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Antibodies Reactive to Non-HLA Antigens in Transplant Glomerulopathy

Rajani Dinavahi,*† Ajish George,‡ Anne Tretin,* Enver Akalin,*† Scott Ames,† Jonathan S. Bromberg,† Graciela DeBoccardo,*† Nicholas DiPaola,§ Susan M. Lerner,† ʈ Anita Mehrotra,* Barbara T. Murphy,*† Tibor Nadasdy, Estela Paz-Artal,¶ Daniel R. Salomon,** Bernd Schro¨ppel,*† Vinita Sehgal,*† Ravi Sachidanandam,‡ and Peter S. Heeger*†

*Department of Medicine, †Recanati Miller Transplantation Institute, and ‡Department of Genetics and Genomics ʈ Sciences, Mount Sinai School of Medicine, New York, New York; §Histocompatibility Laboratory and Department of Pathology, Ohio State Medical Center, Columbus, Ohio; ¶Hospital 12 de Octubre, Madrid, Spain; and **The Scripps Research Institute, La Jolla, California

ABSTRACT Although T and alloimmunity contribute to transplant injury, autoimmunity directed at kidney- expressed, non-HLA antigens may also participate. Because the specificity, prevalence, and importance of antibodies to non-HLA antigens in late allograft injury are poorly characterized, we used a microarray to compare antibody repertoires in pre- and post-transplant sera from several cohorts of patients with and without transplant glomerulopathy. Transplantation routinely induced changes in antibody repertoires, but we did not identify any de novo non-HLA antibodies common to patients with transplant glomerulopathy. The screening studies identified three reactivities present before transplan- tation that persisted after transplant and strongly associated with transplant glomerulopathy. ELISA confirmed that reactivity against peroxisomal-trans-2-enoyl-coA-reductase strongly associated with the development of transplant glomerulopathy in independent validation sets. In addition to providing insight into effects of transplantation on non-HLA antibody repertoires, these results suggest that pretransplant serum antibodies to peroxisomal-trans-2-enoyl-coA-reductase may predict prognosis in kidney transplantation.

J Am Soc Nephrol 22: 1168–1178, 2011. doi: 10.1681/ASN.2010111183 LNCLRESEARCH CLINICAL

The immune response to a transplanted organ is among other antigens, contributes to post-trans- driven by T and B cell alloimmunity directed at do- plant graft injury.13,14 nor MHC,1,2 but evolving evidence from animal In addition to pre-existing autoimmunity, isch- models3–7 and transplant recipients8,9 indi- emia and tissue healing necessi- cates that autoreactivity also participates. When tated by transplant surgery, along with anti-donor transplantation is performed in patients with pri- alloimmunity, result in inflammation15–18 and ex- mary organ failure caused by immune-mediated destruction of normal tissue (e.g. type 1 diabetes), Received November 19, 2010. Accepted February 11, 2011. recurrent post-transplant autoimmunity can con- tribute to graft failure.10,11 Tissue damage accompa- Published online ahead of print. Publication date available at www.jasn.org. nying end-stage organ failure, regardless of etiol- Correspondence: Dr. Rajani Dinavahi, Mount Sinai School of ogy, could expose physiologically sequestered Medicine, Annenberg Building Box 1243, One Gustave L. Levy antigens to the immune system, breaking self-toler- Place, New York, NY 10029. Phone: 212-241-2976; Fax: 212-987- ance.12 Mounting associative evidence suggests that 0389; E-mail: [email protected] such pretransplant autoimmunity to myosin, Copyright © 2011 by the American Society of Nephrology

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posure of cryptic or sequestered self-antigens to the immune each array (see Concise Methods and Figure 1A). Using the system.19–21 These processes overcome self-tolerance, result- normalized data, we chose a stringent threshold to define a

