Introduction: To explore the pathogenesis of gestational diabetic nephropathy (GDM) and its possible biological function by using large data bioinformatics mining algorithm. Materials and methods: The Gene Expression Omnibus (GEO) was retrieved and the data of GDM differential expression chip were screened and downloaded. The differentially expressed genes were screened by using R software Lima package (Log2FC > 1; P < 0.05). Functional enrichment of differentially expressed genes was performed. Protein–protein interaction network of GDM pathogenesis was constructed by the database (STRING) to analyze the interaction between differentially expressed gene-coding proteins. Using Cytohubb software to further screen the key genes (hub genes) in the signaling pathway. In next step, 35 case of GDM and 39 normal pregnant women were selected as subjects. The expression levels of key gene coding proteins in venous blood and placenta tissues of GDM and normal pregnant women detected by immunohistochemical and qRT-PCR. And using cell experiment to analysis the key gene’s effects in GDM. Results: By Bioinformatics Analysis, CDK1 was significantly depressed in GDM (P <0.001), In clinical data, CDK1 protein and mRNA expressions were also significantly down-regulation in GDM compared with NC (P <0.001). In vitro study, with high glucose treatment, the cell were hyperproliferation with CDK1 depressing and AKT overexpression (P <0.001). However, with CDK1 supplement, the cell returned to normal with CDK1 overexpression and AKT depressing (P <0.001). Conclusion: CDK1 is differentially expressed in patients with GDM and play a key part in occurrence and development of GDM. CDK1 may be a key target for treatment and prevention of GDM.