Concerning that there is no research about the relationship between disease classification and functional homogeneity analysis of functional protein module in network medicine, the following research work was carried out. Firstly, a gene relationship network was constructed based on the Mesh database and String9 database. Secondly, the gene relationship network was divided by using optimized modularity-based module classification method (such as BGLL, Nonnegtive Matrix Factorization (NMF) and other clustering algorithms). Thirdly, the GO enrichment analysis was carried out for divided modules, and through the comparison of GO enrichment analysis to the high and low pathogenic topology module, important biology suggests for disease classification could be found from protein functional module characteristics in the aspects of biological process, cellular component, molecular function and so on. Finally, the functional characteristics of topological module for disease classification were analyzed, and the data about the functional features of each module was obtained by the analysis to the properties of the network topology such as average degree, density, and average shortest path length, and further correlativity between disease classification and functional module was revealed.