Environmental factors in autoimmune diseases, February 4–5, 2003, Durham, NC, USA

Exposure assessment is often considered the weakest link in risk assessment. It is important for investigators to continue to utilize the full potential of biomarkers for chemicals whose exposure is of global concern. This review is concerned with the biomarkers of metal toxicity, as the overall exposure to metals encountered occupationally or in the environment would continue causing indirect, delayed effects therefore ecoepidemiology, using designed molecular probes and noninvasive diagnostics will be the leading component for future management of environmental health. An attempt is made here at appraising the need for the development of more biomarkers for use in environmental epidemiology and health risk assessment.

Autoimmune diseases include a heterogeneous group of complex traits, the causes of which are essentially unknown. The threshold liability model is a hypothesis that has a significant influence on thinking about causation in these diseases. Here, I analyze this model and assess its utility in understanding causation in autoimmunity. According to the model, members of a population have a normal distribution of genetic liability for a particular autoimmune disease. Further, a threshold value exists for each autoimmune disease such that an individual develops disease when his/her liability exceeds the threshold value; environmental and stochastic factors and epistatic gene interactions may increase or decrease an individual's disease liability. There are, however, two main problems with the threshold liability model. First, for a particular autoimmune disease, the threshold value divides a population into two distinct groups that consist either of affected or of healthy individuals. I show that this dichotomous division is inaccurate and misleading. Second, the threshold value corresponds to the occurrence of a component-cause of disease, i.e. when an appropriate collection of causative factors for a particular autoimmune disease is present, the disease must inevitably occur. I argue, however, that the disease contribution of essentially unknown random or stochastic factors to causation is at least similar in importance to the contributions of genetic and environmental factors. These stochastic factors add a significant element of unpredictability to the effects of genetic and environmental factors. Consequently causes in autoimmunity do not act deterministically, which is implied by the component-cause concept. Instead, the role of causative factors is to alter disease risk. I therefore reject the threshold liability model and conclude that a probabilistic approach provides the only reasonable way to understand causation in autoimmune diseases. This conclusion has important implications for other deterministic hypotheses in autoimmunity including other component-cause hypotheses.