T cell Dissimilarities in B Cell Activating Factor–Deficient Versus B Cell Activating Factor Receptor 3–Deficient Systemic Lupus Erythematosus‐Prone NZM 2328 Mice as Contributors to Their Divergent Clinical Outcomes

Abstract

Objective

We assessed the contributions of B cell and T cell subsets to the disparate clinical outcomes in NZM.Baff ^−/− and NZM.Br3 ^−/− mice.

Methods

We assessed in NZM wild‐type, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice numbers and percentages of B cells and subsets, T cells and subsets, and in vivo proliferation and survival of forkhead box P3 (Foxp3)⁺ cells by fluorescence‐activated cell sorting. Relationships between percentages of Foxp3⁺ cells and numbers of CD19⁺ and CD4⁺ cells were assessed by linear regressions.

Results

In each age and sex cohort, percentages and numbers of CD19⁺ cells were similar in NZM.Baff ^−/− and NZM.Br3 ^−/− mice. Percentages of CD3⁺ and CD4⁺ cells were greater in NZM.Br3 ^−/− than in NZM.Baff ^−/− mice, with the CD4 to CD3 cell ratios being greater in NZM.Br3 ^−/− than in NZM.Baff ^−/− mice and percentages of Foxp3⁺ cells in NZM.Br3 ^−/− mice being lower than in NZM.Baff ^−/− mice. Percentages of Foxp3⁺ cells correlated positively with CD19⁺ cells in NZM.Baff ^−/− mice but negatively in NZM.Br3 ^−/− mice. In vivo proliferation and survival of Foxp3⁺ cells were lower in NZM.Baff ^−/− mice than in NZM.Br3 ^−/− mice.

Conclusion

Differences between NZM.Baff ^−/− and NZM.Br3 ^−/− mice in Foxp3⁺ cells and their relationships with CD19⁺ cells may have more to do with their divergent clinical outcomes than do differences in numbers of B cells. These unexpected findings suggest that B cell activating factor (BAFF)–B cell maturation antigen (BCMA) or BAFF–Transmembrane activator and calcium‐modulator and cyclophilin ligand interactor (TACI) interactions may help drive development of clinical systemic lupus erythematosus (SLE) even under conditions of considerable B cell depletion. Insufficient blocking of BAFF–BCMA and BAFF–TACI interactions may lie at the heart of incomplete clinical response to BAFF‐targeting agents in human SLE.

INTRODUCTION

Studies in systemic lupus erythematosus (SLE)‐prone mice that have been rendered B cell deficient irrefutably document the absolute requirement for B cells in the development of SLE. ¹ , ² Indeed, pharmacologic and cell‐based therapeutic approaches that target B cells have succeeded to varying degrees in ameliorating disease activity in murine SLE models and in human patients with SLE. ³ , ⁴ , ⁵ , ⁶ , ⁷ , ⁸ , ⁹ , ¹⁰

Of the multiple B cell‐targeting agents tested in human SLE, only belimumab, an anti‐B cell activating factor (BAFF) monoclonal antibody (mAb), is approved to date by the US Food and Drug Administration for the treatment of human SLE. BAFF, also known as BLyS, is a 285–amino acid type II transmembrane protein member of the tumor necrosis factor ligand superfamily. ¹¹ , ¹² BAFF is a vital B cell survival and differentiation factor, ¹³ , ¹⁴ , ¹⁵ with reduced numbers of B cells in BAFF‐deficient mice ¹⁶ , ¹⁷ and increased numbers of B cells and development of SLE‐like features in mice that constitutively overexpress BAFF. ¹⁸ , ¹⁹

BAFF has three receptors: B cell maturation antigen (BCMA), transmembrane activator and calcium‐modulator and cyclophilin ligand interactor (TACI), and B cell activating factor receptor 3 (BR3). ²⁰ , ²¹ , ²² , ²³ Of these receptors, it is BR3 that plays a dominant role in BAFF‐driven B cell survival. ²⁴ , ²⁵ , ²⁶ Not surprisingly, of mice singly‐deficient in one of the BAFF receptors, only BR3‐deficient mice harbor reduced numbers of B cells, ²⁵ , ²⁶ whereas BCMA‐deficient mice harbor normal numbers of B cells, ¹⁷ , ²⁷ and TACI‐deficient mice harbor increased numbers of B cells. ²⁸ , ²⁹

Although SLE‐prone NZM 2328 (NZM) mice bearing a genetically disrupted Baff gene (NZM.Baff ^−/− ) are protected from development of SLE, ³⁰ NZM mice bearing a genetically disrupted Br3 gene (NZM.Br3 ^−/− ) develop SLE with the same time course and severity as do NZM wild‐type (WT) mice. Disease in NZM.Br3 ^−/− mice develops despite a severe reduction in B cell numbers to a degree similar to that in NZM.Baff ^−/− mice. ³¹ Thus, the dichotomy in clinical phenotype between NZM.Baff ^−/− and NZM.Br3 ^−/− mice cannot simply be attributed to a difference between the two mouse lines in the number of B cells.

Our laboratory recently demonstrated that the phenotypes of nonautoimmune‐prone C57BL/6 (B6) mice deficient in BAFF (B6.Baff ^−/− ) and B6 mice deficient in BR3 (B6.Br3 ^−/− ) differ in several ways that involve both B cells and T cells. ³² In this report, we extend our analyses to NZM.Baff ^−/− and NZM.Br3 ^−/− mice and demonstrate that differences between NZM.Baff ^−/− and NZM.Br3 ^−/− mice in forkhead box P3 (Foxp3)⁺ cells and their relationships with CD19⁺ cells may have more to do with the divergent clinical outcomes than do differences in the numbers of B cells or the distribution of B cell subsets. These unexpected findings suggest that BAFF–BCMA and BAFF–TACI interactions in an SLE‐prone host help drive development of clinical disease even under conditions of considerable B cell depletion. This raises the possibility that insufficient blocking of BAFF–BCMA and BAFF–TACI interactions may lie at the heart of the incomplete clinical response to BAFF‐targeting agents in human SLE.

