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Although autoantibodies have been used for decades as diagnostic and prognostic markers in type 1 diabetes (T1D), further analysis of developmental abnormalities in B cells could reveal tolerance checkpoint defects that could improve individualized therapy. To evaluate B cell developmental progression in T1D, immunophenotyping was used to classify circulating B cells into transitional, mature naive, mature activated, and resting memory subsets. Then each subset was analyzed for the expression of additional maturation-associated markers. While the frequencies of B cell subsets did not differ significantly between patients and controls, some T1D subjects exhibited reduced proportions of B cells that expressed transmembrane activator and CAML interactor (TACI) and Fas receptor (FasR). Furthermore, some T1D subjects had B cell subsets with lower frequencies of class switching. These results suggest circulating B cells exhibit variable maturation phenotypes in T1D. These phenotypic variations may correlate with differences in B cell selection in individual T1D patients.

There are few studies of the developmental changes in B-cell subsets in children. Recent data from adult populations demonstrate that alterations to B-cell subsets have functional consequences and can be helpful diagnostically. Comparable studies in children have been hindered by the lack of normative data and by significant changes with age. This study evaluated B-cell subsets by 4-color flow cytometry in 47 children of different ages. The use of a 4-color platform is compatible with broad use in clinical laboratories. We found that there are rapid changes in the B-cell compartment in infancy and early childhood. Total B-cell numbers decline early in life, and this correlates with a decline in transitional B cells and naïve B cells. The decline is most rapid between 1 and 5 years of age, with a slower decline later in childhood. In contrast, nonswitched and switched memory B cells both increase during the 1st 5 years of life. The decline in B-cell numbers did not occur until after 1 year of age, suggesting that the period after birth is a unique developmental window. These data provide a reference set for further studies on B-cell dysfunction in pediatric disorders. The changes occurring in early childhood document the need for age-related assessments and serve to underscore the B-cell-specific kinetics of immunologic development in humans.

Manual gating of bivariate plots remains the most frequently used data analysis method in flow cytometry. However, gating is operator-dependent and cumbersome, particularly with the increasing complexity of modern multicolor immunophenotyping data. A method that can remove operator bias, enable systematic and thorough analysis of complex high-dimensional data, correlate temporal changes in different subsets and lead to biomarker discovery is needed. Here we apply such a method, called cytometric fingerprinting (CF), to data obtained on peripheral blood B cells from an adult patient with type-1 diabetes who underwent pancreatic islet transplantation. We establish that CF can be used to analyze longitudinal trends in immunophenotypic data, and show that results from CF are comparable to those obtained with traditional gating methods. Both methods reveal the appearance of transitional B cells and subsequent accumulation of more mature B cells following immunosuppression and transplantation. This pattern is consistent with a temporally ordered process of B cell auto-reconstitution. We also show the comparative efficiency of fingerprinting in recognizing relative changes in B cell subsets with respect to time, its ability to couple the data with statistical methods (agglomerative clustering) and its potential to define novel subsets.