Premature ageing of the immune system underlies immunodeficiency in ataxia telangiectasia

Clinical Immunology (2011) 140, 26–36

available at www.sciencedirect.com

Clinical Immunology www.elsevier.com/locate/yclim

Premature ageing of the immune system underlies immunodeficiency in ataxia telangiectasia☆ Andrew Robert Exley a,b,⁎, Samantha Buckenham a , Elizabeth Hodges c , Robert Hallam a , Phil Byrd d , James Last d , Claire Trinder a , Susan Harris c , Nicholas Screaton e , Anthony P. Williams f , A. Malcolm R. Taylor d , John M. Shneerson g a

Immunology Laboratory, Department of Pathology, Papworth Hospital NHS Foundation Trust, Cambridge University Health Partners, Cambridge CB23 3RE, UK b Respiratory Infection, Inflammation and Immunology Unit, Thoracic Department, Papworth Hospital NHS Foundation Trust, Cambridge University Health Partners, Cambridge CB23 3RE, UK c Molecular Pathology, Southampton University Hospitals NHS Trust, Southampton SO16 6YD, UK d School of Cancer Sciences, University of Birmingham, Birmingham, B15 2TT, UK e Department of Radiology, Papworth Hospital NHS Foundation Trust, Cambridge University Health Partners, Cambridge CB23 3RE, UK f CR-UK Institute for Cancer Studies, University of Southampton, Southampton SO16 6YD, UK g Respiratory Support and Sleep Centre, Thoracic Department, Papworth Hospital NHS Foundation Trust, Cambridge University Health Partners, Cambridge CB23 3RE, UK Received 1 October 2010; accepted with revision 3 March 2011 Available online 13 March 2011 KEYWORDS ATM kinase; Ataxia telangiectasia; Immune ageing;

Abstract ATM kinase modulates pathways implicated in premature ageing and ATM genotype predicts survival, yet immunodeficiency in ataxia telangiectasia is regarded as mild and unrelated to age. We address this paradox in a molecularly characterised sequential adult cohort with classical and mild variant ataxia telangiectasia. Immunodeficiency has the characteristics of

Abbreviations: ATM, ataxia telangiectasia mutated gene product; A-T, ataxia telangiectasia; BCR B, cell receptor; CHK2, cell cycle checkpoint kinase 2; CREB, cAMP response element-binding protein; IGF1, insulin-like growth factor 1; KAP-1, KRAB associated protein; NBS1, Nimegen breakage syndrome protein 1; SMC1, structural maintenance of chromosomes protein 1; TCR, T cell receptor; TRECs, T cell receptor excision circles; Naïve B cells, CD19+ CD27− IgD+; Memory B cells, CD19+ CD27+; IgM memory B cells, CD19+ CD27+ IgD+; Class switched memory B cells, CD19+ CD27+ IgD−; Classic naïve CD4+ T cells, CD3+ CD4+ CD45RA+; % Thymic naive CD4+ T cells, %CD31+ in CD4+ CD27+ CD28+ CD45RA+; Thymic naive CD4+ T cell counts, CD4+ CD27+ CD28+ CD31+ CD45RA+ lymphocytes; Central naive CD4+ T cells, CD4+ CD27+ CD28+ CD31− CD45RA+ lymphocytes; Naive CD8+ T cells, CD3+ CD8+ CD27+ CD28+ CD45RA+ ☆ This work is supported in part by Papworth Hospital NHS Foundation Trust, a member of the Cambridge University Health Partners; Southampton University Hospitals; and the Ataxia Telangiectasia Society. A.M.R.T., P.J.B. and J.I.L. thank the CR-UK for continued support. ⁎ Corresponding author at: Immunology Laboratory, Department of Pathology, Papworth Hospital NHS Foundation Trust, Cambridge CB23 3RE, UK. Fax: +44 1480 364777. E-mail addresses: [email protected], [email protected] (A.R. Exley), [email protected] (S. Buckenham), [email protected] (E. Hodges), [email protected] (R. Hallam), [email protected] (P. Byrd), [email protected] (J. Last), [email protected] (C. Trinder), [email protected] (S. Harris), [email protected] (N. Screaton), [email protected] (A.P. Williams), [email protected] (A.M.R. Taylor), [email protected] (J.M. Shneerson). 1521-6616/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.clim.2011.03.007

Ageing underlies immunodeficiency in ataxia telangiectasia Naive T cells; T cell receptor; Pneumococcal antibodies

27

premature ageing across multiple cellular and molecular immune parameters. This immune ageing occurs without previous CMV infection. Age predicts immunodeficiency in genetically homogeneous ataxia telangiectasia, and in comparison with controls, calendar age is exceeded by immunological age defined by thymic naïve CD4+ T cell levels. Applying ataxia telangiectasia as a model of immune ageing, pneumococcal vaccine responses, characteristically deficient in physiological ageing, are predicted by thymic naïve CD4+ T cell levels. These data suggest inherited defects of DNA repair may provide valuable insight into physiological ageing. Thymic naïve CD4+ T cells may provide a biomarker for vaccine responsiveness in elderly cohorts. © 2011 Elsevier Inc. All rights reserved.

1. Introduction Pathways implicated in premature ageing, including cell cycle control, oxidative stress and insulin-like growth factor 1 (IGF1) signaling [1–3], are each modulated by the ataxia telangiectasia mutated gene product, ATM kinase [4]. ATM, a serine/threonine kinase, phosphorylates substrates integral to controlling cell responses to DNA damage including DNA repair factors, cell cycle and apoptosis regulators [4]. Biallelic ATM mutation is associated with premature death in ataxia telangiectasia, A-T [5], with a median life expectancy of 25 years reflecting increased susceptibility to leukaemias, lymphomas, pneumonia, chronic lung disease, and neurological decline [6]. Oxidative damage in A-T promotes accelerated telomere shortening [7], implicated in the induction of cellular senescence by ATM substrates [8]. These data supporting premature ageing in ATM deficiency contrast with reports of mild immunodeficiency unrelated to age in a large retrospective study of A-T [9]. A-T is characterised by progressive ataxia, ocular telangiectasia, pulmonary infections, immunodeficiency and increased sensitivity to ionizing radiation [10]. Clinical features show considerable heterogeneity [11] which is likely to reflect the impact of ATM genotype, modifier genes, and environmental factors [7]. ATM genotype and absence of ATM kinase activity correlates with lifespan [5], infection risk, lymphopenia, IgG subclass and IgA deficiencies [12]. ATM appears dispensable for somatic hypermutation but required for efficient Ig class switching [13,14]. However, regulation of B and T cell receptor, BCR, TCR, gene rearrangements is complex [15]. ATM is implicated in both modulation of the cell cycle [16] and non-homologous end joining of coding ends to signal ends during VDJ recombination [17]. Mechanisms underlying poor IgG antipneumococcal antibody responses are unclear [18]. Limited thymic output [19,20] and TCR/BCR repertoires are reported in A-T [19]. In contrast, ATM deficient mice generate normal primary TCR repertoires [21] despite defective thymic output at the TCRalpha stage [21,22]. We therefore sought a unifying principle to explain the immunodeficiency in A-T given the fundamental links between pathways implicated in premature ageing, ATM kinase activity, and ATM genotype. We first test the hypothesis that premature ageing underlies immunodeficiency in A-T by investigating immunological parameters which change with age including B, NK, CD4+ and CD8+ T cells; naïve B and T cells; differentiated T cells; and TCR repertoire diversity [23–28]. We examine the role of the environment,

focusing on chronic CMV infection as the environmental factor most strongly associated with immune ageing [24,29,30]. We investigate a genetically homogeneous subgroup with an age range of 3 decades to determine whether age predicts naïve T cell deficiency and oligoclonal expansions in A-T. Immunological age defined by naïve T cell levels is compared with calendar age in this homogeneous subgroup and age matched controls, as a direct test for premature immune ageing in A-T. Finally, we apply A-T as a model of immune ageing and vaccine responses as functional indices of immunity, to examine the determinants of antipneumococcal antibody responses which are characteristically deficient in physiological ageing and in A-T.

