INTRODUCTION: The symptoms of major depressive disorder (MDD) vary widely. Psycho-neuro-inflammation has shown that MDD's inflammatory factors can accelerate or slow disease progression. This network analysis study examined the complex interactions between depressed symptoms and inflammatory factors in MDD prevention and treatment. MEASURES: We gathered participants' inflammatory factor levels, used the Hamilton Depression Scale (HAMD-17), and network analysis was used to analyzed the data. Network analysis revealed the core inflammatory (nodes) and their interactions (edges). Stability and accuracy tests assessed these centrality measures' network robustness. Cluster analysis was used to group persons with similar dimension depressive symptoms and examine their networks. RESULTS: Interleukin-1β (IL-1β) is the core inflammatory factor in the overall sample, and IL-1β-interleukin-4 (IL-4) is the strongest correlation. Network precision and stability passed. Network analysis showed significant differences between Cluster 1 (with more severe anxiety/somatization and sleep disruption) and Cluster 3 (with more severe retardation and cognitive disorders), as well as between Cluster 2 (with more severe anxiety/somatization, sleep disruption and body weight) and Cluster 3. IL-1β is the core inflammatory factor in Cluster 1 and Cluster 2, while tumor necrosis factor alpha (TNF-α) in Cluster 3. CONCLUSION: IL-1β is the central inflammatory factor in the network, and there is heterogeneity in the core inflammatory factor of MDD with specific depressive dimension symptoms as the main manifestation. In conclusion, inflammatory factors and their links should be prioritized in future theoretical models of MDD and may provide new research targets for MDD intervention and treatment.