Summary
Background
This study investigated the mechanisms involved in development of donor-specific antibody (DSA) and/or C4d-negative transplant glomerulopathy (TGP) by allograft gene expression profiles using microarrays.
Design, Setting, Participants, & Measurements
This cohort study was conducted in kidney transplant recipients. Patients were eligible for inclusion if they required a clinically indicated biopsy at any time point after their transplant. They were then classified according to their histopathology findings and DSA and C4d results. Eighteen chronic antibody-mediated rejection (CAMR), 14 DSA+/C4d− TGP, 25 DSA−/C4d− TGP, and 47 nonspecific interstitial fibrosis/tubular atrophy (IFTA) biopsy specimens were identified. In a subset of patients from the study population, biopsy specimens in each group and normal transplant kidney specimens were analyzed with Affymetrix Human Gene 1.0 ST Arrays.
Results
The mean sum score of glomerulitis and peritubular capillaritis increased from 0.28±0.78 in IFTA specimens to 0.75±0.85 in DSA−/C4d− TGP specimens, 1.71±1.49 in DSA+/C4d−/TGP specimens, and 2.11±1.74 in CAMR specimens (P<0.001). During a median follow-up time of 2 (interquartile range, 1.4–2.8) years after biopsy, graft loss was highest in CAMR specimens (27.8%) compared to IFTA specimens (8.5%), DSA+/C4d− TGP specimens (14.3%), and DSA−/C4d− TGP specimens (16%) (P=0.01). With use of microarrays, comparison of the gene expression profiles of DSA−/C4d− TGP specimens with glomerulitis + peritubular capillaritis scores > 0 to normal and IFTA biopsy specimens revealed higher expression of quantitative cytotoxic T cell–associated transcripts (QCAT). However, both CAMR and DSA+/C4d− TGP specimens had higher expression of not only QCAT but also IFN-γ and rejection-induced, constitutive macrophage-associated, natural killer cell–associated, and DSA-selective transcripts. Endothelial cell–associated transcript expression was upregulated only in CAMR biopsy specimens.
Conclusions
These results suggested that DSA+/C4d− TGP biopsy specimens may be classified as CAMR. In contrast, DSA−/C4d− TGP specimens showed increased cytotoxic T cell–associated transcripts, suggesting T cell activation as a mechanism of injury.
Introduction
The Banff classification (1) requires three criteria for the diagnosis of chronic antibody-mediated rejection (CAMR): histologic evidence of chronic tissue injury, C4d immunostaining of peritubular capillaries, and the presence of antidonor antibodies (DSA). The endothelium is the main target of injury in CAMR. The result of this injury, endothelial remodeling, is demonstrated histologically by duplication of the glomerular capillary basement membranes (transplant glomerulopathy [TGP]) and multilayering of peritubular capillary basement membranes. Another change associated with CAMR is microvascular inflammation, seen histologically as glomerulitis (g) and peritubular capillaritis (ptc) (2–4).
Two issues arise in the use of the Banff criteria for diagnosis. First, there is evidence that CAMR may exist in the absence of C4d expression. Several studies have identified transplant biopsy samples with all criteria for CAMR except C4d positivity (5–7). The second issue is that another criterion for CAMR, TGP, may develop without antibody-mediated allograft injury. TGP is reported to be associated with donor-specific antibody (DSA), especially class II DSA (5,8), but histologic evidence of TGP may be seen without C4d and DSA (9). Increased chemokine (CXCL9 and CXCL10) and chemokine receptor (CXCR3) expression by glomerular leukocytes, which is associated with effector T cell activation (10) and other T cell–mediated inflammatory or cytotoxic processes (11–14), have been demonstrated in TGP biopsy specimens. Nonimmune mechanisms may also be associated with TGP, as suggested by a recent report of hepatitis C virus infection (36%) and thrombotic microangiopathy (32%) in 25 patients with TGP (15).
Gene expression profiles of TGP biopsy specimens according to DSA and C4d staining status have not been investigated by microarrays. In this study, we characterize the clinical, histopathologic, and genomic features of C4d− CAMR (TGP with DSA) and C4d−/DSA− TGP. We hypothesize that TGP is end-organ damage caused by multiple mechanisms and should first be classified into two groups: DSA+ and DSA− TGP (Figure 1). We propose that TGP develops through antibody-mediated injury in patients with DSA, whether C4d+ or C4d− (DSA+/C4d+ TGP and DSA+/C4d− TGP). In patients who lack both DSA and C4d (DSA−/C4d− TGP) but have inflammatory cells as microvascular inflammation (g + ptc scores > 0), or g + ptc + i (interstitial inflammation) scores > 1, TGP might develop through cellular immune-mediated mechanisms.