2. Materials and methods 2.1. Patients and controls We characterise according to ATM genotype, protein expression and kinase activity, a sequential adult cohort referred for elective investigation. Two cases with A-T like disorder were excluded leaving group 1, classical A-T with no ATM kinase activity, four males, eight females, age 24.5 ± 1.6 years; and group 2, variant A-T with limited ATM kinase activity, six males, six females, age 38.7 ± 2.9 years (see Table 1). Healthy controls, 7 males, 10 females, age 38.3 ± 2.2 years, versus classical A-T p b 0.001, versus variant A-T p = 0.92. The study was approved by Papworth Hospital NHS Foundation Trust Research Governance reference number S01345.

2.2. ATM genotyping, protein expression, and kinase activity ATM genotyping was determined by sequencing coding regions, exon–intron boundaries, and known pathogenic intronic sequence variations, then aligning to reference sequences (NM_000051.3), (NG_009830.1) [31]. ATM kinase activity was measured in a lymphoblastoid cell line from each patient, by the ability of cellular ATM to phosphorylate its downstream protein targets, Smc1, KAP1, Nbs1 and CREB at Smc1Ser966, KAP1Ser824, Nbs1Ser343 and CREB Ser121, respectively, using phosphospecific antibodies for each of these, following exposure of cells to 5 Gy gamma rays to activate the ATM kinase. In addition autophosphorylation at ATM Ser1981 was also measured using a phosphospecific antibody. Classical A-T patients are those whose cells have

28

A.R. Exley et al.

Table 1

ATM genotype, protein expression and ATM kinase activity.

Group 1. Classical A-T—no ATM kinase activity Case no.

Sex

D.o.B.

Mutation 1

Mutation 2

ATM protein

AT AT AT AT AT AT AT AT AT AT AT AT

M F F F M F F M F F F M

09/02/85 04/10/79 18/11/81 01/04/84 05/07/88 13/06/80 05/09/73 24/05/87 28/06/90 03/09/89 08/09/75 02/05/85

IVS16 – 2ANT 2639del200 IVS62+1GNA c.2413CNT(CGANTGA) p.Arg805X homozygous 6405insTT homozygous 497del166 634-40delT 103CNT (R35X) homozygous 6997_6998insA 7159_7160ins4 (AGCC) homozygous 7886_7890del5(TATTA) 8098ANT (KNstop)

5363delG 8206delAA 7630del159 0 0 7636del9 (2546delSRI) 2TNC 0 5712_5713insA 0 3802_3802delG 8506ANG (M2836V)

0 0 +++

0 +

2.1 ATM kinase activity present from Normal ATM protein AT P003 F 11/04/85 IVS40 –1050ANG) AT P005 F 20/11/60 IVS40 –1050ANG) AT P006 M 15/06/56 IVS40 –1050ANG) AT P009 F 01/05/61 IVS40 –1050ANG) AT P010 M 25/07/66 IVS40 –1050ANG) AT P018 F 15/11/79 IVS40 –1050ANG) AT P020 M 13/08/77 IVS40 –1050ANG) AT P024 M 13/08/69 IVS40 –1050ANG)

6198+1GNA (del exon 44) 9139CNT (R3047X) 2284delCT 2TNC IVS62+1GNA 9022CNT (R3008C) IVS44-6 del6/exon 45 del29 9022CNT (R3008C)

+ + + ++ + +++ + +++

2.2 ATM kinase activity present from probably normal ATM protein AT P004 F 28.1.85 IVS18+5TNA AT P022 M 4.7.61 IVS25-12TNA AT P023 M 21.9.59 IVS25-12TNA

Not identified Not identified Not identified

+ + +

2.3 ATM kinase activity present from mutant ATM protein AT P014 F 18,5,68 7271TNG (V2424G)

8266ANT (K2756X)

P001 P002 P007 P008 P011 P012 P013 P015 P019 P021 P025 P026

+ + 0

Group 2. Variant A-T—some ATM kinase activity

AT P001 to P026 indicate consecutive referrals grouped by ATM kinase activity. ATM mutations generating protein are shown in bold, with levels indicated as trace (+), half normal level (++) and normal level (+++). Mutations c.7630del159, c.7636del9 (p.2546delSRI), c.2TNC, c.8506ANG;(p.Met2436Val), c.9022CNT;(p.Arg3008Cys) generated ATM protein without any activity. Mutations IVS40-1050ANG, IVS25-12TNA, and IVS18+5TNA are splice site mutations generating some normal ATM (with some activity). The c.7271TNG (p.V2424G) missense mutation generated a near normal level of mutant ATM with residual kinase activity.

no ATM kinase activity, either as a result of absence of ATM (the consequence of two truncating ATM mutations) or who have some ATM protein expressed but without activity. This can only be determined by measuring ATM kinase activity as shown in Supplementary Fig. S1). Both ATM mutations were identified for 21/24 patients and one mutation for the remaining three. ATM kinase activity was determined for all patients. Table 1 shows two major groups of A-T patients: group 1 whose cells showed no ATM kinase activity (including some patients who expressed some ATM) and group 2 patients whose cells showed some ATM kinase activity. In group 2.1, eight cases carried the leaky splice site mutation IVS40-1050ANG generating low levels of normal and active ATM protein, associated with neurologically milder A-T [31,32]. There was, therefore, homogeneity in terms of the level of ATM kinase activity in cells from each of these patients. Group 2.2 patients were cases whose ATM kinase activity probably derived from other leaky splice site mutations and group 2.3 consisted of a single

patient with ATM kinase activity derived from the V2424G missense mutation.

