Polychromatic flow cytometry in evaluating rheumatic disease patients

Abstract

B cells are central players in multiple autoimmune rheumatic diseases as a result of the imbalance between pathogenic and protective B-cell functions, which are presumably mediated by distinct populations. Yet the functional role of different B-cell populations and the contribution of specific subsets to disease pathogenesis remain to be fully understood owing to a large extent to the use of pauci-color flow cytometry. Despite its limitations, this approach has been instrumental in providing a global picture of multiple B-cell abnormalities in multiple human rheumatic diseases, more prominently systemic lupus erythematosus, rheumatoid arthritis and Sjogren’s syndrome. Accordingly, these studies represent the focus of this review. In addition, we also discuss the added value of tapping into the potential of polychromatic flow cytometry to unravel a higher level of B-cell heterogeneity, provide a more nuanced view of B-cell abnormalities in disease and create the foundation for a precise understanding of functional division of labor among the different phenotypic subsets. State-of-the-art polychromatic flow cytometry and novel multidimensional analytical approaches hold tremendous promise for our understanding of disease pathogenesis, the generation of disease biomarkers, patient stratification and personalized therapeutic approaches.

Changes of memory B- and T-cell subsets in lupus nephritis patients

“…The subset of NSM B-cells has been implicated in immune responses against T-cell independent antigens, however recent studies confirmed their role as a long-lasting memory to T-cell dependent antigens involved in reconstitution of switched memory pool upon antigen restimulation [10]. Changes in NSM fraction were accompanied by increased percentage of immature/ /early-transitional B-cells and activated SM cells, both [8,16,23]. Nevertheless, systemic accumulation of B-cells with CD27+CD21 low phenotype, e.g.…”

“…Samples were fixed with FACS lysing solution (BD Biosciences), washed and analyzed in FACS Canto II flow cytometer (BD Biosciences). Based on differential expression of surface markers the following B-cell subsets were identified: immature/ /early-transitional (I/T, CD27-IgD+CD21 low ), late-transitional/naïve (CD27-IgD+CD21+), non-switched memory (NSM, CD27+IgD+), resting class-switched memory (SM, CD27+IgD-CD21+), activated SM (CD27+IgD-CD21 low ), and double-negative (CD27-IgD-) exhausted memory (ExM) as summarized in Figure 1C [8,16,23,25]. Using T-cell panel we identified four subsets within CD4+ or CD8+ gate: naïve (CD45RA+CD45RO-CCR7+), central memory (T CM , CD45RA-CD45RO+CCR7+), effector memory (T EM , CD45RA-CD45RO+CCR7-), and effector memory CD45RA+ (T EMRA , CD45RA+CD45RO-CCR7-) [26,27].…”

“…Lymphocyte phenotyping in SLE patients revealed expansion of CD27+ memory B-cells with parallel decline in naïve compartment, but little is known if they are intrinsic or develop secondarily to disease-related inflammation [14][15][16]. Interestingly, memory B-cells in lupus patients often display 'double negative' (i.e.…”

Understanding B‐cell activation and autoantibody repertoire selection in systemic lupus erythematosus: A B‐cell immunomics approach

“…In a typical sequence of events, PBMC are analyzed using multidimensional flow cytometry after staining for 12–16 surface and intracellular markers. This approach identifies quantitative abnormalities of B-cell homeostasis between SLE, HC, and other autoimmune diseases (25, 26, 29, 30). Moreover, through the use of an increasing number of agnostic automated analytical methods (31, 32), cytometry analysis has the power to identify unheralded populations characteristic of different disease conditions.…”

“…27,28 Addressing these questions requires a comprehensive experi- HC, and other autoimmune diseases. 25,26,29,30 Moreover, through the use of an increasing number of agnostic automated analytical methods, 31,32 cytometry analysis has the power to identify unheralded populations characteristic of different disease conditions. Similar multidimensional datasets can be obtained through other cytometry methods including CyTOF and Chip-Cytometry.…”