Multidimensional profiling of dendritic cell and monocyte subsets in sickle cell anemia: Correlation with clinical and inflammatory parameters

Abstract Dendritic cells (DCs) and monocytes (Mo) are key components of the innate immune system, playing essential roles in initiating, polarizing, and regulating adaptive immune responses, maintaining inflammatory homeostasis, and surveilling peripheral vasculature. These cells can be activated and adopt an inflammatory phenotype upon recognizing damage-associated molecular patterns (DAMPs), which are commonly released during tissue necrosis or intravascular hemolysis—frequent events in individuals with sickle cell anemia (SCA), one of the most prevalent hemoglobinopathies worldwide. Given the heterogeneity of DC populations, an in-depth analysis is necessary to identify which subsets and phenotypes are associated with inflammatory and clinical parameters of the disease. We performed multiparametric flow cytometry to analyze DC and Mo subpopulations and their activation status in PBMCs from SCA patients (HbSS, n = 23) and healthy controls (HbAA, n = 22). Flow cytometry of T lymphocytes, complete blood counts, biochemical parameters, and inflammatory cytokines were also assessed in the same individuals and correlated with DC and Mo data. Unsupervised analysis using X-shift (FlowJo, BD) divided the DC population (Lineage− CD14− HLA-DR+) into nine distinct clusters. Circulating type 1 conventional DCs (cDC1s: Clec9a+ CD141+) were significantly less frequent (p = 0.019) in SCA patients compared to controls. Conversely, one of four clusters of plasmacytoid DCs (pDCs: CD123+ Axl−), characterized by high Sirp-α expression, was significantly increased among patients (p = 0.027), suggesting activation of a specific pDC subset in SCA. Type 2 conventional DCs (cDC2s: CD1c+ CD141−) also showed heterogeneity, being divided into three clusters, one of which was significantly more frequent in SCA patients than in controls (p = 0.010). This cDC2 cluster expressed the lowest levels of Sirp-α and the highest levels of CD40, indicating a more activated/inflammatory phenotype. Unsupervised analysis of Mo and inflammatory DCs (iDCs) (Lineage− CD14+ HLA-DR+) revealed two iDC clusters and seven Mo clusters. One classical monocyte (C-Mo: CD14+ CD16−) cluster, characterized by high Sirp-α and low HO-1 expression, was significantly reduced in SCA patients (p = 0.032). A trend toward increased frequency of one iDC cluster (CD1c+) in SCA patients was observed (p = 0.06); this cluster showed low Sirp-α expression. Expression of HO-1 was elevated in all Mo subsets (classical: CD14+ CD16−; non-classical: CD14intCD16−; intermediate: CD14+ CD16+) as well as in three DC subsets (cDC1, cDC2, and pDC), suggesting that DCs are not only activated but may also participate in heme metabolism following hemolysis. Expression of Sirp-α, the inhibitory receptor that also impairs RBCs clearance, was reduced in all Mo subsets and in cDC2, suggesting their activation and possible role in clearance of circulating RBCs in SCA. Classical and non-classical Mo from SCA patients also increased CD71 expression, suggesting higher iron uptake by these cell subsets. Initial correlation analyses showed that PD-L1 expression by cDC1 was associated with CD4+ T cell exhaustion (PD-1 expression) in SCA patients (p = 0.05). Additionally, IL-17 production by CD4+ and CD8+ T cells correlated with specific clusters of cDC1, cDC2, and iDCs (p < 0.05). Notably, the frequency of regulatory T cells (Foxp3+) was correlated with a specific pDC cluster (p = 0.006), indicating subset-specific roles of DCs in modulating the adaptive immune response in SCA. Bilirubin levels correlated with both iDC frequency (p = 0.031) and CD86 expression (p = 0.047), suggesting a link between iDC activation and disease severity. In contrast, bilirubin was inversely correlated with pDC frequency (p = 0.044) and HO-1 expression by pDCs (p = 0.039), implying a potential regulatory role of pDCs in SCA. Future analyses will further explore correlations across all evaluated parameters. Together, these findings enhance our understanding of DC subset heterogeneity, their activation profiles, and impact on T cell dysfunction in SCA. They also highlight the association between heme/iron handling by DCs and Mos and clinical indicators of disease severity.