Committee:

Eberhard O. Voit, Ph.D. (Ph.D. Advisor) (Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University; Department of Biological Sciences, University of Texas at Dallas)

Qiang Zhang, M.D., Ph.D. (Co-Advisor) (Gangarosa Department of Environmental Health, School of Public Health, Emory University)

Dr. Melissa L. Kemp, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Peng Qiu, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Mark Styczynski, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Assessing the Impact of Dioxin on Human Health through Mathematical Modeling

Biological systems are organized in distinct but connected layers, which makes their analysis a challenge. The higher layers usually correspond to a “big picture” of a physiological event, whereas the lower levels account for increasing granularity and detail. It is infeasible to carry along all details from lower levels, partly for technical reasons, but also because they would overwhelm insights at the higher level due to their sheer numbers and the fact that they typically run on much faster time scales.

              This work addresses the well-known challenge of biomedical multiscale analysis with a novel adaptation of the Template-and-Anchor (T&A) modeling paradigm. It considers a template as a high-level, coarse-grained model that focuses exclusively on the main physiological components of a system and involves correspondingly few variables, processes and parameters. The template contains as variables the anchor models, which are modules of component sub-systems that provide more elaborate descriptions of specific biological details. This conceptual framework does not attempt to capture simultaneously all details within a single computable structure as many other multiscale models do. Instead, the often-overwhelming multilevel task is dissected into smaller, stand-alone models that are analyzed separately. This new adaptation of the T&A approach offers substantial advantages without losing resolution. First, the divide-and-conquer method enhances computational efficiency. Second, unlike other methods, each anchor is analyzed individually, producing a record of crucial input-output relationships that are ultimately used in the template model. Third, anchor models can be replaced with alternative representations without affecting the structure of the template or other anchors. Fourth, the T&A model provides flexible guidelines for its setup and for defining variables across scales. 

Using the T&A approach, this work addresses the health implications of exposure to dioxin (specifically, 2,3,7,8-tetrachlorodibenzo-p-dioxin), a persistent organic pollutant which can severely affect health, depending on the magnitude of exposure. The template captures the overall effects of dioxin on the dynamics of cholesterol, a prominent target of dioxin. The anchor models serving as variables in the overall template model include hepatic cholesterol biosynthesis (via the mevalonate pathway), lipoprotein metabolism, and estrogen synthesis. The creation and combination of anchor and template models enables a holistic evaluation of the impact of dioxin, which can be translated into a tool for comprehensive computational health risk assessments.

              On the theoretical side, this work discerns fundamental differences in the conceptual set-up of templates and anchors which may be viewed as dual structures of each other, as the variables in anchor models are material quantities, whereas the variables in template models are processes. T&A modeling, and multiscale modeling in general, hold promise for a deeper understanding of complex systems and for advancing personalized medicine and risk assessment, interspecies translation, and the development of virtual clinical trials.