MATERIALS AND METHODS

Mice

All mice used in this study bore the identical Foxp3 ^gfp knock‐in. NZM.Foxp3 ^gfp mice were generated by introgressing the Foxp3 ^gfp knock‐in from B6.Foxp3 ^gfp mice into NZM WT mice through a marker‐assisted selection protocol, ³³ and the N7 backcross generation was fully congenic. These mice were then intercrossed with NZM.Baff ^−/− mice ³⁰ and NZM.Br3 ^−/− mice ³¹ to yield the respective mice bearing the Foxp3‐gfp knock‐in.

Genotyping was monitored by polymerase chain reaction. Because the Foxp3 gene is located on the X chromosome, male mice were hemizygous for the Foxp3‐gfp knock‐in, whereas female mice were bred to homozygosity for the Foxp3‐gfp knock‐in. All mice were housed in the same specific pathogen‐free room. Mice two to three months of age were designated as young, and mice six months of age or older were designated as old. For simplicity going forward, the mice will be identified without the Foxp3 ^gfp component (eg, NZM.Baff ^−/− mice rather than NZM.Baff ^−/− .Foxp3 ^gfp mice).

Cell surface staining

Spleen mononuclear cells were stained with fluorochrome‐conjugated mAb specific for CD3, CD4, CD8, CD19, CD21, CD23, and CD25 (BioLegend or BD Pharmingen) and analyzed by fluorescence‐activated cell sorting. B cells were defined as CD19⁺, follicular (FO) B cells as CD19⁺CD21⁺CD23⁺, and marginal zone (MZ) B cells as CD19⁺CD21^hiCD23^lo. The CD19⁺CD21⁻CD23⁻ cell population includes age‐associated B cells (ABCs) (Supplementary Figure 1). Foxp3⁺ cells were divided into CD25⁻ and CD25⁺ subsets (Supplementary Figure 2).

In vivo proliferation of Foxp3⁺ cells

Spleen mononuclear cells were surface stained for CD4, fixed and permeabilized, and stained with allophycocyanin‐conjugated anti–Antigen Kiel 67 (Ki‐67) mAb. Control samples were identically treated, substituting Armenian hamster IgG isotype control mAb for the anti–Ki‐67 mAb (BioLegend). Cells were gated on CD4⁺Foxp3⁺ cells and were analyzed for Ki‐67 expression (Supplementary Figure 3).

In vivo survival of Foxp3⁺ cells

Spleen mononuclear cells were stained for CD4 and stained with the APC Annexin V Apoptosis Detection Kit with 7‐AAD (BioLegend) according to the manufacturer's instructions. Cells were gated on CD4⁺Foxp3⁺ cells and were analyzed for annexin V binding and 7‐aminoactinomycin D (7‐AAD) inclusion (Supplementary Figure 3).

Statistical analysis

All analyses were performed using SigmaPlot software (SYSTAT) or by SAS version 9.4. Parametric testing was performed by one‐way analysis of variance (ANOVA). When the one‐way ANOVA was significant, the Holm‐Sidak test was performed for pairwise comparisons of every combination of group pairs. When the data were not normally distributed or the equal variance test was not satisfied, nonparametric testing was performed by one‐way ANOVA on ranks. When the one‐way ANOVA on ranks was significant, Dunn's test was performed for pairwise comparisons of every combination of group pairs. Because the residuals were not normally distributed and/or the variances were not constant, correlations were calculated using Spearman rank order correlation. Linear regressions were performed to test associations between percentages of Foxp3⁺ cells and numbers of CD19⁺ or CD4⁺ cells. Interaction terms between mouse lines and CD19⁺ or CD4⁺ cells were included to test whether these associations differed between mouse lines. Pairwise comparisons were performed to test differences between each pair of mouse lines. For all tests, P ≤ 0.05 was considered significant. All reported studies were approved by the University of Southern California Institutional Animal Care and Use Committee.

RESULTS

B cell subsets in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice

We previously demonstrated that the distribution of B cell subsets in B6.Baff ^−/− mice differs substantially from that in B6.Br3 ^−/− mice. In each age and sex cohort tested, percentages and numbers of FO B cells were greater in B6.Br3 ^−/− mice than in the corresponding B6.Baff ^−/− mice, whereas percentages and numbers of CD21⁻CD23⁻ B cells were greater in B6.Baff ^−/− mice than in the corresponding B6.Br3 ^−/− mice. ³² To determine whether this difference in distribution of B cell subsets extends to SLE‐prone hosts, we analyzed cohorts of young male, young female, old male, and old female NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice.

Consistent with our previous observations, ³⁰ , ³¹ NZM.Baff ^−/− and NZM.Br3 ^−/− mice each harbored markedly fewer numbers (≥84% reduction) and percentages (≥78% reduction) of CD19⁺ cells than did NZM WT mice, regardless of the age or sex of the mice (P < 0.001 for each comparison; Figure 1A, Table 1). In each age and sex cohort, there were no significant differences between NZM.Baff ^−/− and NZM.Br3 ^−/− mice in the percentages or numbers of CD19⁺ cells (Figure 1A, Table 1). Moreover, although numbers and percentages of FO B cells were greater, albeit modestly, in NZM.Br3 ^−/− mice than in corresponding NZM.Baff ^−/− mice, differences in MZ B cells and CD21⁻CD23⁻ B cells (which includes ABCs) between the two mouse lines were not consistent (Table 1 and Figure 1B–D).

Figure 1.