ing in de novo pathogenic autoimmunity. One example of this positive result at a signal intensity of log210 (1024, dotted line phenomenon in is the development of de novo post- in Figure 1A, third panels), which reduced the false-positive transplant antibodies and reactivity to lung-expressed detection of negative control spots to essentially zero. At this type V collagen in lung transplant patients with bronchiolitis threshold, serum samples from normal volunteers and trans- obliterans.8 Other associations include anti-angiotensin II re- plant recipients reacted to 0.07 to 27% of antigens (Figure 1A, ceptors9 or anti-agrin22 antibodies in patients with kidney right panels). . As validation of our analytic methods, we tested com- The development of a protein microarray platform has per- mercially purchased pooled serum containing antibodies to mitted large-scale antibody screening to non-HLA antigens.23 Ro-52, La, Jo-1, TopoI, RNP, and Smith antigens for reac- Using such arrays, others showed that serum obtained from tivity to the array (Figure 1B). The positive control serum children with well-functioning kidney allografts contained an- reacted significantly to all six autoantigens. Signals for each tibodies to kidney-expressed antigens,24 some transplant re- reactivity were among the strongest detected (Ͼ98th per- cipients develop autoantibodies with acute kidney rejection centile of 9000 antigens on the array). Serum from two of and allograft loss,25 and autoantibodies are found in patients the normal volunteers reacted to none of the test antigens 26 Ͻ Յ with chronic humoral rejection. Whether antibodies to non- (all reactivities log2 10 with percentile ranks 87%). The HLA antigens are pathogenic and/or whether they can be used other two sera each reacted with only one of six control as biomarkers for transplant outcome remains unclear. autoantigens (Figure 1B). Herein, we used a protein microarray to screen non-HLA To test intra-assay variability, we performed three replicate antibody repertoires in kidney-transplant recipients with assays using a single serum sample (Figure 1C). These compar- transplant glomerulopathy (TG), a histopathologically distinct isons revealed Spearman tau correlations coefficients of 0.88 to manifestation of chronic allograft injury27,28 generally consid- 0.93, indicating approximately 10% intra-assay variability. ered to be immune-mediated.29,30 We compared non-HLA an- To assess how well the array detected quantitative differences tibody profiles of patients with TG to those with stable kidney in antibody concentration, we performed side-by-side assays on function after transplantation. Our results, using test and val- serially-diluted serum samples (Figure 1D). These experiments idation sets and confirmed with ELISA assays, indicate that (1) showed that median signal intensities (left panel) fell with the transplantation induces antibodies reactive to a wide assort- dilution, as did the number of positive reactivities (right panel). ment of non-HLA antigens, but these reactivities are unique to the individual transplant recipient; and (2) pretransplant de- Kidney Transplantation Induces Changes in Antibody tection of antibodies reactive to a specific kidney-expressed Repertoires Reactive to Non-HLA Antigens target, peroxisomal-trans-2-enoyl-coA-reductase (PECR), is Next we tested whether kidney transplantation alters antibody strongly associated with late development of TG. repertoires to non-HLA antigens. We obtained sera pretrans- plant and 12 months post-transplant from six stable kidney- transplant recipients (cohort 1; Table 1). Data from this ongo- RESULTS ing trial indicate that these patients had serum creatinine values Յ1.8 mg/dl at 12 months post-transplant, no acute re- Protein Array Measures Antibody Repertoires in jection episodes Ն Banff 1A grade, and no detectable serum Human Serum anti-HLA antibodies. We measured the non-HLA antibody We studied non-HLA antibody repertoires in kidney-trans- repertoires by array and compared pre- and post-transplant plant recipients by screening serum samples for reactivity to a results for each patient (representative result in Figure 2A and protein array containing approximately 9000 antigens. We ini- see Supplemental Figure 1). We found that Spearman tau co- tially performed experiments aimed at understanding assay efficients averaged 0.55 (0.43 to 0.64; Supplemental Figure 1), performance. Figure 1A (left panels) depicts representative raw indicating significant differences between pre- and post-trans- data derived from testing the serum of two individuals. The plant serum antibody repertoires for each recipient. Table 2

signal intensity (log2) and density of reactivities (percentage of quantifies, for each patient and group, the numbers of weak all target ) are shown on the X and Y axes, respectively. pretransplant reactivities, within the lowest 10th or 30th per- To compare samples from different patients performed at dif- centile, respectively) that became strongly positive post-trans- ferent times and with various array lots and to define a positive plant (Ն90th percentile). threshold, we exploited the fact that each array contains nega- When we compared the results of serum samples obtained 12 tive (buffer), and positive control (human IgG), spots. The months apart from normal volunteers (Figure 2A, left panel), we second and third panels in Figure 1A depict only these reactiv- found essentially no change in the repertoires (Spearman tau, ities to the positive (red, Ϸ300 spots) or negative controls 0.91). Neither did we observe any reactivities that commonly in- (black, Ϸ300 spots). We normalized the results among arrays creased from the lower percentile ranks pretransplant to above the so that the mean anti-IgG (positive) value was identical for positive threshold 12 months later (not shown).

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Figure 1. Protein microarray is a screening tool that reproducibly detects serums reactivities to non-HLA antigens. (A) Data normal- ization approach for two representative serum samples from two different patients. Raw signals are shown on the left. Unmanipulated positive control (red) and negative control (black) signals are shown in the next panel. The third panel depicts the signals for normalized positive and negative controls. The final panel on the right shows post normalization histogram for all reactivities. The vertical dotted line in the right two panels is drawn at log210. The numbers refer to percentages of reactivities above log210 threshold. (B) Assay validation with positive control sera. Normalized signal values are plotted for positive control serum (closed circles) and four healthy control serum samples (open circles). The horizontal dotted line is drawn at the significance level of log2 10. (C) Assay variability. Representative Spearman plots of a single serum sample tested on three separate arrays. Spearman plots comparing pairs of arrays with a mean tau of 0.90. The experiment was repeated twice with comparable results (data not shown). (D) Effects of serum dilution. The left panel shows box plots (median, 25th and 75th percentiles) for four different dilutions of the same serum sample tested on four separate arrays. The dashed box surrounds the dilution recommended by the manufacturer. Median reactivity for each array titrates down with serum dilution. The right panel shows signal histograms with numbers of significant reactivities Ͼ10 for each dilution.

