Aim To identify functional gene modules related to atherosclerosis (As) with diabetes by weighted gene co-expression network analysis (WGCNA). Methods GSE23304 data set containing 101 samples of atherosclerotic peripheral plaques (25 of them had diabetes) was downloaded from the gene expression omnibus (GEO), then the gene expression profile was correlated with phenotypic data and analyzed by WGCNA. According to the correlation coefficient size, the study identified the module which phenotype is the most highly associated with atherosclerosis, with functional annotation (GO) of the genes in the module, and then used STRING for protein interaction network analysis. Results 33 modules were obtained by WGCNA analysis, of which the Darkturquoise module identified by atherosclerosis is the most relevant to diabetes, and Darkturquoise is considered to be a key gene module for diabetes in atherosclerosis. Conclusion The atherosclerosis key gene module identified by WGCNA analysis may play an important role in diabetes.