B cells and B cell subsets in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice. Spleen cells from young male (24 NZM WT, 26 NZM.Baff ^−/− , 28 NZM.Br3 ^−/− ), young female (31 NZM WT, 28 NZM.Baff ^−/− , 20 NZM.Br3 ^−/− ), old male (23 NZM WT, 28 NZM.Baff ^−/− , 24 NZM.Br3 ^−/− ), and old female (31 NZM WT, 28 NZM.Baff ^−/− , 41 NZM.Br3 ^−/− ) mice were stained for surface CD19, CD21, and CD23 and analyzed for (A) the percentage of CD19⁺ cells (of mononuclear cells), (B) the percentage of FO B cells (of CD19⁺ cells), (C) the percentage of MZ B cells (of CD19⁺ cells), and (D) the percentage of CD21⁻CD23⁻ B cells (of CD19⁺ cells). Results are plotted as box plots. The WT box denotes NZM WT; the BAFF box denotes BAFF, NZM.Baff ^−/− ; the BR3 box denotes BR3, NZM.Br3 ^−/− . The lines inside the boxes indicate the medians; the outer borders of the boxes indicate the 25^th and 75^th percentiles; and the bars extending from the boxes indicate the 10^th and 90^th percentiles. All analyses were performed by one‐way ANOVA on ranks because the data were not normally distributed. In each panel shown, the null hypothesis was rejected (P < 0.001), and results are shown for the Dunn's test for all pairwise comparisons. ANOVA, analysis of variance; BAFF, B cell activating factor; BR3, B cell activating factor receptor 3; FO, follicular; MZ, marginal zone; WT, wild‐type. ****P ≤ 0.001 (NZM.Baff^−/− or NZM.Br3^−/− vs NZM WT); #P ≤ 0.05; ##P ≤ 0.01, ###P ≤ 0.005, ####P ≤ 0.001 (NZM.Baff^−/− vs NZM.Br3^−/−).

Table 1.

Splenic B cell subsets in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice^*

Age, sex, and genotype	Cell population
	CD19+ cells	FO B cells	MZ B cells	CD21−CD23− B cells
Young male
WT (n = 24), median (IQR)	16.6 (14.5–18.1)	10.4 (7.95–12.4)	1.00 (0.777–1.20)	1.96 (1.54–2.59)
Baff −/− (n = 26), median (IQR)	2.54 (1.79–3.67)	0.124 (0.089–0.159)	0.023 (0.005–0.045)	1.51 (1.04–1.93)
Br3 −/− (n = 28), median (IQR)	1.87 (1.70–2.82)	0.334 (0.223–0.461)	0.038 (0.024–0.055)	1.04 (0.795–1.59)
Overall P value	<0.001 a	<0.001 a	<0.001 a	<0.001 a
WT vs Baff −/− , P value	<0.001 a	<0.001 a	<0.001 a	0.081
WT vs Br3 −/− , P value	<0.001 a	<0.001 a	<0.001 a	<0.001 a
Baff −/− vs Br3 −/− , P value	0.674	0.003 a	0.385	0.067
Young female
WT (n = 31), median (IQR)	18.5 (11.9–23.0)	10.9 (8.03–13.8)	1.27 (0.720–1.55)	2.68 (1.69–3.86)
Baff −/− (n = 28), median (IQR)	2.76 (2.01–3.56)	0.176 (0.151–0.249)	0.012 (0.005–0.031)	1.46 (1.19–2.31)
Br3 −/− (n = 20), median (IQR)	2.41 (2.09–3.36)	0.442 (0.365–0.552)	0.033 (0.024–0.048)	1.40 (1.16–1.99)
Overall P value	<0.001 a	<0.001 a	<0.001 a	<0.001 a
WT vs Baff −/− , P value	<0.001 a	<0.001 a	<0.001 a	0.002 a
WT vs Br3 −/− , P value	<0.001 a	<0.001 a	<0.001 a	0.001 a
Baff −/− vs Br3 −/− , P value	1.000	0.003 a	0.248	1.000
Old male
WT (n = 23), median (IQR)	17.2 (14.6–18.6)	10.3 (7.55–12.5)	0.712 (0.494–0.958)	3.23 (2.66–4.57)
Baff −/− (n = 28), median (IQR)	1.26 (0.948–1.51)	0.045 (0.024–0.073)	0.007 (0.002–0.016)	0.866 (0.657–1.12)
Br3 −/− (n = 24), median (IQR)	0.863 (0.625–1.18)	0.130 (0.073–0.185)	0.008 (0.001–0.024)	0.451 (0.355–0.757)
Overall P value	<0.001 a	<0.001 a	<0.001 a	<0.001 a
WT vs Baff −/− , P value	<0.001 a	<0.001 a	<0.001 a	<0.001 a
WT vs Br3 −/− , P value	<0.001 a	<0.001 a	<0.001 a	<0.001 a
Baff −/− vs Br3 −/− , P value	0.228	0.010 a	1.000	0.030 a
Old female
WT (n = 31), median (IQR)	18.1 (14.0–22.2)	6.90 (4.80–9.28)	0.318 (0.140–0.690)	7.01 (4.78–8.84)
Baff −/− (n = 28), median (IQR)	2.07 (1.44–2.48)	0.069 (0.045–0.117)	0.022 (0.003–0.061)	1.15 (0.796–1.50)
Br3 −/− (n = 41), median (IQR)	1.24 (0.966–1.83)	0.119 (0.076–0.165)	0.001 (0.000–0.015)	0.756 (9.584–1.17)
Overall P value	<0.001 a	<0.001 a	<0.001 a	<0.001 a
WT vs Baff −/− , P value	<0.001 a	<0.001 a	<0.001 a	<0.001 a
WT vs Br3 −/− , P value	<0.001 a	<0.001 a	<0.001 a	<0.001 a
Baff −/− vs Br3 −/− , P value	0.062	0.288	0.008 a	0.234

^*Results are in millions and are expressed as medians (IQR) because the normality tests did not pass. All analyses were performed by one‐way ANOVA on ranks because the data were not normally distributed. Dunn's test was employed for all pairwise comparisons. ANOVA, analysis of variance; BAFF, B cell activating factor; BR3, B cell activating factor receptor 3; FO, follicular; IQR, interquartile range; MZ, marginal zone; WT, wild‐type.

^a Significance at P ≤ 0.05.

CD3 ⁺ and CD4 ⁺ cells in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice

The similar numbers of CD19⁺ cells in NZM.Br3 ^−/− and NZM.Baff ^−/− mice in each age and sex cohort argue against the notion that numbers of B cells per se are at the root of the divergent clinical phenotypes of these mice. Because CD4⁺ T cells play a central role in driving the development and maintenance of SLE, ³⁴ , ³⁵ we turned to T cells. Whereas NZM.Baff ^−/− and NZM.Br3 ^−/− mice harbored fewer CD3⁺ cells and CD4⁺ cells in each age and sex cohort than did the corresponding NZM WT mice, the reductions were modest (1.3%–29.8% reduction for CD3⁺ cells and 9.8%–36.7% reduction for CD4⁺ cells; Table 2). Moreover, numbers of CD3⁺ cells and CD4⁺ cells did not differ between male NZM.Baff ^−/− and NZM.Br3 ^−/− mice at any age, and despite young female NZM.Br3 ^−/− mice harboring more CD3⁺ cells and CD4⁺ cells than their NZM.Baff ^−/− counterparts, this difference dematerialized in old female mices.