2.3. Flow cytometry Five color analyses of fresh EDTA blood after red cell lysis by Versalyse with fixative utilised optimized FITC, PE, ECD, PC5, PC7 labeled combinations of antibodies. We used CD3 (UCHT1), CD4 (4D11), CD8 (2D3), CD19 (J3.119), CD25 (B1.49.9), CD27 (1A4), CD28 (CD28.2), CD31 (5.6E), CD45 (J.33), CD45RA (2H4), CD56 (N901), CD127 (R34.34), all Beckman Coulter, CD27 (Dako), IgD (Southern Biotechnology), CD38, CD21 (BD Biosciences), IgM (Jackson Laboratories), Papworth Hospital Immunology Laboratory, CPA reference 2383. Data were acquired using Cytomics FC500 flow cytometers running 488 nm Argon blue lasers with filters set for FITC 525, PE 575, ECD 620, PC5 675, PC7 775 nm after

Ageing underlies immunodeficiency in ataxia telangiectasia Table 2

29

Differential blood counts and lymphocyte subsets in A-T. Controls, n = 17 Mean ± SEM

Leucocytes Neutrophils Lymphocytes Monocytes Red cells Platelets CD19+ B cells CD3+ T cells CD3+ 4+ T cells CD3+ 8+ T cells CD3− 56+ NK cells % CD3− 56+ % CD3− 56bright % 4+ 25+ 127− 45RA− % 8+ 25− 127− 45RA− % 4+ 27+ 28+ 45RA− % 4+ 27− 28+ % 8+ 27+ 28+ 45RA− %Memory B cells %IgM memory %Class switched

6871 ± 302 3906 ± 264 2232 ± 102 513 ± 37 4721 ± 264 274 ± 12 331 + 32 1593 ± 83 1052 ± 61 470 ± 42 266 ± 28 12.0 ± 1.2 7.3 ± 1.1 5.4 ± 0.3 11.9 ± 1.5 55.3 ± 2.1 5.3 ± 0.5 35.5 ± 2.7 25.6 ± 3.7 12.7 ± 2.3 12.8 ± 1.9

Classical AT (1), n = 12

Variant AT (2), n = 12

Control vs. 1

Control vs. 2

1 vs. 2

7250 ± 648 5225 ± 680 1170 ± 180 542 ± 62 4878 ± 109 371 ± 41 77 + 14 709 ± 103 439 ± 60 236 ± 51 286 ± 56 25.7 ± 4.2 12.3 ± 2.3 8.6 ± 0.8 24.4 ± 3.2 75.6 ± 3.1 11.2 ± 1.4 52.9 ± 3.6 37.0 ± 3.4 19.9 ± 3.9 17.0 ± 4.4

6842 ± 580 3745 ± 255 2030 ± 159 445 ± 34 5053 ± 172 288 ± 28 166 ± 27 1542 ± 147 1108 ± 91 400 ± 72 278 ± 45 14.5 ± 2.6 9.9 ± 1.6 5.0 ± 0.7 12.3 ± 2.6 45.5 ± 3.7 4.9 ± 0.5 33.6 ± 3.9 44.0 ± 4.2 23.5 ± 4.4 16.9 ± 2.7

0.60 0.09 b 0.001 0.57 0.34 0.03 b 0.001 b 0.001 b 0.001 0.002 0.74 0.008 0.07 0.002 0.003 b 0.001 0.002 b 0.001 0.03 0.13 0.39

0.97 0.61 0.30 0.32 0.14 0.66 b 0.001 0.76 0.62 0.41 0.83 0.41 0.20 0.65 0.89 0.03 0.53 0.70 0.003 0.04 0.24

0.64 0.05 0.002 0.19 0.41 0.10 0.009 b 0.001 b 0.001 0.08 0.90 0.04 0.40 0.003 0.01 b 0.001 b 0.001 0.001 0.20 0.55 0.97

Mean values with standard errors are shown for healthy adult controls, classical (1) and mild variant (2) A-T cases with comparisons between groups by t-test, two-tailed. Cell counts are ×106/L except red cells and platelets which are ×109/L. 4+ 25+ 127− 45RA− and 8+ 25− 127− 45RA− are CD4+ and CD8+ T cell subsets indicative of peripheral expansion. CD4+ 27+ 28+ 45RA−, CD8+ 27+ 28+ 45RA−, and CD4+ 27− 28+, denote early and intermediate stage T cells. B cell subsets total memory, IgM memory, and class switched memory B cells are defined as CD19+ CD27+, CD19+ CD27+ IgD+, and CD19+ CD27+ IgD− B cells, respectively.

Advanced Digital Compensation with Cyto Comp cells, Quick Comp CD45 FITC, PE, ECD, PC5 antibody kit and CD45 PC7 using CXP version 2.2 (Beckman Coulter). Individual subsets were defined from viable lymphocytes gated using CD45/side scatter (ss), CD3/ss, CD4/ss, and forward scatter/ss. Five thousand events were collected for each major analyte, save 10,000 CD3 events for TCRVbeta expression [33]. Absolute counts were calculated comparing CD45/ss pan-leucogating [34] and white cell counts (LH500, Beckman Coulter). Sequential gating defined subsets of NK cells [35], B cells [36], naïve T cells [27,28], CD25/127/45RA [37], and CD27/ 28/45RA characterised T cells [38].

2.4. Serotype specific anti-pneumococcal antibody levels Serotype specific IgG anti-pneumococcal antibody levels were determined in a 10-plex assay using carboxylated 690 nm fluorescent 4.4–5.5 μm microspheres (Bangs Laboratories) optimally coated with pneumococcal capsular polysaccharide, serotypes 1, 4, 5, 6B, 7F, 9V, 14, 18C, 19F, 23F, (LGC Promochem) [39], analysed on the FC500 (Beckman Coulter). Serum samples adsorbed with pneumococcal cell wall and serotype 22F polysaccharide were compared with 89-SF standard dilutions [40]. The assay has two to three log10 linear dynamic range; high specificity and reproducibility; median homologous/heterologous inhibition 95.7% (range 92.1– 98.6%), 12.3% (9.3–14.6%); intra- and inter-assay coefficients

of variation b 6%, 13%; limits of detection 0.19 (0.03–2.35) ng/ml versus diluent, 1.88 (0.31–4.08) ng/ml versus preabsorbed serum; median correlation with Luminex based assays 0.87 (0.73–0.92) for 10 serotypes [39]. Cases were primed with conjugate vaccine, Prevnar-7, challenged with polysaccharide vaccine, Pneumovax, then sera drawn 4–6 weeks later, applying the threshold of ≥1.3 mcg/ml [41].

2.5. T cell receptor repertoires TCRVbeta expression was determined using the Beta Mark Kit, CD3 (UCHT1), CD4 (4D11), CD8 (2D3), then expressed as TCRVbeta diversity scores calculated as (24 − (TCRVbeta families expressed ≤ 10% of normal ranges) − (TCRVbeta families expressed N100% of normal ranges, Beckman Coulter)) for CD4+ and CD8+ T cells. Laboratory control values were determined for five healthy controls. TCRVbeta CDR3 spectratypes were determined using standard methods applied to≥106 cells per fraction and analysed for complexity as the sum of amplified peaks per Vbeta family [42]. The 95% confidence interval for the lower limit of normal for CD4+ and CD8+ T cells was 154 and 132, coefficients of variation b 10%, n = 10.

2.6. Statistical analysis Statistical analysis utilised Minitab®, Minitab U.K. applying Student's unpaired t-test for comparisons between controls,

30

A.R. Exley et al.

