To ascertain which mononuclear cell subset deficiency plays a role in the marrow transplant recipient's susceptibility to infections, mononuclear cell subset counts were prospectively determined in 108 patients on day 80. Infections occurring between day 100 and 365 were recorded by an investigator blinded to the subset counts. In univariate analyses, the counts of the following subsets showed a significant inverse correlation with infection rates: total B cells, IgD+ B cells, IgD B cells, total CD4 T cells, CD28+ CD4 T cells, CD28 CD4 T cells, CD45RAlow/− CD4 T cells and monocytes. In multivariate analyses, the counts of the following subsets remained significantly inversely correlated with the infection rates: total B cells (P = .0004) and monocytes (P = .009). CD28 CD8 T-cell counts showed no correlation with infection rates. In conclusion, the susceptibility of patients to infections late posttransplant may be due in part to the slow reconstitution of B cells and monocytes.

Infections are frequent after marrow transplantation, even after neutrophil engraftment.1-6Ochs et al5 noted that the occurrence of postengraftment infection(s) was the dominant independent factor associated with increased nonrelapse mortality (RR = 5.5,P = .0001).

Quantitative deficiencies of lymphocytes and their subsets have been described in transplant recipients surviving past engraftment.6 For example, low memory B-cell counts are frequently detected in the first year and low CD4 T-cell counts (both naive and memory) are frequently detected in the first 5 years after transplant.7,8 However, which cell subset deficiency plays the most crucial role in the susceptibility of patients to late infections is unknown. Therefore, we evaluated mononuclear cell (MNC) subset counts and determined their correlations with the rate of late infections (occurring between day 100 and day 365).

 MNC subset counts were determined in 108 allogeneic marrow recipients transplanted between May 1996 and August 1997, who were outpatients and had no signs of relapse around day 80. Three of the 108 patients subsequently died before day 100 and were not evaluable for day 100-365 infections. The demographic and clinical information on the evaluable 105 patients is given in Table1. Prophylaxis of late infections included sulfamethoxazole/trimethoprim until day 180. A longer course of sulfamethoxazole/trimethoprim, usually with penicillin, was given to patients in whom clinical extensive chronic graft-vs-host disease (GVHD) developed. Six patients received intravenous immunoglobulin between day 100 and 365.

Table 1.

Patient characteristics

Median age 41  (range, 12-63) 
Diagnosis  
 Chronic myeloid leukemia 55  (52%) 
 Acute myeloid leukemia 19  (18%)  
 Acute lymphoid leukemia 9  (9%)  
 Acute biphenotypic leukemia 1  (1%) 
 Myelodysplasia 12  (11%)  
 Myelofibrosis 2  (2%) 
 Essential thrombocythemia 1  (1%)  
 Multiple myeloma 2  (2%)  
 Non-Hodgkin lymphoma 3  (3%) 
 Hodgkin disease 1  (1%)  
Donor compatibility  
 HLA-identical siblings 54  (51%) 
 HLA-A–, -B– and -DR–matched unrelated volunteers 38  (36%)  
 HLA-mismatched relatives 6  (6%)  
 HLA-mismatched unrelated volunteers 7  (7%)  
Pretransplant splenectomy 3  (3%)  
Number of previous hematopoietic cell transplants  
 0 100  (95%)  
 1 5  (5%) 
Conditioning*  
 Busulfan + cyclophosphamide 42  (40%) 
 Total body irradiation + cyclophosphamide 54  (52%) 
 Other 9  (9%)  
Graft  
 T-cell replete marrow 105  (100%)  
GVHD prophylaxis  
 Cyclosporine (daily until d 180) + methotrexate (d 1, 3, 6, 11) 92  (88%) 
 Other 13  (12%)  
Graft failure 0  (0%)  
Acute GVHD grade  
 0 10  (10%)  
 1 4  (4%) 
 2 77  (73%)  
 3 14  (13%)  
 4 0  (0%) 
Chimerism status on day 80  
 Full (more than 90% marrow cells of donor origin) 104  (99%)  
 Mixed (88% marrow cells of donor origin) 1  (1%)  
Relapse before day 365 8  (8%) 
Nonrelapse death before day 365 11  (10%)  
Clinical extensive chronic GVHD diagnosed before day 365 64  (61%) 
Median age 41  (range, 12-63) 
Diagnosis  
 Chronic myeloid leukemia 55  (52%) 
 Acute myeloid leukemia 19  (18%)  
 Acute lymphoid leukemia 9  (9%)  
 Acute biphenotypic leukemia 1  (1%) 
 Myelodysplasia 12  (11%)  
 Myelofibrosis 2  (2%) 
 Essential thrombocythemia 1  (1%)  
 Multiple myeloma 2  (2%)  
 Non-Hodgkin lymphoma 3  (3%) 
 Hodgkin disease 1  (1%)  
Donor compatibility  
 HLA-identical siblings 54  (51%) 
 HLA-A–, -B– and -DR–matched unrelated volunteers 38  (36%)  
 HLA-mismatched relatives 6  (6%)  
 HLA-mismatched unrelated volunteers 7  (7%)  
Pretransplant splenectomy 3  (3%)  
Number of previous hematopoietic cell transplants  
 0 100  (95%)  
 1 5  (5%) 
Conditioning*  
 Busulfan + cyclophosphamide 42  (40%) 
 Total body irradiation + cyclophosphamide 54  (52%) 
 Other 9  (9%)  
Graft  
 T-cell replete marrow 105  (100%)  
GVHD prophylaxis  
 Cyclosporine (daily until d 180) + methotrexate (d 1, 3, 6, 11) 92  (88%) 
 Other 13  (12%)  
Graft failure 0  (0%)  
Acute GVHD grade  
 0 10  (10%)  
 1 4  (4%) 
 2 77  (73%)  
 3 14  (13%)  
 4 0  (0%) 
Chimerism status on day 80  
 Full (more than 90% marrow cells of donor origin) 104  (99%)  
 Mixed (88% marrow cells of donor origin) 1  (1%)  
Relapse before day 365 8  (8%) 
Nonrelapse death before day 365 11  (10%)  
Clinical extensive chronic GVHD diagnosed before day 365 64  (61%) 

HLA indicates human lymphocyte antigens; GVHD, graft-versus-host disease.

*

Usual dosing: busulfan, 16 mg/kg, cyclophosphamide, 120 mg/kg, total body irradiation, 12.0-13.2 Gy.

Treated usually with prednisone 2 mg/kg for 10 to 14 days with subsequent taper over 50 days.

Treated usually with prednisone (0.5-1.0 mg/kg every other day plus cyclosporine (approximately 6 mg/kg orally every other day) for at least 9 months.

Blood was drawn on approximately day 80 under an IRB-approved protocol and MNC subsets were enumerated as described.9 Day 100-365 infections were counted by a chart reviewer blinded to the MNC subset counts (G.E.) and associations between the MNC subset counts and the infection rate were statistically tested (Table2, footnotes).

Table 2.

Significance of associations between day 80 MNC subset counts and day 100-365 infection rates

All infections* (n = 168)Severe infections (n = 20)Viral infections* (n = 65)Bacterial infections* (n = 19)Fungal infections* (n = 31)
Natural killer cells .16 .66 .65 .10 .52 
Monocytes .001 .01 .004 .14 .05 
 (−.34) (−.24) (−.21)   
B cells (total) .0001 .09 .02 .03 .0001 
 (−.36)  (−.18) (−.16) (−.33) 
 IgD+ B cells .0003 .34 .11 .09 .0004 
 (−.27)    (−.27)  
 IgD B cells .0002 .002 .02 .02 .006 
 (−.28) (−.28) (−.19) (−.21) (−.24) 
CD4 T cells (total) .003 .20 .02 .16 .05 
 (−.34)  (−.19)   
 CD45RAhigh CD4 T cells .06 .18 .09 .33 .07 
 CD45RAlow/− CD4 T cells .003 .13 .01 .14 .02 
 (−.32)  (−.19)  (−.21)  
 CD28+CD4 T cells .005 .19 .02 .15 .02 
 (−.33)  (−.19)  (−.22)  
 CD28CD4 T cells .04 .14 .07 .27 .29 
 (−.18)     
CD8 T cells (total) .35 .29 .97 .34 .57  
 CD11alowCD8 T cells .11 .02 .36 .06 .02 
  (−.18)   (−.19)  
 CD11ahigh CD8 T cells .62 .30 .70 .53 .88  
 CD28+CD8 T cells .04 .02 .13 .04 .08 
 (−.25) (−.22)  (−.23)  
 CD28CD8 T cells .84 .66 .35 .98 .62  
CD4CD8 T cells .05 .13 .29 .07 .16 
CD8+ CD8+ T cells .24 .28 .02 .99 .88 
   (−.14)   
All infections* (n = 168)Severe infections (n = 20)Viral infections* (n = 65)Bacterial infections* (n = 19)Fungal infections* (n = 31)
Natural killer cells .16 .66 .65 .10 .52 
Monocytes .001 .01 .004 .14 .05 
 (−.34) (−.24) (−.21)   
B cells (total) .0001 .09 .02 .03 .0001 
 (−.36)  (−.18) (−.16) (−.33) 
 IgD+ B cells .0003 .34 .11 .09 .0004 
 (−.27)    (−.27)  
 IgD B cells .0002 .002 .02 .02 .006 
 (−.28) (−.28) (−.19) (−.21) (−.24) 
CD4 T cells (total) .003 .20 .02 .16 .05 
 (−.34)  (−.19)   
 CD45RAhigh CD4 T cells .06 .18 .09 .33 .07 
 CD45RAlow/− CD4 T cells .003 .13 .01 .14 .02 
 (−.32)  (−.19)  (−.21)  
 CD28+CD4 T cells .005 .19 .02 .15 .02 
 (−.33)  (−.19)  (−.22)  
 CD28CD4 T cells .04 .14 .07 .27 .29 
 (−.18)     
CD8 T cells (total) .35 .29 .97 .34 .57  
 CD11alowCD8 T cells .11 .02 .36 .06 .02 
  (−.18)   (−.19)  
 CD11ahigh CD8 T cells .62 .30 .70 .53 .88  
 CD28+CD8 T cells .04 .02 .13 .04 .08 
 (−.25) (−.22)  (−.23)  
 CD28CD8 T cells .84 .66 .35 .98 .62  
CD4CD8 T cells .05 .13 .29 .07 .16 
CD8+ CD8+ T cells .24 .28 .02 .99 .88 
   (−.14)   

Data are displayed as P value for univariate analysis (Spearman rank correlation coefficient). The correlation coefficient is shown only if P < .05. Bold entries denote the mononuclear cell (MNC) subsets that remained significantly associated with infection rates in multivariate analyses. The significance of association was tested as follows: Poisson regression models were fit using the SAS Genmod procedure using the log of the number of days at risk as a fixed predictor (offset). Days at risk were calculated as 365 or the posttransplant day of death or relapse (whichever occurred first) minus 100. Multivariate models were constructed by including all confounders significant in univariate models, and then applying a forward selection procedure to the MNC subset data. The most significant variable was added at each step until no variable entered at the .05 level of significance. Potential confounders (factors other than MNC subset counts that could influence the rate of late infections) considered in the multivariate analyses were donor relatedness/matching (HLA-matched siblings vs others), number of previous hematopoietic cell transplants (0 vs 1), disease and disease stage (diseases treated with multiple chemothrapies vs no chemotherapy, except for hydroxyurea before transplant), splenectomy (yes vs no), total body irradiation in conditioning regimen (yes vs no), administration of anticytomegalovirus T cells (yes vs no), use of corticosteroids in the first 3 months after transplant (yes vs no), occurrence of clinical extensive chronic graft-versus-host disease (GVHD) by day 365 (yes vs no), use of prophylactic antibiotics between day 100 and 365 apart from the routine trimethoprim/sulfamethoxazole to day 180 (yes vs no), use of intravenous immunoglobulin between day 180 and 365 (yes vs no), use of alpha-interferon between day 100 and 365 (yes vs no), and use of immunosuppressive drugs between day 100 and 365 apart from the routine cyclosporine taper by day 180 (yes vs no).

*

Definition of infection: Isolation of a pathogen from a site associated with symptoms or signs of infection, or, in the absence of a microbiologic isolate, the presence of symptoms and signs diagnostic of infection. For categorizing infections as viral, bacterial, or fungal, the infectious agent had to be microbiologically documented, except for shingles, where clinical diagnosis was considered sufficient. Presumed gastroenteritis and presumed respiratory tract infections were not counted because data on their presence or absence were not reliable. Sinusitis or pneumonia was counted only if verified by an imaging study. Cytomegalovirus (pp65) antigenemia was counted as an infection if more than 5 positive cells per slide were detected.23 A polymicrobial infection of one organ or several adjacent organs was counted as one infection. Infections with one microorganism in 2 nonadjacent organs were counted as 2 infections. Recurrent infections were counted as multiple infections only if clearly separated by a period of healed infection.

Treated in a hospital (not outpatient).

IgD+ B cells represent naive B cells, as most IgD+ B cells have been shown to lack somatic mutations.15-17 Naive CD4 T cells were counted as CD45RAhigh CD4 T cells, as this subset has been shown to contain thymic emigrants.18,19 Naive CD8 T cells were defined as CD11alow CD8 T cells, as virtually all cord blood CD8 T cells are CD11alow and become CD11ahigh after activation.20,21CD28+ T cells represent cells that can receive both the T-cell receptor-mediated signal and the CD28-mediated costimulatory signal.22 

On day 80, the counts of all MNC subsets studied (Table 2) were significantly lower compared with the MNC subset counts in 103 healthy adult volunteers (P < .001, Mann-Whitney test). Between day 100 and day 365 or the day of relapse or death (whichever occurred first), a total of 168 infections developed (average, 1.6 per patient).

In univariate analyses, the counts of the following MNC subsets inversely correlated with the rate of all infections (P < .05): total B cells, IgD+ B cells, IgD B cells, total CD4 T cells, CD45RAlow/−CD4 T cells, CD28+ CD4 T cells, CD28 CD4 T cells, CD28+ CD8 T cells, and monocytes (Table 2).

In multivariate analyses, factors other than the MNC cell subsets possibly influencing the rate of infections were considered as confounders (Table 2, footnote). Of all the potential confounders, only the use of corticosteroids in the first 3 months after transplant was associated with significantly increased rate of all day 100-365 infections in univariate analyses (P = .04). However, in the multivariate analyses, only low total B-cell count and low monocyte count remained significantly associated with increased rate of infections (P = .0004 for B cells, P = .009 for monocytes).

Both the univariate and the multivariate analyses were also performed separately for severe infections (defined as infections requiring hospitalization), viral infections, bacterial infections, and fungal infections. In the univariate analyses, the rates of severe, viral, bacterial, and fungal infections tended to inversely correlate with the same MNC subset counts, as the rates of all infections (Table 2). In the multivariate analyses, the low IgD B-cell count remained significantly associated with increased rates of severe infections (P = .003) and bacterial infections (P = .03), the low monocyte count remained significantly associated with increased rate of viral infections (P = .004), and the low total B-cell count remained significantly associated with increased rate of fungal infections (P = .0003).

We also evaluated whether a day 80 MNC subset count was associated with relapse rate or nonrelapse mortality before day 365, using a Mann-Whitney test. No MNC subset count was significantly different in the patients who relapsed compared with those who did not. The total B-cell count was lower in the patients who died without relapse (median, 0.9 × 106/L) than in the patients who did not (median, 2.5 × 106/L), (2-sided P = .092, 1-sided P = .046); whereas the other MNC subset counts were not different.

These data are insufficient to resolve the question of whether the association between B cell and monocyte counts and infections reflects the importance of B cells and monocytes for decreasing susceptibility to infections or that the B cell and monocyte counts may be merely surrogate markers for the quality of the marrow graft. We attempted to determine this by evaluating absolute neutrophil count as a measure of graft function. Day 80 neutrophil counts showed no correlation with infections (Spearman rank correlation coefficientr = −0.05) and no correlation with B-cell counts. In contrast, day 80 IgG level showed a trend toward inverse correlation with infections (Spearman rank correlation coefficientr = −0.40), suggesting that the B cells themselves may be important. As the IgG level was available for only 34 patients who did not receive intravenous immunoglobulin between day 0 and day 80, this was not statistically significant. Other data also support B-cell function as important. Riches et al10 described 3.5 times greater incidence of late infections in patients with low compared with those with normal serum IgG2 and IgG4 levels. Among marrow transplant recipients participating in our randomized trial of placebo versus intravenous immunoglobulin that did not contain IgA,11 there was a significant inverse correlation between day 100 serum IgA level and the rate of late infections (P = .01) (unpublished data). Sheridan et al12 described significant association between low serum IgG2 and IgG4 levels and the incidence of late pneumococcal infections. Thus, given the lack of an association between day 80 neutrophil counts and late infections and given the probable association between day 80 immunoglobulin levels and late infections, we favor the explanation that the slow reconstitution of B cells themselves plays an important role in susceptiblity to infections. Interestingly, low monocyte counts were also associated with infections. However, monocyte deficiency was not as dramatic as B-cell deficiency (median monocyte count was 291 vs 391 × 106/L in patients and normals, respectively; whereas median B-cell count was 2 vs 253 × 106/L). It is possible that the association of monocyte counts with infections could be due to the importance of monocyte/macrophage-mediated phagocytosis, antigen presentation, or secretion of monokines such as interleukin-1.

The primary goal of this study was to identify an MNC subset associated with infections. However, the data also provide the opportunity to ask which MNC subsets are not associated with infections. Of the subsets listed in Table 2, the count of the CD28 CD8 T cells was the least associated with the rate of all infections (Spearman rank correlation coefficient r = −0.01, P = .84). This is not surprising, as CD28 CD8 T cells in vitro do not readily proliferate on CD3 cross-linking and are considered anergic.13,14 Thus, the lack of association between CD28 CD8 T-cell counts and infections suggests that the CD28 CD8 T cells are also anergic in vivo.

We conclude that the reconstitution of B cells and monocytes may play an important role in marrow transplant recipient defense against microorganisms. This may be tested by adoptively transferring donor B cells and/or monocytes. Alternatively, the use of donor peripheral blood stem cells instead of marrow may provide a larger B-cell/monocyte inoculum, or these cells may be augmented by the use of growth factors.

We are indebted to the hard work of the staff of the Fred Hutchinson Cancer Research Center Long-Term Follow-Up Department and the staff of the Fred Hutchinson Cancer Research Center Outpatient Department.

Supported by National Institutes of Health grants Nos. CA68496 and AI46108.

The publication costs of this article were defrayed in part by page charge payment. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 U.S.C. section 1734.

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Author notes

Jan Storek, FHCRC, D1-100, 1100 Fairview Ave N, Seattle, WA 98109-1024; e-mail: jstorek@fhcrc.org.

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