Background <p>Chronic recurrent non-specific parotitis (CRNP) is characterized by recurrent parotid swelling and pain without identifiable obstructive lesions or systemic autoimmune diseases. The immunological features underlying CRNP remain poorly defined.</p> Methods <p>Peripheral blood mononuclear cells (PBMCs) from 5 patients with CRNP and 6 healthy controls (HCs) were analyzed using high-dimensional single-cell cytometry by time-of-flight (CyTOF). This pilot study was designed as an exploratory and descriptive analysis. Unsupervised clustering was used to construct a peripheral immune cell atlas, followed by nominal group comparisons, phenotypic analyses of selected subsets, and descriptive correlation and receiver operating characteristic (ROC) analyses.</p> Results <p>At the major lineage level, the relative proportions of B cells, CD4⁺ T cells, CD8⁺ T cells, myeloid cells, and natural killer (NK) cells were largely comparable between CRNP patients and HCs, except for a nominally lower proportion of double-negative T cells in CRNP. At the subset level, several exploratory differences were observed. These included nominally higher proportions of CXCR3^highCD127^high CD4⁺ central memory T cells and CD4⁺ terminally differentiated effector memory T cells re-expressing CD45RA, together with nominally lower proportions of naïve CD4⁺ T cells, naïve CD8⁺ T cells, and regulatory T cells. Exploratory phenotypic analyses further suggested variation in activation-, senescence-, and immune checkpoint-associated markers. Within the myeloid compartment, the relative proportion of conventional dendritic cells was nominally higher, whereas classical monocytes were nominally lower. Correlation and ROC analyses were performed only as descriptive within-cohort visualizations and should not be interpreted as evidence of immune cell interactions or diagnostic performance.</p> Conclusions <p>This exploratory CyTOF-based pilot study provides a preliminary descriptive overview of peripheral immune cell variation in CRNP. Given the small sample size, lack of multiple-testing correction, and potential demographic and technical confounders, these findings should be interpreted as hypothesis-generating and require validation in larger, age- and sex-matched, batch-controlled cohorts.</p>