Figure 1 Deficiency of naïve cells varies with ATM kinase activity. Percentage of (a) naïve B CD19+ CD27− IgD+ and (b) classic naïve CD4 + 45RA+, (c) thymic naïve CD4+ T cells, %CD31+ in CD4/27/28/45RA+, and (d) naïve CD8+, CD3/8/27/28/45RA+ T cells where open circles are healthy controls; filled, classical A-T; light shaded, variant A-T. Horizontal bars are medians, cases versus controls, #p b 0.05, or means, t-test versus controls *p b 0.05, **p b 0.01, ***pb 0.001, classical versus variant A-T +p b 0.05, ++p b 0.01, +++p b 0.001.

classical A-T, and variant A-T, mean, SEM; and Mann– Whitney U test for non-parametric data, medians quoted. A p b 0.05 was regarded as statistically significant. Pearson correlation coefficients tested correlation between parameters. We used the least squares method with a single predictor for simple linear regression. Regression lines of age versus % thymic naïve T cells were parallel for controls and group 2.1, genetically homogeneous A-T. Immunological age defined by thymic naïve CD4+ T cell levels is then compared with calendar age by generating a single regression line and determining residual values using pooled data from the homogeneous A-T subgroup and age matched controls.

3. Results 3.1. The pattern of immunodeficiency in classical A-T is typical of ageing Differential blood counts are maintained in classical A-T except for a mild lymphopenia affecting B cells, CD4+ and CD8+ T cells with relative expansion of NK cells (see Table 2), a characteristic pattern of ageing [23]. There is no clinical or radiological evidence of expansion of secondary lymphoid tissues, indicating changes in peripheral blood counts represent a real contraction of the immune system not compartment effects. There is a relative deficiency of naïve CD19+ IgD+ B cells, and classical naive CD4+ CD45RA+, thymic naïve CD4+

CD31/45RA+, and naïve CD8+ CD27/28/45RA+ T cells (Fig. 1). Mean naïve cell counts are reduced, for naïve B cells to 20 ±4%, thymic naïve CD4+ 7.5% ± 3.7%, central naïve CD4+ 15% ±4%, total naïve CD4+ 11% ± 4%, and naïve CD8+ T cells to 18% ± 6% of control values, pb 0.001. There is no deficit of CD56bright NK cell levels, a putative subset of young NK cells [35] (Table 2). Thus immunodeficiency in A-T particularly affects naïve B and T cells, a typical feature of ageing [23]. Applying naïve T cell counts as indices of immunological age [23,24] then naïve cell levels are lower in classical A-T than controls, thymic naïve CD4+ T cells 19 ± 9 versus 255 ± 30 × 106/L, central naïve CD4+ T cells 25 ± 6 versus 170 ± 29 × 106/L, naïve CD8+ T cells 32 ± 10 versus 182 ± 29 × 106/L, p b 0.001 for each. Yet mean ages are 24.5 ± 1.6 years in classical A-T versus 38.3 ± 2.2 years in controls p b 0.001. Thus immunological age greatly exceeds calendar age in classical A-T consistent with premature ageing of the immune system. There is also a relative deficit of thymic naive CD4+ T cells in variant A-T versus age matched controls (Fig. 1), suggesting gradation of premature ageing with ATM kinase activity.

3.2. Deficiency of naïve T cells predicts peripheral expansion and a restricted oligoclonal T cell repertoire The reduction in naïve CD4+ T cells and CD19+ B cell levels in both classical and variant A-T, (Fig. 1) suggests a common

Ageing underlies immunodeficiency in ataxia telangiectasia

31

Figure 2 Naïve T cell deficiency predicts peripheral expansion and restricted, oligoclonal TCR repertoires. Linear regression showing naïve T cell levels as single predictors of (a–c) restricted TCR repertoires and (d) expansion of CD8 + 25/127/45RA− T cells; A-T cohort shown as heavy shaded circles except (b), CMV seropositives are filled circles. (a) Thymic naïve CD4/27/28/31/45RA + T cells. (b) Naïve CD8/27/28/45RA+ T cells. (a and b) Expression of TCRVbeta families by flow cytometry, diversity scores are ((24 − (families expressed ≤ 10% or N 100% normal values)); TCRVbeta CDR3 spectratype complexity scored as the sum of amplified peaks per Vbeta family.

mechanism operating across a range of ATM kinase activity. Relative and absolute thymic naïve CD4 + T cell levels predict naïve CD8+ T cell levels across the A-T cohort, r2 = 0.67 p b 0.001 and r2 = 0.58 p b 0.001 n = 24, respectively. CD4+ TCRVbeta diversity scores are higher in controls at 22 ± 2 n = 5, versus 16 ± 2 p b 0.001 in classical A-T, and 20 ± 2 in variant A-T, not significant. CD8+ TCRVbeta diversity scores are higher in controls at 20 ± 2 n = 5 versus 12 ± 2 p b 0.001 in classical A-T, and 16 ± 2 p b 0.05 in variant A-T. Deficiency of thymic naïve CD4+ T cells and naïve CD8+ T cells predicts reduction in diversity of the CD4+ and CD8+ TCRVbeta repertoires across the A-T cohort (Fig. 2a and b). These findings were confirmed using molecular typing by showing TCRVbeta CDR3 spectratype complexity scores are lower in classical A-T than variant A-T for CD4+ T cells, 150 ± 5 versus 166 ± 3 p b 0.01, and CD8+ T cells 112 ± 8 versus 140 ± 5 p b 0.01, respectively. Low thymic naïve CD4+ T cell counts predict low TCRVbeta CDR3 complexity scores, r2 = 0.387 p = 0.001, and similarly low naïve CD8+ T cell counts predict low TCRVbeta CDR3 complexity scores (Fig. 2c) across the cohort. Naïve CD8+ T cell levels are better predictors of their TCRVbeta diversity and CDR3 spectratype complexity scores than thymic naïve CD4+ T cells are as predictors of CD4+ TCR repertoires. Total naïve CD4+ T cell counts may be better predictors of TCR repertoires than thymic naïve CD4+ T cells, r2 = 0.486 p b 0.001 for TCRVbeta diversity and r2 = 0.418 p = 0.001 for CDR3 spectratype complexity scores.