Table 2.

Splenic T cell subsets in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice^*

Age, sex, and genotype	Cell population
	CD3+ cells	CD4+ cells	Foxp3+ cells	CD25+Foxp3+ cells
Young male
WT (n = 24), median (IQR)	29.2 (25.9–31.2)	19.9 (17.5–21.5)	1.66 (1.39–1.81)	1.35 (1.15–1.46)
Baff −/− (n = 26), median (IQR)	20.5 (18.3–28.5)	12.6 (11.5–16.1)	1.06 (0.909–1.23)	0.890 (0.798–1.03)
Br3 −/− (n = 28), median (IQR)	23.8 (18.0–31.0)	14.9 (11.6–18.9)	1.01 (0.850–1.27)	0.875 (0.717–1.09)
Overall P value	0.004 a	<0.001 a	<0.001 a	<0.001 a
WT vs Baff −/− , P value	0.003 a	<0.001 a	<0.001 a	<0.001 a
WT vs Br3 −/− , P value	0.068	0.005 a	<0.001 a	<0.001 a
Baff −/− vs Br3 −/− , P value	0.872	0.700	1.000	1.000
Young female
WT (n = 24), mean ± SD	31.4 ± 8.28	21.5 ± 5.77	1.79 ± 0.440	1.47 ± 0.361
Baff −/− (n = 28), mean ± SD	23.5 ± 7.41	13.9 ± 4.31	1.08 ± 0.453	0.923 ± 0.373
Br3 −/− (n = 20), mean ± SD	31.0 ± 9.79	19.4 ± 6.45	1.38 ± 0.435	1.20 ± 0.384
Overall P value	0.001 a	<0.001 a	<0.001 a	<0.001 a
WT vs Baff −/− , P value	0.003 a	<0.001 a	<0.001 a	<0.001 a
WT vs Br3 −/− , P value	0.873	0.206	0.006 a	0.029 a
Baff −/− vs Br3 −/− , P value	0.006 a	0.002 a	0.027 a	0.019 a
Old male
WT (n = 23), median (IQR)	24.2 (19.9–29.4)	17.5 (14.4–21.2)	2.25 (1.74–2.53)	1.70 (1.41–1.93)
Baff −/− (n = 28), median (IQR)	20.7 (17.1–23.2)	13.8 (11.4–15.1)	1.16 (0.984–1.36)	0.926 (0.824–1.11)
Br3 −/− (n = 24), median (IQR)	19.2 (15.9–22.1)	12.8 (10.6–14.5)	1.06 (0.845–1.26)	0.881 (0.707–1.05)
Overall P value	0.014 a	<0.001 a	<0.001 a	<0.001 a
WT vs Baff −/− , P value	0.069	0.001 a	<0.001 a	<0.001 a
WT vs Br3 −/− , P value	0.017 a	<0.001 a	<0.001 a	<0.001 a
Baff −/− vs Br3 −/− , P value	1.000	1.000	1.000	1.000
Old female
WT (n = 31), median (IQR)	28.2 (21.1–34.1)	18.8 (14.2–24.4)	2.44 (1.93–3.19)	2.02 (1.49–2.58)
Baff −/− (n = 28), median (IQR)	22.4 (15.8–29.5)	13.6 (9.56–18.0)	1.41 (1.15–1.58)	1.09 (0.857–1.32)
Br3 −/− (n = 41), median (IQR)	22.6 (15.9–26.7)	15.1 (10.0–16.9)	1.26 (1.05–1.73)	1.04 (0.853–1.40)
Overall P value	0.016 a	<0.001 a	<0.001 a	<0.001 a
WT vs Baff −/− , P value	0.047 a	0.002 a	<0.001 a	<0.001 a
WT vs Br3 −/− , P value	0.028 a	0.005 a	<0.001 a	<0.001 a
Baff −/− vs Br3 −/− , P value	1.000	1.000	1.000	1.000

^*Results are in millions and are expressed as mean ± SD when both the normality and equal variance tests passed or as median (IQR) when the normality tests did not pass. Analyses were performed by one‐way ANOVA or by one‐way ANOVA on ranks when the data were not normally distributed or when the equal variance test was not satisfied. Results are also shown for the Holm‐Sidak test or Dunn's test for all pairwise comparisons. ANOVA, analysis of variance; BAFF, B cell activating factor; BR3, B cell activating factor receptor 3; Foxp3, forkhead box P3; IQR, interquartile range; WT, wild‐type.

^a Significance atP values ≤ 0.05.

The similarities in absolute numbers of CD3⁺ and CD4⁺ cells in NZM.Baff ^−/− and NZM.Br3 ^−/− mice notwithstanding, the percentages of CD3⁺ and CD4⁺ cells in these mice differed. With the exception of young male mice, percentages of CD3⁺ and CD4⁺ cells were significantly greater in NZM.Br3 ^−/− mice than in corresponding NZM.Baff ^−/− mice (Figure 2A–B). Of note, the ratios of CD4⁺ cells to CD3⁺ cells were also significantly greater in NZM.Br3 ^−/− mice than in corresponding NZM.Baff ^−/− mice in each age and sex other than young male mice (Figure 2C).

Figure 2.

