Depression is a common mental disorder with complex pathophysiology, and serum proteomics offers a promising approach to discover potential biomarkers. However, the wide dynamic range of serum proteins, particularly the dominance of high-abundance proteins, often masks low-abundance components that may carry key pathological information. In this study, we performed a serum proteomic analysis focusing on low-abundance fractions in individuals with depression. A total of 211 serum samples were collected from patients diagnosed with depression and healthy controls. This dataset provides a valuable resource for understanding the molecular mechanisms of depression and may facilitate the discovery of low-abundance serum protein biomarkers. The data can be reanalyzed for protein–protein interaction networks, pathway enrichment, or comparison with other psychiatric disorders.