One potential mechanism for generating restricted T cell receptor repertoires is linkage between deficiency of naïve cells and peripheral expansion, post-thymic differentiation and oligoclonal proliferation of T cells. Indices of peripheral T cell expansion include CD4+ CD25bright CD127/CD45RA− [43] and CD8+ CD25/127/45RA− T cells [37]; both are increased in classical A-T (Table 2). Deficiency of naïve CD8+ T cells predicts peripheral expansion as shown by the increase in CD8+ CD25/ 127/45RA− T cells across the A-T cohort (Fig. 2d). Expansion of TCRVbeta families predicts the reduction in CD8+ TCRVbeta diversity scores, r2 = 0.53, slope =2.12, pb 0.001. Differential expression of CD27 and CD28 provides indices of post-thymic differentiation. Late stage CD27− CD28− T cells are increased across the A-T cohort, 0.5% ± 0.1% of CD4+ T cells in controls versus 2.2% ±0.8% in A-T p b 0.05, and 9.2% ± 2.1% of CD8+ T cells versus 16.4 ±3.2% pb 0.05, respectively, consistent with evidence linking increased CD28− T cells and oligoclonal T cell receptor repertoires [28]. Intermediate CD4+ CD27− CD28+, early CD4+ CD27+ CD28+ CD45RA− and early CD8+ CD27+ CD28+ CD45RA− T cells are also increased in classical A-T (Table 2). Previous infection with CMV as determined by detection of IgG antibodies is the environmental factor most strongly associated with immune ageing [29]. We therefore determined whether immune ageing in A-T was restricted to cases seropositive for IgG antibodies to CMV. We find naïve T cell deficiency, peripheral expansion, and restricted, oligoclonal TCR repertoires in A-T occur largely in the absence of

32 Table 3

A.R. Exley et al. Serum immunoglobulins, IgG anti-pneumococcal Ab responses, and CMV serology. IgE

IgG2

IgA

IgG

IgG3

IgM

Pneumo

CMV

10–120 kU/L

1.2–2.4 g/L

0.8–1.8 g/L

6.0–10.4 g/L

0.2–0.8 g/L

0.4–1.4 g/L

N6

IgG

b2 5 b2 2 2 b2 b2 2 b2 b2 b2 b2

0.52 0.86 0.23 2.16 0.11 0.37 0.14 1.87 3.23 0.05 0.48 0.14

2.00 2.40 3.30 0.30 0.10 0.60 0.10 0.40 1.20 0.10 1.80 0.50

9.5 7.9 12.6 11.1 8.1 6.1 9 11.2 11.8 4.7 5.6 8.6

0.24 0.43 0.55 0.45 0.24 0.25 1.60 0.37 0.76 0.04 0.08 0.47

1.7 1.4 1.6 2.2 1.0 4.8 1.1 3.6 1.9 0.7 0.5 1.1

0 6 1 0 2 1 1 n/a n/a 0 n/a 0

Neg Neg Pos Pos Neg Neg Neg n/a n/a Neg Neg Neg

Group 2.1 AT P003 AT P005 AT P006 AT P009 AT P010 AT P018 AT P020 AT P024

15 79 b2 96 40 52 4 9

1.60 5.23 3.95 2.00 4.34 n/a 3.39 2.08

1.10 3.90 1.10 3.50 2.10 3.00 2.00 3.00

7.1 14.3 8.2 11.6 12.7 9.8 13.2 12.1

0.50 0.54 0.23 0.30 0.40 n/a 0.91 0.26

1.1 3.3 0.5 2.2 1.3 2.8 2.5 2.8

10 4 5 4 2 5 8 n/a

Neg Neg Pos Pos Neg Pos Neg Neg

Group 2.2 AT P004 AT P022 AT P023

21 12 100

2.58 1.94 1.82

1.50 1.80 1.60

9.6 9.8 14.4

0.44 0.36 0.45

1.8 1.0 0.9

8 5 9

Pos Neg Neg

Group 2.3 AT P014

13

2.76

2.50

7.7

0.25

2.7

7

Neg

Normal range Cases Group 1 AT P001 AT P002 AT P007 AT P008 AT P011 AT P012 AT P013 AT P015 AT P019 AT P021 AT P025 AT P026

SCIG SCIG

Case numbers, groups as in Table 1. SCIG are cases receiving subcutaneous immunoglobulin infusions. Serum immunoglobulins are shown with normal ranges (Dade Behring BN2-nephelometer). Pneumo, serotypes with IgG anti-pneumococcal antibodies ≥1.3 mcg/ml after priming with protein-polysaccharide vaccine, Prevnar-7, and boosting with 23 valent polysaccharide vaccine, Pneumovax. CMV IgG is positive or negative by ELISA. n/a not available including two on SCIG where CMV status is unknown.

previous CMV infection (Table 3). There is some evidence of accelerated immune ageing since all CMV seropositives have lower TCRVbeta diversity scores than is predicted by naïve CD8+ T cell levels (Fig. 2b, filled circles).

naïve CD4+ T cell levels to define immunological age [23,24], (see Statistical Analysis), we find that immunological age exceeds calendar age by 13.0 years (95% C.I. 4.6–21.4 years) p = 0.004 in the homogeneous group with mild variant A-T.

3.3. Age predicts naïve T cell deficiency and oligoclonal expansions in genetically homogeneous variant A-T

3.4. A-T as a potential model for physiological immune ageing

The genetically homogeneous subgroup of mild variant A-T spanning 3 decades (group 2.1 Table 1) provides an opportunity to directly examine the impact of age on immunodeficiency in A-T. Age is a powerful predictor of naïve CD4+ and CD8+ T cell deficiency (Fig. 3a and b). Age also predicts expansion of CD8+ CD27− CD28− T cells (Fig. 3c), and an increase in peaked or skewed families within the CD8+ TCRVbeta CDR3 spectratype (Fig. 3d) consistent with oligoclonal expansions. In genetically diverse healthy controls also, age predicts naive T cell levels, r2 = 0.471 p =0.005 for naïve CD8+ T cell counts. Applying thymic

We then test the hypothesis that since premature immune ageing underlies immunodeficiency in A-T, studies of immune responses in A-T may offer insights into physiological ageing. Pneumococcal polysaccharide vaccine does not protect the elderly from pneumococcal pneumonia [44] possibly because prevention of naso-pharyngeal colonisation by pneumococci requires high antibody levels [45] achievable with conjugate vaccines [46] when T cell help is not limited by immune ageing [23]. We therefore tested IgG anti-pneumococcal antibody responses in A-T after priming with conjugate, Prevnar [18], and boosting with pneumococcal polysaccharide, Pneumovax,

Ageing underlies immunodeficiency in ataxia telangiectasia

33

Figure 3 Age predicts deficiency of naïve T cells, peripheral expansion and oligoclonal TCR repertoires in genetically homogeneous A-T. Linear regression showing age as a single predictor of naïve T cells (a and b), peripheral T cell expansion (c), and oligoclonal TCR repertoires (d); with classical A-T, filled circles; variant A-T, shaded circles; homogeneous cohort, crossed circles. (a) Thymic naïve CD4+ T cells as % CD31+ in CD4/45RA+. (b) Naïve CD8/27/28/45RA+ T cells. (c) %CD8+ 27− 28− T cells. (d) TCRVbeta CDR3 scored as the sum of Vbeta families with peaked or skewed spectratypes.

vaccines. The number of serotypes with antibody levels above threshold varies with ATM kinase activity, in classical A-T the median response is 1 of 10 serotypes (interquartile range 0–1) versus 6 (4.3–8.0) in variant A-T p b 0.001 (Table 3). Class switching appears impaired in classical A-T as shown by low serum IgE, IgG2, and IgA levels (Table 3), although CD27+ memory B cells are increased and class switched memory B cell levels are maintained across the A-T cohort (Table 2). No B cell parameter predicts IgG anti-pneumococcal antibody responses, consistent with redundancy within memory B cell subsets [47]. In contrast, thymic naïve CD4+ T cell counts are strong predictors of the number of serotypes with IgG antipneumococcal antibody levels above threshold, r2 = 0.728 p b 0.001, linking immunological ageing with deficient antibody responses. Different measures of naïve CD4+ T cells do not improve the prediction of pneumococcal antibody responses, r2 = 0.679 p b 0.001 and r2 = 0.436 p = 0.002 for total and central naïve CD4+ T cell counts, respectively.

