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. 2018 Jan 30;22(5):1276-1287.
doi: 10.1016/j.celrep.2018.01.015.

Age-Associated Decline in Thymic B Cell Expression of Aire and Aire-Dependent Self-Antigens

Affiliations

Age-Associated Decline in Thymic B Cell Expression of Aire and Aire-Dependent Self-Antigens

Sergio Cepeda et al. Cell Rep. .

Abstract

Although autoimmune disorders are a significant source of morbidity and mortality in older individuals, the mechanisms governing age-associated increases in susceptibility remain incompletely understood. Central T cell tolerance is mediated through presentation of self-antigens by cells constituting the thymic microenvironment, including epithelial cells, dendritic cells, and B cells. Medullary thymic epithelial cells (mTECs) and B cells express distinct cohorts of self-antigens, including tissue-restricted self-antigens (TRAs), such that developing T cells are tolerized to antigens from peripheral tissues. We find that expression of the TRA transcriptional regulator Aire, as well as Aire-dependent genes, declines with age in thymic B cells in mice and humans and that cell-intrinsic and cell-extrinsic mechanisms contribute to the diminished capacity of peripheral B cells to express Aire within the thymus. Our findings indicate that aging may diminish the ability of thymic B cells to tolerize T cells, revealing a potential mechanistic link between aging and autoimmunity.

Keywords: Aire; B cell; aging; thymus.

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Conflict of interest statement

DECLARATION OF INTERESTS

The authors declare no competing interests.