CD3⁺ cells and CD4⁺ cells in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice. Spleen cells from young male (24 NZM WT, 26 NZM.Baff ^−/− , 28 NZM.Br3 ^−/− ), young female (24 NZM WT, 28 NZM.Baff ^−/− , 20 NZM.Br3 ^−/− ), old male (23 NZM WT, 28 NZM.Baff ^−/− , 24 NZM.Br3 ^−/− ), and old female (31 NZM WT, 28 NZM.Baff ^−/− , 41 NZM.Br3 ^−/− ) mice were stained for surface CD3 and CD4 and analyzed for (A) the percentage of CD3⁺ cells, (B) the percentage of CD4⁺ cells, and (C) the ratio of CD4⁺ cells to CD3⁺ cells. Analyses were performed by one‐way ANOVA or by one‐way ANOVA on ranks when the data were not normally distributed or the equal variance test was not satisfied. In each panel shown, the null hypothesis was rejected (P < 0.001) with the exceptions of the percentage of CD3⁺ cells for young males (P = 0.013) and the percentage of CD4⁺ cells for young males (P > 0.05). Results are shown for the Holm‐Sidak test or Dunn's test for all pairwise comparisons and are plotted as in Figure 1. ANOVA, analysis of variance; BAFF, B cell activating factor; BR3, B cell activating factor receptor 3; WT, wild‐type. ****P ≤ 0.001 (NZM.Baff^−/− or NZM.Br3^−/− vs NZM WT); #P ≤ 0.05; ##P ≤ 0.01, ###P ≤ 0.005, ####P ≤ 0.001 (NZM.Baff^−/− vs NZM.Br3^−/−).

Foxp3⁺ cells in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice

A greater percentage of CD4⁺ cells and an increased ratio of CD4⁺ cells to CD3⁺ cells ratio in NZM.Br3 ^−/− mice relative to those in NZM.Baff ^−/− mice does not necessarily indicate a disproportionately greater expression of effector T cells in the former than in the latter. CD4⁺Foxp3⁺ T cells play an indispensable role in immune homeostasis, as evidenced by the rapid and lethal autoimmune T cell proliferative disease that develops in both Foxp3 ^−/− mice and Scurfy mice (which bear a nonfunctional mutated Foxp3 gene) and by the ability of adoptively transferred Treg cells from a Foxp3‐sufficient host to rescue Foxp3‐deficient recipients from disease development. ³⁶ , ³⁷ , ³⁸

Numbers of Foxp3⁺ cells were significantly reduced in both NZM.Baff ^−/− and NZM.Br3 ^−/− mice in comparison to NZM WT mice across each age and sex cohort (Table 2). Numbers of Foxp3⁺ cells harbored by young male, old male, and old female NZM.Baff ^−/− mice did not differ from those harbored by the corresponding NZM.Br3 ^−/− mice, and Foxp3⁺ cells were lesser in number in young female NZM.Baff ^−/− mice than in young female NZM.Br3 ^−/− mice (Table 2).

Nevertheless, percentages of Foxp3⁺ cells varied substantially among NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice. In each age and sex cohort, there was a hierarchy in the percentages of Foxp3⁺ cells, with percentages being greatest in NZM WT mice, lowest NZM.Br3 ^−/− mice, and intermediate in NZM.Baff ^−/− mice (Figure 3A). That is, despite the greater percentages of CD4⁺ cells and greater CD4/CD3 ratios in NZM.Br3 ^−/− mice than in NZM.Baff ^−/− mice, percentages of Foxp3⁺ cells in NZM.Br3 ^−/− mice were lower than those in NZM.Baff ^−/− mice in each age and sex cohort, with the differences achieving statistical significance in young male, old male, and old female mice.

Figure 3.

Foxp3⁺ cells and CD25⁺Foxp3⁺ cells in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice. Spleen cells from young male (24 NZM WT, 21 NZM.Baff ^−/− , 28 NZM.Br3 ^−/− ), young female (24 NZM WT, 27 NZM.Baff ^−/− , 20 NZM.Br3 ^−/− ), old male (23 NZM WT, 28 NZM.Baff ^−/− , 24 NZM.Br3 ^−/− ), and old female (29 NZM WT, 28 NZM.Baff ^−/− , 41 NZM.Br3 ^−/− ) mice were analyzed for (A) Foxp3⁺ cells and (B) CD25⁺Foxp3⁺ cells. Analyses were performed by one‐way ANOVA or by one‐way ANOVA on ranks when the data were not normally distributed or the equal variance test was not satisfied. In each panel shown, the null hypothesis was rejected (P ≤ 0.001) with the exception of the percentage of CD25⁺Foxp3⁺ cells for young females (P > 0.05). Results are shown for the Holm‐Sidak test or Dunn's test for all pairwise comparisons and are plotted as in Figure 1. (C) Percentages of Foxp3⁺ cells and (D) percentages of CD25⁺Foxp3⁺ cells versus CD19⁺ cells are plotted for the 100 NZM WT (green), 104 NZM.Baff ^−/− (pink), and 113 NZM.Br3 ^−/− (blue) mice reported in panels A and B. Circles represent the individual mice, and the lines represent the linear regressions. ANOVA, analysis of variance; BAFF, B cell activating factor; BR3, B cell activating factor receptor 3; Foxp3, forkhead box P3; WT, wild‐type. ****P ≤ 0.001 (NZM.Baff^−/− or NZM.Br3^−/− vs NZM WT); #P ≤ 0.05; ##P ≤ 0.01, ###P ≤ 0.005, ####P ≤ 0.001 (NZM.Baff^−/− vs NZM.Br3^−/−).

Because CD25⁻Foxp3⁺ cells may display in vivo plasticity and convert to proinflammatory Th17 cells, ³⁹ we also assessed percentages and numbers of CD25⁺Foxp3⁺ cells. In each mouse line, numbers of CD25⁺Foxp3⁺ cells correlated strongly with numbers of Foxp3⁺ cells (r = 0.977 for NZM WT, r = 0.957 for NZM.Baff ^−/− , r = 0.990 for NZM.Br3 ^−/− ; P < 0.001 for each comparison), and percentages CD25⁺Foxp3⁺ cells correlated strongly with percentages of Foxp3⁺ cells (r = 0.978 for NZM WT, r = 0.913 for NZM.Baff ^−/− , r = 0.899 for NZM.Br3 ^−/− ; P < 0.001 for each comparison). As with numbers of Foxp3⁺ cells, there were no significant differences in numbers of CD25⁺Foxp3⁺ cells among young male, old male, and old female NZM.Baff ^−/− mice and the corresponding NZM.Br3 ^−/− mice (Table 2). As with percentages of Foxp3⁺ cells, there was a hierarchy in percentages of CD25⁺Foxp3⁺ cells, with percentages generally being greatest in NZM WT mice, lowest in NZM.Br3 ^−/− mice, and intermediate in NZM.Baff ^−/− mice (Figure 3B).