Figure 1.
Hypothesis of the mechanisms leading to the development of transplant glomerulopathy stratified by donor-specific antibody (DSA) and C4d results. AMR, antibody-mediated rejection; CNI, calcineurin inhibitor, g, glomerulitis; i, interstitial inflammation; ptc, peritubular capillaritis; TMA, thrombotic microangiopathy.
Materials and Methods
Study Design
All clinically indicated kidney transplant biopsies performed at our institution between January 2009 and July 2011 were eligible for inclusion. Patients were excluded if they were younger than 18 years of age, had an inadequate biopsy specimen, or did not undergo DSA testing. Biopsy specimens were grouped by a diagnosis of CAMR, TGP, and nonspecific interstitial fibrosis/tubular atrophy (IFTA), and further subgrouped by DSA and C4d status. Biopsy specimens classified as normal were used as a control group for microarray analysis. Demographic and clinical information were obtained from the patients’ charts after approval from the institutional review board. The clinical and research activities being reported are consistent with the Principles of the Declaration of Istanbul as outlined in the “Declaration of Istanbul on Organ Trafficking and Transplant Tourism.”
Histopathology, C4d Staining, and Electron Microscopy
Two pathologists (J.P. and D.S.) who were blinded to the diagnosis independently scored and assessed all biopsy specimens using Banff 2007/2009 criteria (16,17). One pathologist (J.P.) evaluated all electron micrographs for transplant glomerulopathy and other changes. Biopsy specimens were examined by light microscopy using hematoxylin and eosin, periodic acid-Schiff, Masson trichrome, and C4d immunoperoxidase stains. Immunoperoxidase staining for C4d was performed on paraffin-embedded sections using a polyclonal rabbit antihuman antibody (Cell Marque) at a dilution of 1:100 with the Dako Envision system.
Evaluation of the biopsy specimens was based on the Banff 2007/2009 acute and chronic indices, including glomerulitis (g), interstitial inflammation (i), tubulitis (t), intimal arteritis (v), peritubular capillaritis (ptc), transplant glomerulopathy (cg), mesangial matrix increase (mm), interstitial fibrosis (ci), tubular atrophy (ct), vascular fibrous intimal thickening (cv), arteriolar hyaline thickening (ah), and C4d (18). Biopsy specimens were classified as TGP by electron microscopy if they showed electron-lucent widening of the subendothelial zone of the glomerular basement membrane, subendothelial accumulation of flocculent material, with or without a new subendothelial basement membrane layer (19).
Anti-HLA Antibody Detection
Anti-HLA antibodies were studied by Luminex HLA Single Antigen Bead assays (LABScreen, One Lambda Inc., Canoga Park, CA), which use a panel of color-coded beads coated with purified single HLA antigens. These antigens include HLA-A, -B, -Cw, -DR, and -DQ. The antibody specificity and strength were analyzed with HLA Fusion software, version 2.0 (One Lambda Inc.). The cutoff value for a positive DSA was a mean fluorescence intensity ≥1000.
RNA Preparation and Microarray Hybridization
One biopsy core was collected into a vial containing 1 ml of RNALater (Ambion, catalog no. AM7023), stored at −20°C for 24 hours and then transferred to −70°C until RNA isolation. Renal tissue and glomerular content in all cores were verified by Pathology Department technical personnel using a dissecting microscope and any nonrenal tissue was removed. Total RNA was isolated using the Qiagen RNeasy Mini Kit (catalog no. 74104). The complete protocols for converting total RNA into biotin-labeled RNA and for Affymetrix Human Gene 1.0 ST Array hybridization (28,869 gene probe sets) are in the manufacturer’s instructions for the Ambion Whole Transcript Expression Kit (catalog no. 4425209, Ambion, Austin, TX) and the Affymetrix Gene Chip Whole Transcript Terminal Labeling Kit (catalog no. 900671, Affymetrix, Santa Clara, CA).
Statistical Analyses
Demographic and Clinical Data.