Figures

Figure 1
Figure 1. Increased B Cell Frequency and Altered Phenotype in the Aged Mouse Thymus
(A) Frequency (percentage of viable singlets) expressing surface CD19 cells in young (5 weeks) and aged (10–24 months) mouse thymus (n = 11). (B) Representative surface IgD and IgM staining (gated on CD19+ viable singlets) on intrathymic B cells in aged (12 months) mouse thymus. Data are mean ± SEM. (C) Frequency of IgM+IgD+, IgM+IgD, and IgMIgD cells among CD19+ viable singlets in young (5 weeks, n = 6) and aged (10–24 months, n = 8) mouse thymus. (D) Representative surface CD23 and CD21 staining (gated on CD19+CD93CD43 viable singlets) in spleen and thymus from a 12-month-old mouse. (E) Frequency of CD21CD23 “ABCs” among CD19+CD93CD43 viable singlets in thymus of 5-week-old (n = 5) and 12- to 24-month-old (n = 4) mice. p values were calculated using unpaired two-tailed Student’s t test. See also Figure S1.
Figure 2
Figure 2. Distinct Gene Expression Signature and Loss of Aire Expression in Aged Intrathymic B Cells
Gene expression in sorted (≥98.5% purity) CD19+ intrathymic B cells was analyzed using RNA-seq in young (5 weeks) and aged (12–24 months) thymus. (A) Unsupervised hierarchical clustering of genes (log2 signal SD > 0.5) distinguishes B cells from young (5 weeks, n = 7) and aged (12–24 months, n = 5) thymus. (B) Analysis of differentially expressed genes (false discovery rate [FDR] value < 0.05, fold change > 2). Colors indicate statistically significantly decreases (green) or increases (red) in gene expression with age. Top five most significantly changed genes are labeled. Aire was revealed as the gene with the most statistically significant change (decrease) in aged intrathymic B cells. (C) RNA-seq RPKM expression values for Aire, RANK, CD40, CD80, T-bet, and CD11c in sorted (≥98.5% purity) intrathymic B cells from 5-week-old (n = 7) and 12- to 24-month-old (n = 5) mice. Bars indicate mean ± SEM. (D) RNA-seq RPKM expression values for Mxd1, Myb, Rbpj, and Rogdi as described in (A). Bars indicate mean ± SEM. p values were calculated using limma. See also Figure S2.
Figure 3
Figure 3. Aire and Aire-Dependent Gene Expression in Mouse and Human Intrathymic B Cells Diminishes with Age
(A) RNA-seq RPKM values for Aire (black) and RANK (red) in sorted human intrathymic B cells (≥98.5% purity) from young (3 months, 5 months, and 4 years; n = 3) and aged (42–61 years, n = 3) patients. Individuals are represented by unique symbols. (B) Relative expression of genes in the Aire-dependent B cell-specific gene list (Yamano) and a random list of similar size, in intrathymic B cells from young (5 weeks, n = 5) and aged (12–24 months, n = 7) mice (left) and young (3 months, 5 months, and 4 years; n = 3) and aged (42–61 years, n = 3) humans. Statistically significant changes (calculated using limma; see Experimental Procedures) are indicated in black, and changes not statistically significant are shown in gray. p values for over-representation of up- or down-regulated genes were calculated by chi-square testing. See also Table S1.
Figure 4
Figure 4. Aire Expression in Aged Intrathymic B Cells Is Diminished on a per Cell Basis and in All IgG Subclasses
(A) Expression of Aire-GFP in IgM+IgD+, IgM+IgD, and IgMIgD thymic B cells in Adig reporter mice (green) or reporter negative (gray) control mice. Representative gating strategy is shown on the left and Aire-driven GFP expression on the right. (B) Frequency of Aire-GFP+ cells within each IgM/IgD subset of thymic B cells in 5-week-old (n = 6) and 12- to 24-month-old (n = 4) Adig mice. Bars indicate mean ± SEM. p values were calculated using unpaired two-tailed Student’s t test. (C) Frequency of IgG1, IgG2a, IgG2b, and IgG3 class-switched cells within the CD19+IgMIgD subset of thymic B cells in 5-week-old (n = 5 or 6) mice. (D) Frequency of IgG2a and IgG2b cells within the CD19+IgMIgD subset of thymic B cells in 5-week-old (n = 4–6) and 12- to 24-month-old (n = 3 or 4) mice. (E) Frequency of Aire-GFP expression in each IgG subset in 5-week-old Adig mice (n = 4). Gated on viable singlet CD19+IgMIgD and respective IgG. (F) Frequency of Aire-GFP+ cells in the IgG1 and IgG2b subsets in 5-week-old (n = 4) and 12- to 24-month-old (n = 3) Adig mice. p values were calculated using unpaired two-tailed Student’s t test. Gated on viable singlet CD19+IgMIgD and respective IgG. See also Figure S3.
Figure 5
Figure 5. Age-Associated Decline in the Capacity of Peripheral B Cells to Be Licensed to Express Aire in Thymus Despite Increased CD40-Mediated Aire Induction
(A) Representative sorting gates for donor LN B cells from Adig mice stained for surface CD19, IgD, and IgG. (B) Representative post-sort re-analysis of purified CD19+IgD+IgGAire-GFP LN B cells from Adig mice (CD45.2) before intrathymic injection into CD45.1 recipient mice. (C) Frequency of Aire-GFP+ donor cells in donor B cells (gated on CD45.2+CD19+ viable singlets) 7 days after intrathymic injection of 5 × 105 CD19+IgD+IgGAire-GFP LN B cells from young (5-week-old) or aged (12-month-old) Adig mice into young (5-week-old) or aged (12- to 17-month-old) CD45.1 recipient mice. Bars indicate mean ± SD. p values were calculated using unpaired two-tailed Student’s t test. (D) Frequency of Aire-GFP+ cells in 5-week-old or 12-month-old Adig spleen B cells cultured for 3 days with or without agonistic anti-CD40 antibody (10 μg/mL) (n = 3). Bars indicate mean ± SEM. p values were calculated using unpaired two-tailed Student’s t test.

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References

    1. Akashi K, Richie LI, Miyamoto T, Carr WH, Weissman IL. B lymphopoiesis in the thymus. J Immunol. 2000;164:5221–5226. - PubMed
    1. Akiyama T, Shimo Y, Yanai H, Qin J, Ohshima D, Maruyama Y, Asaumi Y, Kitazawa J, Takayanagi H, Penninger JM, et al. The tumor necrosis factor family receptors RANK and CD40 cooperatively establish the thymic medullary microenvironment and self-tolerance. Immunity. 2008;29:423–437. - PubMed
    1. Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11:R106. - PMC - PubMed
    1. Anders S, Pyl PT, Huber W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–169. - PMC - PubMed
    1. Anderson MS, Venanzi ES, Klein L, Chen Z, Berzins SP, Turley SJ, von Boehmer H, Bronson R, Dierich A, Benoist C, Mathis D. Projection of an immunological self shadow within the thymus by the aire protein. Science. 2002;298:1395–1401. - PubMed

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