Relationships between percentages of Foxp3⁺ and CD25 ⁺Foxp3⁺ cells and numbers of CD19 ⁺ cells in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice

Not only were percentages of Foxp3⁺ and CD25⁺Foxp3⁺ cells in NZM.Br3 ^−/− mice lower than those in corresponding NZM.Baff ^−/− mice, but the relationships between percentages of Foxp3⁺ and CD25⁺Foxp3⁺ cells and numbers of CD19⁺ cells in these two mouse lines also differed. Although linear regression analyses for the percentage of Foxp3⁺ or the percentage of CD25⁺Foxp3⁺ cells versus CD19⁺ cells yielded positive estimated slopes for NZM.Baff ^−/− mice (0.196 and 0.231, respectively), the corresponding estimated slopes were negative for NZM.Br3 ^−/− mice (−0.226 and −0.099, respectively; Figure 3C–D), with the differences between the two mouse strains being statistically significant (P = 0.041 and P = 0.034, respectively). Linear regression analyses for the percentage of Foxp3⁺ or the percentage of CD25⁺Foxp3⁺ cells compared with CD4⁺ cells also documented numerical differences between the estimated slopes for NZM.Baff ^−/− and NZM.Br3 ^−/− mice, but these differences failed to achieve significant differences (P ≥ 0.468).

Differential in vivo proliferation and survival of CD25 ⁺Foxp3⁺ cells in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice

In light of the differential relationships that percentages of Foxp3⁺ and CD25⁺Foxp3⁺ cells had with numbers of CD19⁺ cells in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice, we interrogated the in vivo proliferation and survival of CD25⁺Foxp3⁺ cells. Strikingly, both in vivo proliferation (as assessed by expression of Ki‐67) and in vivo survival (as assessed by annexin V nonexpression and 7‐AAD exclusion) in NZM.Baff ^−/− and NZM.Br3 ^−/− mice differed from each other in every age and sex cohort, with proliferation and survival each being lower in NZM.Baff ^−/− mice than in NZM.Br3 ^−/− mice (Figure 4).

Figure 4.

In vivo proliferation and survival of CD25⁺Foxp3⁺ cells in NZM WT, NZM.Baff ^−/− , and NZM.Br3 ^−/− mice. (A) Spleen cells from young male (19 NZM WT, 20 NZM.Baff ^−/− , 28 NZM.Br3 ^−/− ), young female (19 NZM WT, 28 NZM.Baff ^−/− , 17 NZM.Br3 ^−/− ), old male (6 NZM WT, 24 NZM.Baff ^−/− , 16 NZM.Br3 ^−/− ), and old female (12 NZM WT, 28 NZM.Baff ^−/− , 2 NZM.Br3 ^−/− ) mice were gated on the CD4⁺CD25⁺Foxp3⁺ population and analyzed for (A) Ki‐67 expression and for (B) annexin V nonexpression and 7‐AAD exclusion. Analyses were performed by one‐way ANOVA or by one‐way ANOVA on ranks when the data were not normally distributed or the equal variance test was not satisfied. In each panel shown, the null hypothesis was rejected (P ≤ 0.034). Results are shown for the Holm‐Sidak test or Dunn's test for all pairwise comparisons and are plotted as in Figure 1. 7‐AAD, 7‐aminoactinomycin D; ANOVA, analysis of variance; BAFF, B cell activating factor; BR3, B cell activating factor receptor 3; Foxp3, forkhead box P3; Ki‐67, Antigen Kiel 67; WT, wild‐type. ****P ≤ 0.001 (NZM.Baff^−/− or NZM.Br3^−/− vs NZM WT); #P ≤ 0.05; ##P ≤ 0.01, ###P ≤ 0.005, ####P ≤ 0.001 (NZM.Baff^−/− vs NZM.Br3^−/−).

DISCUSSION

There is no question that the pharmacologic inhibition of BAFF can be beneficial to patients with SLE. The BAFF inhibitor, belimumab, demonstrated efficacy in four independent randomized, double‐blind, placebo‐controlled trials in patients with SLE, ⁵ , ⁶ , ⁷ , ⁸ and its effectiveness has been well documented for SLE in real world experience. ⁴⁰ , ⁴¹ , ⁴² Despite other BAFF inhibitors not having been successful in SLE clinical trials, ⁴³ , ⁴⁴ , ⁴⁵ telitacicecept, a BAFF and a proliferation‐inducing ligand (APRIL) inhibitor, has shown great promise in early clinical trials ⁴⁶ and has been approved in China for the treatment of SLE ⁴⁷ and shown real world effectiveness in China. ⁴⁸ Given that BAFF inhibitors lead to reductions in B cells in the context of clinical benefit, ⁴⁹ , ⁵⁰ it has been presumed that the clinically relevant effects of BAFF inhibition are predominantly, if not solely, due to effects on B cells.

Our present study challenges this presumption. Despite BR3 being the BAFF receptor that plays the dominant role in BAFF‐driven B cell survival, ²⁴ , ²⁵ , ²⁶ BR3‐deficient NZM.Br3 ^−/− mice (which bear fewer B cells than NZM.Baff ^−/− mice) develop clinical disease with the same time course and severity as do BR3‐sufficient NZM WT mice, ³¹ and A/WySnJ mice (which bear a mutated Br3 gene) develop elevated serum titers of IgG anti‐double stranded DNA (dsDNA) antibodies and clinically overt glomerulonephritis as they age. ⁵¹

A priori, one could argue that a difference between NZM.Baff ^−/− and NZM.Br3 ^−/− mice in distribution of B cell subsets rather than in the total number of B cells is what drives their disparate development of clinical disease. ABCs have been ascribed a role in autoimmunity, ⁵² , ⁵³ so a greater number of ABCs or a disproportionately high representation of ABCs could help drive an underlying autoimmune diathesis into frank clinical disease. However, NZM.Br3 ^−/− mice, in comparison to NZM.Baff ^−/− mice, harbored neither greater numbers of CD21⁻CD23⁻ B cells (which includes ABCs) nor a skewed distribution of B cells favoring CD21⁻CD23⁻ B cells. Thus, the disparate development of clinical disease between NZM.Baff ^−/− mice, which are largely protected from clinical disease, and NZM.Br3 ^−/− mice, which develop clinical disease with the same time course and severity as do NZM WT mice, likely cannot be attributed to ABCs.