4. Discussion This study provides clinical confirmation of experimental data linking ATM kinase deficiency with premature ageing [1–4,8]. In contrast to simpler retrospective studies [9], investigation of a molecularly characterised cohort reveals evidence of premature immune ageing in A-T affecting multiple cellular

and molecular analytes [23,25,28,30]. A key defect in the immune ageing is the deficiency of naïve T cells, consistent with reduced thymic output in ATM deficiency [19–22]. The deficiency of naïve T cells with oligoclonal expansions and deficient TCR repertoires in A-T is similar to the effects of early thymectomy [24], but occurs in the absence of CMV infection which is known to accentuate immune ageing [24,30]. ATM deficiency alone is insufficient to generate deficient TCR repertoires [21] implying a role for other environmental factors as drivers of progressive deficiency, such as oxidative stress [2], infection and inflammation [48–50]. Naïve T cell counts are proportionally much lower than total CD4+ and CD8+ T cell counts due to the expansion of differentiated cells. Another feature of physiological immune ageing is a deficiency of naive B cells [25], a novel observation in A-T consistent with low B cell counts [12], a deficiency of pre-B cells [51] and excess unrepaired coding ends during BCR gene assembly in ATM deficiency [52]. Immunodeficiency in A-T affects B and T cells, not NK [35], myeloid nor erythroid cells, although our studies are confined to peripheral blood samples and lymphoblastoid cell lines. Therefore we cannot exclude a role for restricted self-renewal of haematopoietic stem cells due to oxidative stress [53], given the preferential decline in lymphoid rather than myeloid output from ageing haematopoietic stem cells [54]. Deficiency of naïve B and T cells may be due to a stem cell defect and/or a defect in the generation of pre-B and pre-T cells secondary to

34 limited TCR/BCR rearrangements in A-T [21,22,51,52]. We use an established, robust method for rapidly determining thymic naïve CD4+ T cell levels [27] which proves highly discriminating in A-T, circumventing problems in identifying recent thymic emigrants, rare in adults and preferentially incorporated into the naïve T cell pool [55]. This may result in an underestimate of immune ageing since surface phenotype may be maintained during post-thymic proliferation [26] which contributes twice as much to the naïve cell pool as thymic output [56]. Controls and mild variant A-T are well matched for age, but classic A-T cases are younger. This may also lead to an underestimate of immune ageing. Controversially [26,27], total naïve CD4+ T cell counts are better than thymic naïve CD4+ T cell counts as predictors of diverse TCR repertoires, suggesting central naïve CD4+ T cells support diversity of the TCR repertoire. The production of naïve T cells reflects both thymic production, defective in A-T [21,22], and homeostatic proliferation [55] which might be boosted by cytokine therapy. The characteristic features of immune ageing are seen in classical A-T and mild variant disease where age is a strong predictor of immune parameters. The reduction in naïve B cells and thymic naïve CD4+ T cell levels is less pronounced in mild disease, consistent with a protective effect of some ATM kinase activity. These data, taken together, suggest naïve B and T cell levels may be useful biomarkers of therapeutic responses in A-T and other conditions where naïve cell levels are limiting. The evidence of immune ageing in A-T suggests it may provide a model for physiological ageing. We focussed on pneumococcal antibody responses as a functional index of immunity which is impaired in ageing. No B cell phenotype predicts deficient anti-pneumococcal antibody responses, consistent with evidence of redundancy in SCID/Hu mice [47]. In contrast, deficiency of thymic naïve CD4+ T cells strongly predicts poor IgG anti-pneumococcal antibody responses in A-T. This novel observation is consistent with experimental data [57,58] prompting further evaluation of thymic naïve CD4+ T cell levels as a biomarker for vaccine responsiveness in seniors. In conclusion, the data herein suggest studies on clinical cohorts with molecular defects of DNA repair offer insight into physiological immune ageing secondary to accumulated DNA damage. This study provides further evidence that a combination of host factors, cellular repair mechanisms for DNA repair, thymic capacity, and environmental insults contribute to the naturally occurring age-related changes in immunity. The ageing population with increased susceptibility to infections necessitates a better understanding of immune ageing to inform future interventional health measures. Supplementary materials related to this article can be found online at doi:10.1016/j.clim.2011.03.007.

Conflict of interest None for any author.

Acknowledgments We thank Stephen Doherty and Southampton University School of Medicine for cell sorting facilities, FACS Aria (Becton Dickenson), and Venkat Srinivasan for help with ATM

A.R. Exley et al. gene sequencing and Cancer Research-UK and the Ataxia telangiectasia Society (UK) for continued support. We thank the patients' and their referring doctors for their support.

References [1] A. Matheu, A. Maraver, P. Klatt, I. Flores, I. Garcia-Cao, C. Borras, et al., Delayed ageing through damage protection by the Arf/p53 pathway, Nature 448 (7151) (2007) 375–379. [2] A. Alexander, S.L. Cai, J. Kim, A. Nanez, M. Sahin, K.H. MacLean, et al., ATM signals to TSC2 in the cytoplasm to regulate mTORC1 in response to ROS, Proc. Natl Acad. Sci. U.S.A. 107 (9) (2010) 4153–4158. [3] Y. Suh, G. Atzmon, M.O. Cho, D. Hwang, B. Liu, D.J. Leahy, et al., Functionally significant insulin-like growth factor I receptor mutations in centenarians, Proc. Natl Acad. Sci. U.S.A. 105 (9) (2008) 3438–3442. [4] S. Matsuoka, B.A. Ballif, A. Smogorzewska, E.R. McDonald III, K.E. Hurov, J. Luo, et al., ATM and ATR substrate analysis reveals extensive protein networks responsive to DNA damage, Science 316 (5828) (2007) 1160–1166. [5] A. Li, M. Swift, Mutations at the ataxia-telangiectasia locus and clinical phenotypes of A-T patients, Am. J. Med. Genet. 92 (3) (2000) 170–177. [6] T.O. Crawford, R.L. Skolasky, R. Fernandez, K.J. Rosquist, H.M. Lederman, Survival probability in ataxia telangiectasia, Arch. Dis. Child. 91 (7) (2006) 610–611. [7] A. Tchirkov, P.M. Lansdorp, Role of oxidative stress in telomere shortening in cultured fibroblasts from normal individuals and patients with ataxia-telangiectasia, Hum. Mol. Genet. 12 (3) (2003) 227–232. [8] Fd'Adda di Fagagna, P.M. Reaper, L. Clay-Farrace, H. Fiegler, P. Carr, T. von Zglinicki, et al., A DNA damage checkpoint response in telomere-initiated senescence, Nature 426 (6963) (2003) 194–198. [9] A. Nowak-Wegrzyn, T.O. Crawford, J.A. Winkelstein, K.A. Carson, H.M. Lederman, Immunodeficiency and infections in ataxia-telangiectasia, J. Pediatr. 144 (4) (2004) 505–511. [10] E. Boder, R.P. Sedgwick, Ataxia-telangiectasia; a familial syndrome of progressive cerebellar ataxia, oculocutaneous telangiectasia and frequent pulmonary infection, Pediatrics 21 (4) (1958) 526–554. [11] C.G. Woods, A.M.R. Taylor, Ataxia telangiectasia in the British Isles: the clinical and laboratory features of 70 affected individuals, QJM 82 (2) (1992) 169–179. [12] E.R. Staples, E.M. McDermott, A. Reiman, P.J. Byrd, S. Ritchie, A.M.R. Taylor, et al., Immunodeficiency in ataxia telangiectasia is correlated strongly with the presence of two null mutations in the ataxia telangiectasia mutated gene, Clin. Exp. Immunol. 153 (2) (2008) 214–220. [13] Q. Pan-Hammarstrom, S. Dai, Y. Zhao, I.F. Dijk-Hard, R.A. Gatti, A.L. Borresen-Dale, et al., ATM is not required in somatic hypermutation of VH, but is involved in the introduction of mutations in the switch mu region, J. Immunol. 170 (7) (2003) 3707–3716. [14] B. Reina-San-Martin, H.T. Chen, A. Nussenzweig, M.C. Nussenzweig, ATM is required for efficient recombination between immunoglobulin switch regions, J. Exp. Med. 200 (9) (2004) 1103–1110. [15] G.K. Mahowald, J.M. Baron, M.A. Mahowald, S. Kulkami, A.L. Bredemeyer, C.H. Bassing, et al., Aberrantly resolved RAGmediated DNA breaks in Atm-deficient lymphocytes target chromosomal breakpoints in cis, Proc. Natl Acad. Sci. U.S.A. 106 (43) (2009) 18339–18344. [16] M.E. Dujka, N. Puebla-Osorio, O. Tavana, M. Sang, C. Zhu, ATM and p53 are essential in the cell-cycle containment of DNA

