Objective Using bioinformatics analysis to explore possible molecular mechanisms in the pathogenesis of schizophrenia and to search for biomarkers for the diagnosis of schizophrenia. Methods The GSE48072 dataset from the Gene Expression Omnibus （GEO） database was selected for bioinformatic analysis of the mRNA expression profiles of 31 schizophrenia patients and 35 healthy controls. Functional enrichment analysis was performed on the differential genes obtained from the screening. The protein-protein interaction （PPI） network of differential genes was constructed using string database and key genes were screened by Cytoscape software. The Cytoscape plugin CytoHubba was used to search for hub genes. The diagnostic value of key genes was verified by subject operating characteristic （ROC） curves. Results A total of 82 differential genes were screened. The results of the enrichment analysis showed that the differential genes were mainly concentrated in inflammation， immune regulation and unsaturated fatty acid metabolism. A total of 5 hub genes， CD244， GZMH， GZMA， KLRD1 and GZMK， were obtained after screening， and the areas under the ROC curves were 0.817， 0.725， 0.724， 0.717 and 0.693， respectively. Conclusions Patients with schizophrenia have abnormalities in inflammatory pathways， unsaturated fatty acids， and vitamin metabolism. The expression changes of CD244 and other 5 related genes can be used as biological markers for the diagnosis of schizophrenia.