Nonetheless, some B cell‐related differences between NZM.Baff ^−/− and NZM.Br3 ^−/− mice could be contributory to their disparate clinical outcomes. We previously documented reductions of Ig‐secreting cells, plasma cells, and the number and size of germinal centers in NZM.Baff ^−/− mice in comparison with those in NZM WT mice. Of note, serum levels of IgG antichromatin and IgG anti‐histone were no different in old (7–9 months of age) NZM.Baff ^−/− mice than in age‐matched NZM WT mice, and serum levels of anti‐dsDNA did not differ between NZM.Baff ^−/− mice and NZM WT mice at any tested age (4–6 months, 7–9 months, 10–13 months). ³⁰ In contrast, we previously documented that despite the profound reduction in B cells in NZM.Br3 ^−/− mice, numbers of spleen and bone marrow plasma cells in these mice were similar to those in NZM WT mice. In addition, serum levels of anti‐dsDNA were lower at four to six months of age in NZM.Br3 ^−/− mice than in NZM WT mice, although they caught up by seven to nine months of age. ³¹

Although these B cell‐related differences may contribute to the disparate clinical outcomes observed in NZM.Baff ^−/− and NZM.Br3 ^−/− mice, T cell‐related differences may certainly be contributory as well. In nonautoimmune‐prone B6 mice, percentages of Foxp3⁺ cells and CD25⁺Foxp3⁺ cells are lower in old B6.Br3 ^−/− mice than in corresponding old B6.Baff ^−/− mice. ³² In SLE‐prone NZM mice, percentages of CD3⁺ and CD4⁺ cells were greater in NZM.Br3 ^−/− mice than in corresponding NZM.Baff ^−/− mice, with the ratios of CD4⁺ cells to CD3⁺ cells also being greater in NZM.Br3 ^−/− mice than in corresponding NZM.Baff ^−/− mice. Despite the relative increase in CD4⁺ cells in NZM.Br3 ^−/− mice, percentages of Foxp3⁺ cells and CD25⁺Foxp3⁺ cells were numerically lower in NZM.Br3 ^−/− mice than in corresponding NZM.Baff ^−/− mice in each age and sex cohort. This implies that effector CD4⁺ cells (including pathogenic ones that drive disease) may be more represented in NZM.Br3 ^−/− mice than in NZM.Baff ^−/− mice. Elucidation of differences, if any, between NZM.Baff ^−/− and NZM.Br3 ^−/− mice in the distribution of effector CD4⁺ cells producing proinflammatory cytokines (eg, IL‐17, IFNγ) or in levels of circulating proinflammatory cytokines will require further investigation. In addition, since CD8⁺ cells were not directly enumerated in our study, identification of a possible contribution of these cells to the disparate clinical outcomes between NZM.Baff ^−/− and NZM.Br3 ^−/− mice also requires further investigation.

Moreover, the relationships between percentages of Foxp3⁺ cells or CD25⁺Foxp3⁺ cells and CD19⁺ cells strikingly differed between NZM.Baff ^−/− and NZM.Br3 ^−/− mice. Although the percentages of Foxp3⁺ cells and CD25⁺Foxp3⁺ cells increased in the former as the CD19⁺ cell count rose, the percentages of Foxp3⁺ cells and CD25⁺Foxp3⁺ cells decreased in the latter as the CD19⁺ cell count rose.

Collectively, these results point to BAFF–BCMA and BAFF–TACI interactions affecting T cell responses in vivo. Indeed, BAFF overexpression augments in vivo Th1 inflammatory responses while suppressing Th2 inflammatory responses, ⁵⁴ and the frequency and absolute numbers of Foxp3⁺ cells are greater in B6 mice that bear a Baff transgene than in B6 WT mice, whereas Foxp3⁺ cells are reduced in B6.Baff ^−/− mice. ⁵⁵ , ⁵⁶ Experiments are needed in mice singly‐deficient in BCMA or TACI, in mice doubly‐deficient in both BCMA and TACI, and in mice deficient in APRIL (because APRIL engages both BCMA and TACI) ⁵⁷ , ⁵⁸ , ⁵⁹ , ⁶⁰ to help dissect the contributions of BCMA and TACI to in vivo T cell responses in nonautoimmune‐prone and autoimmune (SLE)‐prone hosts.

Our results with NZM congenic mice mirror our previous results with B6 congenic mice in some ways, including the greater percentages of FO B cells in BR3‐deficient mice than in the corresponding BAFF‐deficient mice and the lower percentages of Foxp3⁺ cells and CD25⁺Foxp3⁺ cells in BR3‐deficient mice than in the corresponding BAFF‐deficient mice. Nevertheless, some important differences emerged. Although the relationships between percentages of Foxp3⁺ cells or CD25⁺Foxp3⁺ cells and CD4⁺ cells were divergent in B6.Baff ^−/− and B6.Br3 ^−/− mice, they were similar in NZM.Baff ^−/− and NZM.Br3 ^−/− mice. Conversely, although the relationships between percentages of Foxp3⁺ cells or CD25⁺Foxp3⁺ cells and CD19⁺ cells were similar in B6.Baff ^−/− and B6.Br3 ^−/− mice, they were divergent in NZM.Baff ^−/− and NZM.Br3 ^−/− mice. Moreover, although in vivo survival of CD25⁺Foxp3⁺ cells was greater in B6.Baff ^−/− mice than in B6.Br3 ^−/− mice, in vivo survival of CD25⁺Foxp3⁺ cells was greater in NZM.Br3 ^−/− mice than in NZM.Baff ^−/− mice.

