A probabilistic approach for links between rheumatic diseases and weather

Rheumatoid arthritis (RA) is an autoimmune disorder characterized by a painful swelling that can eventually result in bone erosion and joint deformity. Many works have studied the effect of weather on arthritis and rheumatism. However, some studies showed that the relationship was not clinically significant, and thus scientific evidence on the link remains sparse and non-conclusive. The aim of this paper is to clarify what sort of changes of weather factors lead to the deterioration of the symptom of RA by a probabilistic method in conjunction with cytokine network. As a method, we chose a naive Bayes classifier rather than usual regression models. While a naive Bayes classifier is normally used for the problem of discrimination, we invented a new application of naive Bayes and applied it to calculate the tendency of meteorological factors towards high risk of deterioration of RA. Among meteorological factors, we selected barometric pressure and relative humidity. We identified three patterns of tendencies of weather factors that led to deterioration of rheumatic diseases. These findings suggested mechanisms connecting weather and RA. The differences of three patterns were associated with the varied responses of cytokine network including interleukin IL-6 as a key cytokine. Our findings are expected to contribute to avoid the event of destructive deterioration of RA on the basis of daily observation of the weather. Correspondence to: Hiroshi Morimoto, The graduate school of informatics, Nagoya University, Japan, E-mail: h.morimoto@i.nagoya-u.ac.jp or hiroshim@ info.human.nagoya-u.ac.jp