk factors. Therefore, computer simulations encompassing the biology of inflammation and damage / healing that will be calibrated with inflammatory analyte data, as well as non-invasive data on the onset and progression of pressure ulcers, will be capable of predicting the onset, progression, and characteristics of pressure ulcers post-spinal cord injury in individuals. We also postulate that chronic inflammation and its integrated effects on the healing cascade lead to fibrosis, which in turn creates a milieu conducive to urinary tract infections and further fibrosis, with detectable changes in inflammatory mediators in the urine. Therefore, we will be able to create and calibrate a computer simulation of the onset and progression of urinary tract infection following spinal cord injury. Finally, we postulate the inflammatory process set in motion by spinal cord injury, coupled with extensive utilization of a manual wheelchair, will lead to shoulder injuries in persons with spinal cord injuries. Therefore, we will be able to create and calibrate a computer simulation of this process based on analysis of inflammatory cytokines in the blood.

Methods

This project will create, calibrate, and validate computer simulations of the interlinked inflammatory and damage/healing responses following spinal cord injury. Three complications of spinal cord injury linked to inflammation and healing are pressure ulcers, urinary tract infections, and musculoskeletal injuries. Extrapolating from our work on diabetic foot ulcers, we will model and predict, on a patient-specific basis, the pressure ulcer response post-spinal cord injury. We have carried out preliminary studies on the formation of urinary tract infections in an inflammatory milieu, and this preliminary work will be used to build a computer simulation of this process following spinal cord injury. Though we have not carried out preliminary work on how inflammation leads to musculoskeletal injury, we have done work in trauma/hemorrhagic shock and phonotraumatic injury. Moreover, we have created a schema of how nerve and muscle injury interact to promote inflammation (Figure 1). This preliminary work will guide our effort to create a computer simulation of the inflammation and musculoskeletal tissue damage/healing following spinal cord injury.

Based on existing literature, we understand that spinal cord injury results in an elevation in baseline, circulating inflammatory cytokines and other inflammatory mediators such as nitric oxide (NO). The characteristics of the inflammatory response in each patient are likely to be partially dictated by the nature of the original spinal cord trauma and partially by genetic variations (single-nucleotide polymorphisms) in genes coding for cytokines. In the case of Specific Aim 1, we believe that elevated inflammatory milieu interacts non-linearly with local, pressure-driven ischemia-reperfusion and secondary oxygen radical formation to cause pressure ulcers. In the case of Specific Aim 2, we believe that the initial elevation in pro-inflammatory cytokines drives the increase in anti-inflammatory cytokines, which predispose the patient to urinary tract infections. The ongoing presence of pro-inflammatory stimuli (including infections) maintains and propagates the anti-inflammatory response, which in turn results in fibrosis, tissue damage, and further inflammation. Accordingly, we will develop ABM capable of reproducing the dynamics (time courses) of inflammatory cytokines in the blood and urine of patients sampled frequently at early time points post-injury. Based on these data, we will create patient-specific ABM. In subsequent work, these calibrated agent-based models will be used to predict the rates of formation of pressure ulcers and urinary tract infections in patients at intermediate and late time points post-injury. Finally, we will also create similar models of musculoskeletal injury following spinal cord injury. These models will include interactions between damaged nerves and muscles. We believe that the inflammatory milieu characteristic of the spinal cord injury patient, in conjunction with the biomechanical stress associated with continuous use of a manual wheelchair, will result in increased incidence of musculoskeletal injury. We will create a computer simulation of this response that, in future studies, will be used to predict patient-specific predisposition to musculoskeletal injury.

Dr. Constantine will analyze the data obtained in the proposed studies using standard statistical methods to determine significant changes in biofluids and other markers, along with associations with specific outcome measures related to pressure ulcers, urinary tract infections, and musculoskeletal injuries. In addition, these data will be used for data-driven modeling, an approach parallel to our ABM. We have made much progress in the use of mathematical and agent-based models to gain insights into the acute inflammatory response. The work we propose herein would greatly extend our progress. However, it is prudent to take a parallel approach in our modeling efforts. As described above, we will obtain repeated samples from the same patient over time. This rich dataset will allow us to use statistical modeling approaches sufficiently powered to augment our ABM. Our goal will be to compare the predictions from this statistical model with the predictions of the ABM, both of which will be based on the data obtained.

The Center for Inflammation and Regenerative Modeling (CIRM) and the Society for Complexity in Acute Illness

Mathematical modeling of a complex biological process such as inflammation benefits tremendously from interdisciplinary expertise. Dr. Vodovotz established the first institution dedicated solely to studying inflammation through an interdisciplinary process consisting of biomarker analysis, modeling/simulation, and experiments (Figure: the Center for Inflammation and Regenerative Modeling (CIRM, www.mirm.pitt.edu/cirm). The CIRM includes investigators both at the University of Pittsburgh and at collaborating institutions, both academic and industrial. The CIRM was created under the auspices of the University of Pittsburgh's McGowan Institute for Regenerative Medicine (MIRM; www.mirm.pitt.edu), the first national center for regenerative medicine. At the CIRM, the two main types of simulations being carried out involve either differential equations or ABM. The former are a class of models that has been time-tested and that forms much of the underlying knowledge base of classical physiology. The latter involves the simulation of discreet "agents" that move and interact with other agents, leading to emergent phenomena for relatively simple underlying rules.

Drs. Vodovotz and An, as well as Steve Chang of Immunetrics and collaborators at IBM, were among the founders of the Society for Complexity in Acute Illness (SCAI; www.scai-med.org), with over 160 members worldwide. Dr. Vodovotz is currently SCAI's Secretary, and Dr. An and Mr. Chang serve on SCAI's Board of Directors. The Society's International Conference on Complexity in Acute Illness (www.iccai.org) serves as the only dedicated venue for work on basic and translational applications of mathematical modeling in inflammatory diseases.

Figure 2 - Evidence-based modeling. Model building is an iterative process involving calibration from existing or new data, and validation from prediction of data. This process identifies both areas where a model is correct and where it is deficient relative to data and therefore must be corrected