Demographic and clinical data were compared using the Kruskal-Wallis test or ANOVA for continuous variables and the chi-squared or Fisher exact test for categorical variables. Kaplan-Meier death-censored survival estimates were determined by defining the survival time as the time from the date of the biopsy and death (with a functioning graft), the most recent follow-up date or the end of the study period. Graft failure was defined as return to dialysis after transplantation. All statistical analyses were performed using Stata software, version 11.0 (College Station, TX). A P value cutoff of <0.05 was considered to represent a statistically significant difference.
Microarray Data.
A subset of 57 patients had adequate biopsy specimens, which were used for gene expression profiling by microarrays. The gene expression profiles of the biopsy specimens were compared according to the following groups: (1) normal transplant kidney biopsy specimens (n=12); (2) nonspecific IFTA (n=17); (3) DSA−/C4d− TGP (g + ptc > 0) (n=8); (4) DSA+/C4d− TGP (n=9); (5) DSA+/C4d+ CAMR (n=11). We did not have an adequate number of biopsy samples of DSA−/C4d− TGP with g + ptc score of 0.
The methods for microarray analysis are described in detail in our previous publications (20,21). Gene Set libraries were taken from the Molecular Signatures Database (22), and new libraries were generated by mapping HUGO gene identifiers to the University of Alberta, Edmonton, pathogenesis-based transcripts (PBT; http://transplants.med.ualberta.ca/Nephlab/data/gene_lists.html) gene sets. The following core PBT were analyzed: (1) KT: kidney-specific transcripts (n=63); (2) IRIT: injury and repair-induced transcripts (n=228); (3) GRIT: γ-IFN and rejection-induced transcripts (n=50); (4) QCAT: quantitative cytotoxic T cell–associated transcripts (n=25); (5) CMAT: quantitative constitutive macrophage-associated transcripts (n=72); (6) BAT: B cell–associated transcripts (n=50); (7) NKAT: natural killer cell–associated transcripts (n=244); (8) ENDAT: endothelial cell–associated transcripts (n=114); (9) DSAST: DSA-selective transcripts (n=25).
Analysis for changes in gene expression of gene ontology categories was performed using the GOstats Bioconductor package to calculate P values by conditional hypergeometric tests for over or under-representation of each GO term. The data discussed in this publication were deposited in GEO with accession number GSE44131.
Results
Patient Demographic Characteristics
One hundred four participants were included in our analyses. Histologic diagnoses included 18 with CAMR, 14 with DSA+/C4d− TGP, 25 with DSA−/C4d− TGP, and 47 with nonspecific IFTA. Of the 39 TGP biopsy specimens, only 4 were diagnosed by electron microscopy alone. Of the 18 CAMR biopsy specimens, 7 also had histopathologic findings of TGP.
There were no significant differences in age, sex, race, cause of kidney disease, anti–hepatitis C antibody status, history of transplantation or acute rejection, or immunosuppression (Table 1). The IFTA group was associated with the shortest median time interval between the date of transplantation and biopsy compared with other three groups. The two TGP groups were associated with more proteinuria at the time of biopsy compared to the IFTA group (P=0.03).
Table 1.