Ageing underlies immunodeficiency in ataxia telangiectasia

35

breaks during V(D)J recombination in vivo, Oncogene 29 (7) (2009) 957–965. A.L. Bredemeyer, C.Y. Huang, L.M. Walker, C.H. Bassing, B.P. Sleckman, Aberrant V(D)J recombination in ataxia telangiectasia mutated-deficient lymphocytes is dependent on nonhomologous DNA end joining, J. Immunol. 181 (4) (2008) 2620–2625. A. Stray-Pedersen, I.S. Aaberge, A. Fruh, T.G. Abrahamsen, Pneumococcal conjugate vaccine followed by pneumococcal polysaccharide vaccine; immunogenicity in patients with ataxiatelangiectasia, Clin. Exp. Immunol. 140 (3) (2005) 507–516. A. Giovannetti, F. Mazzetta, E. Caprini, A. Aiuti, M. Marziali, M. Pierdominici, et al., Skewed T-cell receptor repertoire, decreased thymic output, and predominance of terminally differentiated T cells in ataxia telangiectasia, Blood 100 (12) (2002) 4082–4089. T. Morio, N. Takahashi, F. Watanabe, F. Honda, M. Sato, M. Takagi, et al., Phenotypic variations between affected siblings with ataxia-telangiectasia: ataxia-telangiectasia in Japan, Int. J. Hematol. 90 (4) (2009) 455–462. I.R. Matei, R.A. Gladdy, L.M.J. Nutter, A. Canty, C.J. Guidos, J.S. Danska, ATM deficiency disrupts TCRa locus integrity and the maturation of CD4+CD8+ thymocytes, Blood 109 (5) (2007) 1887–1896. M.S. Vacchio, A. Olaru, F. Livak, R.J. Hodes, ATM deficiency impairs thymocyte maturation because of defective resolution of T cell receptor alpha locus coding end breaks, Proc. Natl Acad. Sci. U.S.A. 104 (15) (2007) 6323–6328. P. Sansoni, R. Vescovini, F. Fagnoni, C. Biasini, F. Zanni, L. Zanlari, et al., The immune system in extreme longevity, Exp. Gerontol. 43 (2) (2008) 61–65. D. Sauce, M. Larsen, S. Fastenackels, A. Duperrier, M. Keller, B. Grubeck-Loebenstein, et al., Evidence of premature immune aging in patients thymectomized during early childhood, J. Clin. Invest. 119 (10) (2009) 3070–3078. D. Veneri, R. Ortolani, M. Franchini, G. Tridente, G. Pizzolo, A. Vela, Expression of CD27 and CD23 on peripheral blood B lymphocytes in humans of different ages, Blood Transfus. 7 (1) (2009) 29–34. R.D. Kilpatrick, T. Rickabaugh, L.E. Hultin, P. Hultin, M.A. Hausner, R. Detels, et al., Homeostasis of the naive CD4+ T cell compartment during aging, J. Immunol. 180 (3) (2008) 1499–1507. S. Kohler, A. Thiel, Life after the thymus: CD31+ and CD31− human naive CD4+ T-cell subsets, Blood 113 (4) (2009) 769–774. Np Weng, A.N. Akbar, J. Goronzy, CD28-T cells: their role in the age-associated decline of immune function, 7Trends in Immunology 30 (2009) 306–312. G. Pawelec, A. Akbar, P. Beverley, C. Caruso, E. Derhovanessian, T. Fulop, et al., Immunosenescence and cytomegalovirus: where do we stand after a decade? Immunity & Ageing 7 (1) (2010) 13. S. Chidrawar, N. Khan, W. Wei, A. McLarnon, N. Smith, L. Nayak, et al., Cytomegalovirus-seropositivity has a profound influence on the magnitude of major lymphoid subsets within healthy individuals, Clin. Exp. Immunol. 155 (3) (2009) 423–432. G. Barone, A. Groom, A. Reiman, V. Srinivasan, P.J. Byrd, A.M. Taylor, Modeling ATM mutant proteins from missense changes confirms retained kinase activity, Hum. Mutat. 30 (8) (2009) 1222–1230. C.M. McConville, T. Stankovic, P.J. Byrd, G.M. McGuire, Q.Y. Yao, G.G. Lennox, et al., Mutations associated with variant phenotypes in ataxia-telangiectasia, Am. J. Hum. Genet. 59 (2) (1996) 320–330. J.M. Faint, D. Pilling, A.N. Akbar, G.D. Kitas, P.A. Bacon, M. Salmon, Quantitative flow cytometry for the analysis of T cell receptor Vbeta chain expression, J Immunol Methods 225 (1–2) (1999) 53–60.

