Identifying Integrative Molecular Pathways for Predictive Modeling of Infectious Disease

The signs and symptoms of infectious disease are similar in presentation, such as fever and fatigue, but differ in magnitude, duration, and sequence. Although observable responses of dysfunction are well characterized, the integrative system mechanisms driving such trajectories are poorly known, even during normative circumstances. Here, molecular pathways are presented that enable predictive modeling of autonomic dysfunction due to infectious agents, and that illustrate a coordinating integration of body system dynamics. To arrive at this result, a molecular model is presented which shows, for the first time, that the hormone cortisol (CORT) and prostaglandin E2 (PGE2) have approximately equivalent chemical affinity, as indicated by the positioning of functional groups in hydrogen bonding and hydrophobicity, with the ligand binding domain of the glucocorticoid receptor (GR). A mathematical model is developed to predict that the signs and symptoms of illnesses are associated with the competitive inhibition at the GR of CORT and PGE2 within the hypothalamus that prevents normal gene expression during DNA transcription. To validate the pathways and model, a case study is presented to analyze the cause and presentation of fever and fatigue over multiple days due to the injection of a pneumococcal vaccine as influenced by physical activity. The research provides quantitative understanding of the root causes of signs and symptoms of infectious disease, which for example can offer a quantitative explanation of common symptomatic concerns of illness, such as fever, and can result in optimal drug treatment plans to minimize the effects of ailments. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/835546v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@2832c0org.highwire.dtl.DTLVardef@11bebbeorg.highwire.dtl.DTLVardef@121f1borg.highwire.dtl.DTLVardef@1b84fb5_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG