Biomedical and Life Sciences

Gene Expression and its Discontents examines a class of probability models describing how epigenetic context affects gene expression and organismal development, using the asymptotic limit theorems of information theory in a highly formal manner. Taking classic results on spontaneous symmetry breaking abducted from statistical physics in groupoid, rather than group, circumstances, the work suggests that epigenetic information sources act as analogs to a tunable catalyst, directing development into different characteristic pathways according to the structure of external signals. The results have significant implications for epigenetic epidemiology, in particular for understanding how environmental stressors, in a large sense, can induce a broad spectrum of developmental disorders in humans. The authors then apply the perspective to a number of chronic diseases broadly associated with obesity, using data at different scales of observation.