Abstract
Psychological stress perturbs normal physiological function or homeostasis. Restoration of normalcy demands more supply of energy. A physiological mechanism via activated stress response system is aimed at providing quick energy to deal with such emergency situations. If stress response system remains activated for longer period, maintaining physiological homeostasis becomes difficult because of higher demand for energy which eventually leads to increased susceptibility to infection or disease. Although there are reports, associating psychological stress with physiological functions and diseases, a clear understanding of mechanism of stress manifestation is yet to be established. In order to facilitate extensive exploration and prediction of possible mechanisms, integration of molecular (gene-level) data pertaining to psychological stress, physiological processes and stress-associated diseases is needed. We report power of text-mining in combination with our data-integration methods and mathematical formulation to develop integrated geneassociation networks. These networks can be analyzed to gain holistic insights into the relationship between psychological stress-associated genes (stressome) and related physiological functions and diseases. We built the human psychostressome networks to understand and predict pathways and candidate genes responsible for perturbing balance among various physiological functions and disease manifestation. Using the current methodology, we were able to predict involvement of serotonin receptors and uridine 5'-diphospho-glucuronosyltransferases in mediating effects of psychological stress.
Keywords: Disease, gene networking, meta-analysis, physiology, psychological stress.