Mining association rules and correlation relationships have been studied in the data mining field for many years. However, the rules mined only indicate association relationships among variables in an interested system. They do not specify the essential underlying mechanism of the system that describe causal relationships. In this paper, we present an approach for mining causal relationships among attributes and propose a potential application in the field of bioinformatics. Based on the theory of causal diagram, we show the properties of our approach.