Although our results demonstrate differences between NZM.Baff ^−/− and NZM.Br3 ^−/− mice in numbers of Foxp3⁺ (and CD25⁺Foxp3⁺) cells, differences in suppressor function, if any, were not assessed and, therefore, remain yet to be determined. In that light, we previously reported identical in vitro suppressive activity (as assessed by suppression of division and proliferation of anti‐CD3‐stimulated CD4⁺ cells) of Foxp3⁺ cells isolated from B6 WT mice, B6.Baff ^−/− mice, and B6 mice bearing a Baff transgene. ⁵⁶ Unpublished pilot experiments demonstrated that Foxp3⁺ cells isolated from B6.Br3 ^−/− mice also had the same in vitro suppressive activity as did Foxp3⁺ cells isolated from B6 WT mice.

Experiments performed subsequent to the studies stated above, however, convinced us that in vitro suppressor assays of Foxp3⁺ cells do not reliably inform on the ability of these cells to suppress in vivo. Complete absence of CTLA‐4 in Ctla4 ^−/− mice promotes unopposed CD28‐driven costimulation of T cells, resulting in marked T cell expansion, infiltration of vital organs, and death by three to six weeks of age. ⁶¹ , ⁶² To study the function of Foxp3⁺ cells in such mice, we generated littermate B6.Ctla4 ^+/+ , B6.Ctla4 ^+/− , and B6.Ctla4 ^−/− mice that bore the same Foxp3 ^gfp knock‐in construct as in the present study. By studying B6.Ctla4 ^−/− mice at 3 weeks of age (a time just before the onset of death in such mice) and their B6.Ctla4 ^+/+ and B6.Ctla4 ^+/− littermates at the same time, we demonstrated that along with the expected marked global expansion of T cells in the B6.Ctla4 ^−/− mice, Foxp3⁺ cell expansion was greater in the B6.Ctla4 ^−/− mice than in their B6.Ctla4 ^+/+ or B6.Ctla4 ^+/− littermates. Importantly and counterintuitively, in vitro suppressor activity of Foxp3⁺ cells on a per‐cell basis from B6.Ctla4 ^−/− mice was identical to that of Foxp3⁺ cells from their B6.Ctla4 ^+/+ or B6.Ctla4 ^+/− littermates. ⁶³ That is, CTLA‐4‐deficient Foxp3⁺ cells exhibited normal in vitro suppressive activity despite their inability to prevent lethal T cell lymphoproliferation in vivo, demonstrating a disconnect between the in vitro suppression assay and in vivo biology. Thus, functional assessment of Foxp3⁺ (and CD25⁺Foxp3⁺) cells in NZM.Baff ^−/− and NZM.Br3 ^−/− mice will require future labor‐ and time‐intensive in vivo experiments, such as adoptive transfer studies and generation of bone marrow chimeras.

The differences in percentages of Foxp3⁺ (and CD25⁺Foxp3⁺) cells and in CD4 to CD3 ratios between NZM.Baff ^−/− and NZM.Br3 ^−/− mice are quantitatively modest. Nevertheless, persistent small quantitative differences over protracted periods of time can have meaningful clinical ramifications. For example, with incremental modest increases in serum uric acid level, the rates of acute gout flares and associated hospitalizations substantially increase. ⁶⁴ Thus, in hosts that bear a genetic diathesis to SLE (NZM genetic background), quantitatively modest differences in certain immune parameters (B cell‐based and T cell‐based) could be the difference between protection from disease and development of disease. Detailed studies of in vivo biology, rather than just in vitro or ex vivo studies, are indispensable and will be necessary to truly understand underlying pathogenesis and maintenance of clinical disease.

Our unexpected findings suggest that BAFF–BCMA and/or BAFF–TACI interactions in an SLE‐prone host help drive development of clinical disease even under conditions of considerable B cell depletion. Indeed, NZM mice doubly‐deficient for BR3 and BCMA (NZM.Br3 ^−/− .Bcma ^−/− mice) or doubly‐deficient for BR3 and TACI (NZM.Br3 ^−/− .Taci ^−/− mice) are largely protected from development of clinical disease. ⁶⁵ This raises the possibility that insufficient blocking of BAFF–BCMA and/or BAFF–TACI interactions may lie at the heart of the incomplete clinical response to belimumab in human SLE. ⁵ , ⁶ , ⁷ , ⁸ In addition, the increased level of circulating BAFF that ensues following administration of rituximab to patients with SLE ⁶⁶ , ⁶⁷ with the resultant increased BAFF available to interact with BCMA and/or TACI may have contributed to the failure of rituximab in SLE clinical trials. ⁶⁸ , ⁶⁹ Further studies are certainly warranted and needed.

An important caveat to all in vivo studies of hosts with germline deletions, including the present study, is that the biologic and clinical changes observed in such hosts do not necessarily predict the biologic and clinical responses in genetically unaltered hosts to corresponding pharmacologic treatments. In NZM.Br3 ^−/− mice, the increased (or excessive) BAFF–BCMA and BAFF–TACI interactions resulting from the lifelong absence of BR3 and the attendant lifelong increase in circulating BAFF ³¹ may have facilitated development of clinical disease. In a genetically unaltered NZM host in which BAFF–BCMA or BAFF–TACI interactions had not been excessive, pharmacologic targeting of BR3 could potentially be successful. Indeed, a phase 2b clinical trial in primary Sjögren disease of ianalumab, an anti‐BR3 mAb, met its primary endpoint, ⁷⁰ and a phase 3 clinical trial of ianalumab in human SLE is currently recruiting participants (NCT05639114).

A final point to emphasize is that neither BAFF nor BR3 is specific to B cells. BAFF can stimulate T cells in vitro in the absence of B cells ⁷¹ and polarize T cell responses in vivo in B cell‐deficient mice. ⁵⁴ BR3 is expressed not only on B cells but on activated T cells and dendritic cells as well. ¹² Thus, although the reduction in B cells in hosts bearing disrupted Baff or Br3 genes may be the most readily apparent phenotypic alteration in such hosts, differential alterations more subtle than the reductions in B cells in NZM.Baff ^−/− compared with NZM.Br3 ^−/− mice likely contribute to profound differences in clinical outcomes.

AUTHOR CONTRIBUTIONS

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr W. Stohl had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design

W. Stohl.

Acquisition of data

Wu.

Analysis and interpretation of data

W. Stohl, M. Stohl.

Supporting information

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DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.