[34] D. Glencross, L.E. Scott, I.V. Jani, D. Barnett, G. Janossy, CD45-assisted PanLeucogating for accurate, cost-effective dual-platform CD4+ T-cell enumeration, Cytometry 50 (2) (2002) 69–77. [35] C. Romagnani, K. Juelke, M. Falco, B. Morandi, A. D'Agostino, R. Costa, et al., CD56brightCD16- killer Ig-like receptor- NK cells display longer telomeres and acquire features of CD56dim NK cells upon activation, J. Immunol. 178 (8) (2007) 4947–4955. [36] B.L. Ferry, J. Jones, E.A. Bateman, N. Woodham, K. Warnatz, M. Schlesier, et al., Measurement of peripheral B cell subpopulations in common variable immunodeficiency (CVID) using a whole blood method, Clin. Exp. Immunol. 140 (3) (2005) 532–539. [37] R.M. Dunham, B. Cervasi, J.M. Brenchley, H. Albrecht, A. Weintrob, B. Sumpter, et al., CD127 and CD25 expression defines CD4+ T cell subsets that are differentially depleted during HIV infection, J. Immunol. 180 (8) (2008) 5582–5592. [38] V. Appay, S.L. Rowland-Jones, Lessons from the study of T-cell differentiation in persistent human virus infection, Semin. Immunol. 16 (3) (2004) 205–212. [39] G. Lal, P. Balmer, E. Stanford, S. Martin, R. Warrington, R. Borrow, Development and validation of a nonaplex assay for the simultaneous quantitation of antibodies to nine Streptococcus pneumoniae serotypes, J Immunol Methods 296 (1–2) (2005) 135–147. [40] N.F. Concepcion, C.E. Frasch, Pneumococcal type 22f polysaccharide absorption improves the specificity of a pneumococcalpolysaccharide enzyme-linked immunosorbent assay, Clin. Diagn. Lab. Immunol. 8 (2) (2001) 266–272. [41] F.A. Bonilla, I.L. Bernstein, D.A. Khan, Z.K. Ballas, J. Chinen, M.M. Frank, et al., Practice parameter for the diagnosis and management of primary immunodeficiency, Ann. Allergy Asthma Immunol. 94 (5 Suppl 1) (2005) S1–S63. [42] C.J. Wu, A. Chillemi, E.P. Alyea, E. Orsini, D. Neuberg, R.J. Soiffer, et al., Reconstitution of T-cell receptor repertoire diversity following T-cell depleted allogeneic bone marrow transplantation is related to hematopoietic chimerism, Blood 95 (1) (2000) 352. [43] M. Vukmanovic-Stejic, Y. Zhang, J.E. Cook, J.M. Fletcher, J.M. McQuaid, J.E. Masters, et al., Human CD4+ CD25hi Foxp3+ regulatory T cells are derived by rapid turnover of memory populations in vivo, J. Clin. Invest. 116 (9) (2006) 2423–2433. [44] L.A. Jackson, K.M. Neuzil, O. Yu, P. Benson, W.E. Barlow, A.L. Adams, et al., Effectiveness of pneumococcal polysaccharide vaccine in older adults, N. Engl. J. Med. 348 (18) (2003) 1747–1755. [45] D. Goldblatt, M. Hussain, N. Andrews, L. Ashton, C. Virta, A. Melegaro, et al., Antibody responses to nasopharyngeal carriage of Streptococcus pneumoniae in adults: a longitudinal household study, J. Infect. Dis. 192 (3) (2005) 387–393. [46] D.A. Scott, S.F. Komjathy, B.T. Hu, S. Baker, L.A. Supan, C.A. Monahan, et al., Phase 1 trial of a 13-valent pneumococcal conjugate vaccine in healthy adults, Vaccine 25 (33) (2007) 6164–6166. [47] L. Moens, M. Wuyts, I. Meyts, K. De Boeck, X. Bossuyt, Human memory B lymphocyte subsets fulfill distinct roles in the antipolysaccharide and anti-protein immune response, J. Immunol. 181 (8) (2008) 5306–5312. [48] E.J. Yager, M. Ahmed, K. Lanzer, T.D. Randall, D.L. Woodland, M.A. Blackman, Age-associated decline in T cell repertoire diversity leads to holes in the repertoire and impaired immunity to influenza virus, J. Exp. Med. 205 (3) (2008) 711–723. [49] I. Messaoudi, J. Warner, D. Nikolich-Zugich, M. Fischer, J. Nikolich-Zugich, Molecular, cellular, and antigen requirements for development of age-associated T cell clonal expansions in vivo, J. Immunol. 176 (1) (2006) 301–308.

[17]

[18]

[19]

[20]

[21]

[22]

[23]

[24]

[25]

[26]

[27]

[28]

[29]

[30]

[31]

[32]

[33]

36 [50] K. Ito, K. Takubo, F. Arai, H. Satoh, S. Matsuoka, M. Ohmura, et al., Regulation of reactive oxygen species by ATM is essential for proper response to DNA double-strand breaks in lymphocytes, J. Immunol. 178 (1) (2007) 103–110. [51] Y. Xu, T. Ashley, E.E. Brainerd, R.T. Bronson, M.S. Meyn, D. Baltimore, Targeted disruption of ATM leads to growth retardation, chromosomal fragmentation during meiosis, immune defects, and thymic lymphoma, Genes Dev. 10 (19) (1996) 2411–2422. [52] C.Y. Huang, G.G. Sharma, L.M. Walker, C.H. Bassing, T.K. Pandita, B.P. Sleckman, Defects in coding joint formation in vivo in developing ATM-deficient B and T lymphocytes, J. Exp. Med. 204 (6) (2007) 1371–1381. [53] K. Ito, A. Hirao, F. Arai, S. Matsuoka, K. Takubo, I. Hamaguchi, et al., Regulation of oxidative stress by ATM is required for selfrenewal of haematopoietic stem cells, Nature 431 (7011) (2004) 997–1002. [54] R.H. Cho, H.B. Sieburg, C.E. Muller-Sieburg, A new mechanism for the aging of hematopoietic stem cells: aging changes the clonal composition of the stem cell compartment but not individual stem cells, Blood 111 (12) (2008) 5553–5561.

A.R. Exley et al. [55] N. Vrisekoop, I. den Braber, A.B. de Boer, A.F. Ruiter, M.T. Ackermans, S.N. van der Crabben, et al., Sparse production but preferential incorporation of recently produced naive T cells in the human peripheral pool, Proc. Natl Acad. Sci. U.S.A. 105 (16) (2008) 6115–6120. [56] I. Bains, R. Antia, R. Callard, A.J. Yates, Quantifying the development of the peripheral naive CD4+ T-cell pool in humans, Blood 113 (22) (2009) 5480–5487. [57] G. Sen, Q. Chen, C.M. Snapper, Immunization of aged mice with a pneumococcal conjugate vaccine combined with an unmethylated CpG-containing oligodeoxynucleotide restores defective immunoglobulin G antipolysaccharide responses and specific CD4+–T-cell priming to young adult levels, Infect. Immun. 74 (4) (2006) 2177–2186. [58] Q. Chen, J.L. Cannons, J.C. Paton, H. Akiba, P.L. Schwartzberg, C.M. Snapper, A novel ICOS-independent, but CD28- and SAP-dependent, pathway of T cell-dependent, polysaccharidespecific humoral immunity in response to intact Streptococcus pneumoniae versus pneumococcal conjugate vaccine, J. Immunol. 181 (12) (2008) 8258–8266.