Objective To determine the expression of APP and MAPT， two Alzheimer disease related biomarkers in gliomas， and to develop glioma prognosis predicting factors and therapeutic targets. Methods The WHO pathological grade， primary or secondary status， IDH mutation status， 1p/19q heterozygous deletion status， survival period and other data of 325 and 609 patients with grade Ⅱ to Ⅳ glioma included in the two databases of the China Glioma Genome Atlas （CGGA） and the Cancer Genome Atlas （TCGA）， as well as the expression level of APP and MAPT genes. After the gene expression level was standardized， the expression differences of the two genes in glioma， IDH mutation/wild-type， 1p/19q heterozygous deletion/wildtype were compared. Kaplan Meier （K-M） survival curve was used to analyze the relationship between APP and MAPT gene levels and the prognosis of primary and secondary glioma， and Log-rank was used for comparison. The list of genes related to MAPT expression level in CGGA and TCGA databases were screened. The molecular mechanism of MAPT affecting the prognosis of glioma was analyzed by gene ontology （GO） function enrichment. Results In CGGA and TCGA databases， the expression level of MAPT in grade Ⅱ to Ⅳ glioma patients was statistically significant （P ＜ 0.01）； There was significant difference between two groups in each database （all P＜ 0.01）. In TCGA database， there was a statistically significant difference in APP expression level between patients with grade Ⅲ and Ⅳ glioma （P ＜ 0.01）. In CGGA and TCGA databases， the expression level of MAPT in IDH mutant patients with grade Ⅱ to Ⅳ glioma was higher than that in IDH wild-type patients， and the difference was statistically significant （P ＜ 0.01）. In TCGA database， there was a statistically significant difference in APP expression between IDH mutant and wild-type patients with grade Ⅳ glioma （P ＜ 0.01）. In TCGA database， the expression level of APP in grade Ⅱ and Ⅲ glioma and MAPT between 1p/19q loss of heterozygosity and wild-type in grade Ⅲ glioma patients were statistically significant （P ＜ 0.001）. In CGGA database， there was a statistically significant difference in MAPT expression between 1p/19q loss of heterozygosity and wild-type patients with grade Ⅳ glioma （P ＜ 0.001）. K-M survival curve analysis showed that MAPT gene could effectively judge the prognosis of patients with primary glioma， and patients with higher MAPT expression had better prognosis （P ＜ 0.001）. GO function enrichment analysis showed that MAPT expression level was positively correlated with actin cytoskeleton assembly， tubulin cytoskeleton assembly， Wnt pathway， nervous system development， DNA based transcriptional regulation， RNA polymerase Ⅱ promoter transcriptional regulation of glioma， and negatively correlated with cell migration， cell adhesion， angiogenesis， cell division， cell proliferation， etc. Cell model validation found that overexpression of MAPT could inhibit the migration and invasion of glioma cells. Conclusions The expression level of MAPT can predict the prognosis of patients with primary glioma， and there is a correlation between MAPT and the malignant degree of glioma， which is a potential target for glioma research and treatment.