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Complex diseases are generally thought to be under the influence of one more mutated risk genes and jointly genetic and environmental factors, which are thought to be of key importance. And with the accumulation of high-throughput datasets, it plays a more and more important role to interpret the pathogenesis of complex diseases systematically using bioinformatics methods in life science. Many association methods have been developed to identify susceptibility genes assuming a single-gene disease model, referred to as single-locus methods. Pathway based approaches, combined with association methods, consider the joint effects of multiple genes and environmental factors. By analyzing the contribution of genetic factors to complex disease and the environmental factors in the same KEGG pathways, we demonstrated an approach to mine risk pathways associated with the complex disease: A SNP and pathway based association method (SPAM). By quantitating genetic and biological environmental factors properly and integrating these two aspects, we worked out two RS scoring measurements to mine intimate biological pathways, which could demonstrate the pathogenesis of complex disease well from a new perspective. Finally, this method was introduced into bipolar disorder (BD), and it turned out well by literature retrieving. Furthermore, this method will be introduced into other complex diseases to provide additional insights into the pathogenesis better.