Demographic and clinical data of the patient population
| Variable | CAMR (DSA+/C4d+) (n=18) | TGP (DSA+/C4d−) (n=14) | TGP (DSA−/C4d−) (n=25) | IFTA (DSA−/C4d−) (n=47) | P Value |
|---|---|---|---|---|---|
| Age (yr) | 46 (35–46) | 45 (39–58) | 44 (31–56) | 50 (37–61) | 0.33 |
| Men, n (%) | 10 (56) | 8 (57) | 18 (72) | 27 (57) | 0.61 |
| African Americans, n (%) | 5 (28) | 4 (29) | 9 (36) | 17 (36) | 0.89 |
| Deceased-donor transplant, n (%) | 11 (61) | 10 (71) | 16 (64) | 36 (77) | 0.55 |
| Prior transplantation, n (%) | 1 (6) | 2 (14) | 3 (12) | 7 (15) | 0.81 |
| Prior acute rejection, n (%) | 7 (39) | 2 (14) | 3(12) | 6 (13) | 0.10 |
| Underlying diagnosis, n (%) | 0.07 | ||||
| Diabetes | 4 (22) | 3 (21) | 7 (28) | 4 (9) | |
| Hypertension | 2 (11) | 2 (14) | 9 (36) | 18 (38) | |
| Diabetes and hypertension | 0 | 1 (7) | 1 (4) | 6 (13) | |
| Glomerular | 4 (22) | 4 (28) | 5 (20) | 11 (23) | |
| Other | 3 (17) | 1 (7) | 3 (12) | 6 (13) | |
| Unknown | 5 (28) | 3 (21) | 0 | 2 (4) | |
| Hepatitis C virus antibody positive, n (%) | 1 (6) | 2 (14) | 2 (8) | 1 (2) | 0.22 |
| Time to biopsy (yr) | 3.9 (2.2–8.1) | 5.1 (2.7–10) | 4.1 (2–7.1) | 1.4 (0.3–5.3) | <0.001 |
| Serum creatinine at biopsy (mg/dl) | 2.3 (1.7–4) | 1.6 (1.4–2.3) | 2.7 (2–3) | 2.3 (1.9–2.9) | 0.02 |
| Spot urinary protein-to-creatinine ratio at biopsy | 0.7 (0.1–2) | 2.1 (0.1–3) | 1.1 (0.3–2.3) | 0.2 (0.1–0.7) | 0.03 |
| Immunosuppression, n (%) | 0.10 | ||||
| Tacrolimus/MMF/prednisone | 10 (56) | 10 (72) | 8 (32) | 31 (66) | |
| CsA/MMF/prednisone | 1 (5) | 1 (7) | 0 | 2 (4) | |
| CsA or tacrolimus + prednisone | 3 (17) | 2 (14) | 6 (24) | 3 (6) | |
| Tacrolimus/MMF | 1 (5) | 0 | 1 (4) | 2 (4) | |
| Other | 3 (17) | 1 (7) | 10 (40) | 9 (20) |
All continuous variables are displayed as median (interquartile range) for continuous variables and n (%) for categorical variables. P values represent comparisons between the four groups. CAMR, chronic antibody-mediated rejection; DSA, donor-specific antibody; TGP, transplant glomerulopathy; IFTA, interstitial fibrosis/tubular atrophy; MMF, mycophenolate mofetil; CsA, cyclosporine A.
CAMR and DSA+/C4d− TGP Groups Have Increased Microcirculation Injury
The mean Banff scores of the four groups stratified by the histologic diagnosis are shown in Table 2. The mean g score was increased in the CAMR group (0.72±0.83) and both DSA+ and DSA− TGP groups (0.64±0.84 and 0.48±0.82, respectively) compared with the IFTA group (0.06; P=0.008). However, the mean ptc score was significantly higher only in the CAMR (1.39±1.14) and DSA+/C4d− TGP (1.07±1.11) groups (P<0.001), but not in the DSA−/C4d− TGP (0.25±0.44) group compared with the IFTA group (0.21), suggesting that peritubular capillaritis correlates better with DSA regardless of C4d status, while glomerulitis correlates with TGP regardless of DSA status. The scores for g + ptc and g + ptc + i increased from the IFTA group (0.28 and 0.96) to the DSA−/C4d− TGP (0.75 and 1.63), DSA+/C4d−/TGP (1.71 and 2.79), and CAMR (2.11 and 3.72) groups, respectively (P<0.001 for both comparisons). While the g + ptc score was >0 in only 17% of the IFTA group, it was seen in 72% and 79% of CAMR and DSA+/C4d− TGP biopsy specimens, respectively. Half of the DSA−/C4d− TGP biopsy specimens showed inflammatory cells with g + ptc scores >0% (52%) and g + ptc + i scores >1 (50%).
Table 2.
Comparison of the mean Banff scores stratified by pathologic diagnosis
| Banff Classification | CAMR (DSA+/C4d+) (n=18) | TGP (DSA+/C4d−) (n=14) | TGP (DSA−/C4d−) (n=25) | IFTA (DSA−/C4d−) (n=47) | P Value |
|---|---|---|---|---|---|
| g | 0.72±0.83 | 0.64±0.84 | 0.48±0.82 | 0.06±0.25 | 0.008 |
| ptc | 1.39±1.14 | 1.07±1.11 | 0.25±0.44 | 0.21±0.59 | <0.001 |
| i | 1.61±1.03 | 1.07±0.73 | 0.88±0.6 | 0.68±0.89 | 0.006 |
| g + ptc | 2.11 | 1.71 | 0.75 | 0.28 | <0.001 |
| g + ptc = 0 (%) | 5 (28) | 3 (21) | 12 (48) | 39 (83) | <0.001 |
| g + ptc > 0 (%) | 13 (72) | 11 (79) | 13 (52) | 8 (17) | <0.001 |
| g + ptc + i | 3.72 | 2.79 | 1.63 | 0.96 | <0.001 |
| g + ptc + i = 0 (%) | 0 | 1 (7) | 2 (8) | 23 (49) | <0.001 |
| g + ptc + i = 1 (%) | 4 (22) | 0 | 10 (42) | 13 (28) | <0.001 |
| g + ptc + i > 1 (%) | 14 (78) | 13 (93) | 12 (50) | 11 (23) | <0.001 |
| Tubulitis | 0.56±0.78 | 0.29±0.47 | 0.04±0.2 | 0.11±0.31 | 0.15 |
| Mesangial matrix | 0.83±0.99 | 0.93±0.73 | 0.68±0.9 | 0.28±0.45 | 0.03 |
| Interstitial fibrosis | 1.67±0.97 | 1.21±0.70 | 1.48±0.77 | 1.62±0.85 | 0.51 |
| Tubular atrophy | 1.83±1.1 | 1.29±0.61 | 1.36±0.91 | 1.51±0.83 | 0.46 |
| Intimal arteritis | 0.06±0.24 | 0 | 0 | 0.02±0.15 | 0.99 |
| Chronic vascular score | 0.83±0.71 | 0.71±0.91 | 0.96±0.89 | 0.76±0.61 | 0.78 |
| Arteriolar hyalinization | 0.94±1.09 | 1.14±1.1 | 1.04±1.02 | 0.64±0.92 | 0.22 |
Variables shown as mean ± SD or n (%). P values represent comparisons between the four groups. CAMR, chronic antibody-mediated rejection; DSA, donor-specific antibody; TGP, transplant glomerulopathy; IFTA, interstitial fibrosis/tubular atrophy; g, glomerulitis; ptc, peritubular capillaritis; i, interstitial inflammation.
Mesangial matrix expansion, a marker of chronic injury, was significantly different among the four groups and was highest in the DSA+/C4d− TGP group (0.93±0.73) followed by the CAMR (0.83±0.99), DSA−/C4d− TGP (0.68±0.9), and IFTA groups (0.28±0.45) (P=0.03).
There were no significant differences in the t, ct, ci, v, cv, and ah scores.
Decreased Death-Censored Graft Survival in CAMR
Figure 2 shows the Kaplan-Meier death-censored graft survival. During a median postbiopsy follow-up time of 2 (interquartile range, 1.4–2.8) years, graft loss after biopsy was observed in 8.5% of IFTA, 16% of DSA−/C4d− TGP, 14.3% of DSA+/C4d− TGP, and 27.8% of CAMR patients. CAMR was associated with a significantly lower graft survival compared with IFTA (P=0.01) but not compared with TGP with (P=0.08) and without (P=0.09) DSA.
Figure 2.
Kaplan-Meier death-censored graft survival stratified by histopathology, donor-specific antibody (DSA), and C4d result. CAMR, chronic antibody-mediated rejection; IFTA, interstitial fibrosis/tubular atrophy; TGP, transplant glomerulopathy.
Gene Expression Analysis
There were differentially expressed genes in DSA−/C4d− TGP with a g + ptc score >0 (n=43 genes), DSA+/C4d− TGP (n=1381 genes), and CAMR (n=3515 genes) biopsy specimens compared with normal transplant kidney biopsy specimens. Although there were no significant differentially expressed genes between DSA−/C4d− TGP and IFTA biopsy specimens, there were 254 differentially expressed genes in DSA+/C4d− TGP and 1264 in CAMR biopsy specimens compared with nonspecific IFTA.
There was no difference in expression of any PBT sets between nonspecific IFTA and normal transplant kidney biopsy specimens (Table 3). Comparison of DSA−/C4d− TGP biopsy specimens to normal (P=0.04) and nonspecific IFTA (P=0.008) biopsy specimens revealed significantly higher expression of QCAT, suggesting a role for cytotoxic T cells in development of DSA− TGP. However, CAMR and DSA+/C4d− TGP biopsy specimens had higher expression of QCAT, GRIT, CMAT, and DSAST compared with normal transplant kidney biopsy specimens, and in addition, higher NKAT compared with nonspecific IFTA biopsy specimens. ENDAT expression was upregulated in CAMR biopsy specimens compared with nonspecific IFTA biopsy specimens. CAMR biopsy specimens compared with DSA−/C4d− TGP biopsy specimens showed higher expression of GRIT, QCAT, CMAT, and DSAST. CAMR compared with DSA+/C4d− TGP biopsy specimens showed differentially higher expression of CMAT and DSAST. DSA+ TGP compared with DSA− TGP showed higher expression of GRIT and DSAST. These results suggest similar gene expression profiles in CAMR and DSA+/C4d− TGP involving increased activity of cytotoxic T cells, natural killer cells, macrophages, leading to cellular (GRIT) and antibody-mediated rejection (DSAST).
Table 3.
P values for upregulated genes in pathogenesis-based transcripts sets
| PBT | IFTA to Normal | DSA− TGP to Normal | DSA+ TGP to Normal | CAMR To Normal | DSA− TGP to IFTA | DSA+ TGP to IFTA | CAMR to IFTA | DSA+ TGP to DSA− TGP | CAMR to DSA− TGP | CAMR to DSA+ TGP |
|---|---|---|---|---|---|---|---|---|---|---|
| KT | 0.76 | 0.91 | 0.98 | 0.94 | 0.82 | 0.94 | 0.90 | 0.33 | 0.74 | 0.32 |
| IRIT | 0.63 | 0.44 | 0.98 | 0.31 | 0.18 | 0.20 | 0.10 | 0.34 | 0.23 | 0.31 |
| GRIT | 0.43 | 0.17 | 0.04 | 0.03 | 0.08 | 0.004 | 0.003 | 0.02 | 0.008 | 0.16 |
| QCAT | 0.30 | 0.04 | 0.02 | 0.01 | 0.008 | <0.001 | 0.002 | 0.11 | 0.04 | 0.16 |
| CMAT | 0.15 | 0.06 | 0.04 | 0.006 | 0.12 | 0.06 | 0.004 | 0.11 | 0.006 | 0.03 |
| BAT | 0.27 | 0.09 | 0.12 | 0.12 | 0.08 | 0.11 | 0.07 | 0.72 | 0.29 | 0.22 |
| NKAT | 0.49 | 0.33 | 0.09 | 0.09 | 0.05 | 0.02 | 0.02 | 0.15 | 0.10 | 0.30 |
| ENDAT | 0.51 | 0.44 | 0.22 | 0.07 | 0.36 | 0.17 | 0.02 | 0.22 | 0.05 | 0.08 |
| DSAST | 0.33 | 0.12 | <0.001 | <0.001 | 0.12 | <0.001 | <0.001 | <0.001 | <0.001 | 0.007 |
P values are calculated from t-statistics for upregulated genes in gene set analyzed. P<0.05 was considered to represent statistically significant difference. PBT, pathogenesis-based transcripts; IFTA, interstitial fibrosis/tubular atrophy; DSA, donor-specific antibody; TGP, transplant glomerulopathy; CAMR, chronic antibody-mediated rejection; KT, kidney transcripts; IRIT, injury and repair-induced transcripts; GRIT, γ-IFN and rejection-induced transcripts; QCAT, quantitative cytotoxic T cell–associated transcripts; CMAT, quantitative constitutive macrophage-associated transcripts; BAT, B cell–associated transcripts; NKAT, natural killer cell–associated transcripts; ENDAT, endothelial cell–associated transcripts; DSAST, donor-specific antibody selected transcripts.
The common top overrepresented gene ontology biologic process terms in all CAMR, DSA+/C4d−, and DSA−/C4d− TGP biopsy specimens are shown in Table 4. These genes are involved in activation, regulation, and effector function of leukocytes, T and B lymphocytes, mast cells, and immune response, suggesting an immune-mediated mechanisms in development of all TGP whether DSA+ or C4d+.
Table 4.
Common top overrepresented gene ontology biologic process terms in all chronic antibody-mediated rejection, donor-specific antibody–positive/C4d-negative, and donor-specific antibody–negative /C4d-negative TGP biopsy specimens
| GOBPID | Term |
|---|---|
| GO:0050867 | Positive regulation of cell activation |
| GO:0050778 | Positive regulation of immune response |
| GO:0002694 | Regulation of leukocyte activation |
| GO:0002429 | Immune response-activating cell surface receptor signaling pathway |
| GO:0051716 | Cellular response to stimulus |
| GO:0051251 | Positive regulation of lymphocyte activation |
| GO:0035556 | Intracellular signal transduction |
| GO:0007154 | Cell communication |
| GO:0006955 | Immune response |
| GO:0023052 | Signaling |
| GO:0002695 | Negative regulation of leukocyte activation |
| GO:0050852 | T cell receptor signaling pathway |
| GO:0050853 | B cell receptor signaling pathway |
| GO:0006917 | Induction of apoptosis |
| GO:0070663 | Regulation of leukocyte proliferation |
| GO:0016265 | Death |
| GO:0007166 | Cell surface receptor signaling pathway |
| GO:0042107 | Cytokine metabolic process |
| GO:0002274 | Myeloid leukocyte activation |
| GO:0042108 | Positive regulation of cytokine biosynthetic process |
| GO:0006954 | Inflammatory response |
| GO:0007159 | Leukocyte cell-cell adhesion |
| GO:0023051 | Regulation of signaling |
| GO:0030890 | Positive regulation of B cell proliferation |
| GO:0043299 | Leukocyte degranulation |
| GO:0002699 | Positive regulation of immune effector process |
| GO:0016064 | Immunoglobulin-mediated immune response |
| GO:0007249 | I-κB kinase/NF-κ B cascade |
| GO:0002440 | Production of molecular mediator of immune response |
| GO:0048583 | Regulation of response to stimulus |
| GO:0050670 | Regulation of lymphocyte proliferation |
| GO:0009891 | Positive regulation of biosynthetic process |
| GO:0002460 | Adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains |
| GO:0033005 | Positive regulation of mast cell activation |
| GO:0006952 | Defense response |
| GO:0006916 | Antiapoptosis |
GO, gene ontology.
Discussion
In this study, we report that both CAMR and DSA+/C4d− TGP biopsy specimens had higher microvascular inflammation (g + ptc) scores and similar gene expression profiles demonstrating activation of cytotoxic T cells, natural killer cells, macrophages, and gene transcripts associated with cellular and antibody-mediated rejection. The difference between CAMR and DSA+/C4d− TGP was a higher g + ptc score (2.11 versus 1.71) and more immune activity–related genes expressed. These results suggest that although there is more histopathologic and genomic immune activity in CAMR biopsy specimens, DSA+/C4d− TGP should be considered as a part of CAMR at a different level of ongoing chronic antibody-mediated allograft injury. In contrast, DSA−/C4d− TGP biopsy specimens lack gene transcript findings associated with antibody-mediated rejection (DSAST) or GRIT and only show upregulation of QCAT, suggesting a mechanism involving T cell activation. Interestingly, higher ptc scores were observed only in DSA+ but not in DSA−/C4d− TGP biopsy specimens. However, all TGP biopsy specimens had higher g scores regardless of DSA or C4d status, in agreement with previous evidence that peritubular capillaritis is a more specific marker of CAMR than is glomerulitis (23).
Our data raise the question of how allograft damage in DSA+ patients can occur without complement activation or C4d deposition. The Edmonton group showed that the biopsy specimens from DSA+ patients displayed three molecular phenotypes: upregulation of ENDAT (24), NKAT (25), and GRIT (26), similar to our findings. IFN-γ secreted by T cells and NK cells is essential for induction of class I and II antigens on endothelium and increases antibody binding to the endothelium, which is followed by complement fixation to induce allograft inflammation and injury. Complement-independent activation of endothelium, through DSA by Fc-Fc receptors, chemokines, and chemokine receptors, such as CXCL1 (fractalkine) and CX3CL1, adhesion molecules, and NK cells, has been shown in animal models and human kidney allografts (2).
Transplant glomerulitis is not currently a diagnostic criterion for any type of rejection but has been shown to be associated with TGP, circulating DSA, and positive C4d staining. Batal et al. reported that glomerulitis is associated with higher ptc scores, C4d positivity, and subsequent development of DSA and TGP, but not with interstitial inflammation, tubulitis, intimal arteritis, or T cell–mediated acute rejection (27). The same group later documented higher intraglomerular and peritubular capillary granzyme B+ leukocytes in 25 biopsy specimens with glomerulitis (28).
A study of the significance of peritubular capillaritis showed that >80% of biopsy specimens with glomerulitis and 50% of specimens with borderline or T cell–mediated rejection also had peritubular capillaritis, suggesting that it may not be specific for AMR (19). The microcirculation sum score (g + ptc) has been shown to be the best predictor of DSA and predicted graft failure independent of C4d and TGP. In a study by Sis et al., 67% of specimens with a g + ptc score >0 had DSA versus 20% of those with a g + ptc score of 0 (3).
Biopsy specimens from DSA+ patients with light microscopic (peritubular capillaritis and glomerulitis) or electron microscopic (endothelial swelling, subendothelial widening, and basement membrane duplication) features of AMR have been documented regardless of their C4d status, suggesting the existence of C4d− CAMR (6). Loupy et al. identified a category of DSA+ patients with histologic features of AMR (high g and ptc scores) but negative C4d in 3-month protocol biopsy specimens. These patients also had a higher rate of TGP (43%) in follow-up biopsy specimens at 1 year compared with biopsy specimens without subclinical AMR (0%), providing further evidence for C4d− CAMR (7). The same group also reported that microvascular inflammation and DSA are more robust predictors of poor allograft outcome than C4d positivity (29).
Hidalgo et al. studied the gene expression profiles of biopsy specimens with AMR and identified 23 selective gene transcripts in AMR (DSAST) but not cellular rejection (25). Six of those 23 genes showed selective high expression in NK cells and 8 were primarily expressed in endothelium. In our study DSAST was significantly upregulated in DSA+ biopsy specimens regardless of C4d status, as well as NKAT compared with IFTA biopsy specimens. However, NKAT was increased not only in AMR but also in acute cellular rejection and in biopsy specimens with IFTA and inflammation (30).
Dean et al. reported increased intragraft gene expression of inflammatory genes associated with adaptive and innate immunity in positive cross-matched kidney transplant recipients who developed TGP (31). Elster et al. investigated the intragraft gene expression of TGP biopsy specimens using 87 genes related to immune function and fibrosis (13). Fifty-seven genes were increased in 20 TGP biopsy specimens compared with stable kidney allografts, including ICAM-1, IL-10, CCL3, and CD86. Our results showed increased expression of QCAT but not of GRIT, DSAST, ENDAT, or NKAT, suggesting cytotoxic T cell–mediated but not antibody-mediated chronic injury. Homs et al. reported increased expression of IFN-γ, T-bet (a marker for Th1 CD4 T cells), and granzyme B (a CD8 marker) in TGP biopsy specimens, suggesting an active T cell–mediated inflammatory and cytotoxic process in the pathogenesis of TGP (11). Several other studies have also recognized that an increased cellular immune response involving T cells and monocytes is associated with the development of TGP (12–14). In our study group, half of the patients with DSA−/C4d− TGP with g + ptc score of 0 or g + ptc + i score ≤1 had no significant inflammatory cells, but we did not have adequate biopsy samples for microarray gene expression analysis. The pathogenesis of DSA−/C4d− TGP without any inflammatory cells therefore requires future study.
The small number of samples used for genomic analysis is a limitation of this study and makes it difficult to make changes in the current criteria. To validate our results, a multicenter study with large numbers of biopsy specimens needs to be conducted.
In summary, we have shown that regardless of C4d status, biopsy specimens from patients with TGP and DSA have increased microvascular inflammation scores and upregulated PBT related to antibody-mediated and cellular rejection, suggesting that DSA+/C4d− TGP should be classified as CAMR. In contrast, DSA−/C4d− TGP showed increased g scores without ptc and their gene expression profiles lacked upregulation of gene transcripts of antibody-mediated injury, but did show increased cytotoxic T cell–associated transcripts, suggesting T-cell activation as a mechanism of injury.
Disclosures
None.
Acknowledgments
This study is supported by an internal grant from Montefiore Medical Center and Albert Einstein College of Medicine.
The project described was supported in part by the National Center for Research Resources and the National Center for Advancing Translational Sciences, components of the National Institutes of Health, through CTSA grant numbers UL1RR025750, KL2RR025749, and TL1RR025748. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.
This study was accepted as an oral presentation at American Transplant Congress 2013 in Seattle, Washington.
Footnotes
Published online ahead of print. Publication date available at www.cjasn.org.
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