Autoantibody Repertoires in Kidney Transplant Madrid Spain (cohort 2) and seven patients from the Ohio Recipients with TG State University (cohort 3). Clinical characteristics are sum- We next examined autoantibody profiles in patients with marized in Table 1 and Supplemental Tables 1 (A and B). biopsy proven TG, a well-defined pathologic entity com- Sera from four of 12 patients with TG contained donor- monly associated with serum-donor HLA-specific antibod- reactive antibodies by single-antigen testing. Serum samples ies.27–30 We evaluated pre- and post-transplant serum sam- were obtained a median of 4 years and 5.4 years post-trans- ples from five patients followed at Hospital 12 de Octubre in plant from the two cohorts, respectively.

Table 1. Patient characteristics Patient Cohort Median Time Since Donor-specific Median Serum Median Age in Median Proteinuria by (Number of Diagnosis Transplant in Years Anti-HLA Creatinine in Years (Range) Dipstick or g/24 h Patients) (Range) Antibodiesa mg/dl (Range) 1(n ϭ 6)b 54 (11 to 80) Stable kidney function 1 0/6 Not available 1.3 (1.0 to 1.8) 2(n ϭ 5) 44.5 (40 to 57) TG 4 (3 to 19) 1/5 2.4 g/24 h 2.2 (2 to 3.2) 3(n ϭ 7) 49.5 (37 to 72) TG 5.4 (1.6 to 13.8) 3/7 171 mg/24 h (n ϭ 3)c 2.7 (1.6 to 3.8) 4(n ϭ 9) 60 (33 to 74) TG 6 (3 to 22) 2/9 100 (dipstick) 2.2 (1 to 5) 5(n ϭ 8) 64 (39 to 77) Stable kidney function 6.5 (3 to 10) Not tested Neg (dipstick) 1.15 (0.8 to 1.8) aNumber of patients with anti-donor HLA antibody/total number of patients in the group. bThe data derive from an ongoing study (CTOT01, www.ctot.org), and the results are unvalidated. cNo available data on four patients.

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data with less stringent thresholds (Ͻ30th to Ͼ90th percentile) increased the numbers of reactivities for each patient but did not reveal any common targets (not shown). Together, the results suggest that TG is as- sociated with changes in non-HLA anti- body repertoires, but the induced altera- tions seem to be unique to the individual.

Pretransplant Autoantibody Repertoires in Kidney Transplant Recipients Who Develop TG Primary organ failure is commonly caused by and/or associated with autoreactivity di- rected at antigens expressed in the failing organ.31,32 Because pre-existing autoim- mune memory likely persists post-trans- plant, it could negatively affect transplant outcome. To address this, we reanalyzed our data and assessed whether pretrans- plant autoantibodies that persisted post- transplant were strongly associated with Figure 2. Transplantation induces new antibodies reactive to non-HLA antigens. (A) the development of TG. Representative Spearman plots depicting antigen reactivities in two serum samples We identified 65 reactivities with signal obtained 12 months apart from a normal volunteer (left panel) and pretransplant and intensities Ͼ90th percentile that were de- 12 months post-transplant from an individual transplant recipient with stable kidney tectable in both pre- and post-transplant function (cohort 1, middle panel) and an individual transplant recipient with TG (cohort 2, right panel). (B) Median spearman tau correlation coefficients for each group. The P serum samples of all five (cohort 2) patients values were determined by Mann-Whitney U test. with TG and 44 reactivities common to all stable patients (cohort 1; Figure 3). Thirty- When we compared pre- and post-transplant repertoires seven of 65 antigens common to the five TG patients (cohort 2) for each patient (Figure 2A and Supplemental Figure 2), we were unique (not found in a single stable patient serum; Figure found that Spearman tau coefficients ranged from 0.74 to 0.93. 3). When we compared these 37 reactivities with those com- Few (range, 3 to 46) pretransplant reactivities within the lowest mon to the seven other patients with TG (cohort 3, 73 individ- 10th percentile became strongly positive (Ͼ 90th percentile) in ual reactivities), we discovered three candidate biomarker re- the post-transplant sample (Tables 3 and 4). We found essen- activities common to all 12 TG patients and absent in all stable tially no overlap in the antigenic targets among the 12 patients kidney transplant recipients; Figure 3). These antigens (Table 5) are (Tables 3 and 4). Ingenuity analysis revealed that these proteins mapped to diverse pathways (not shown). Reanalyzing the Table 3. New reactivities detected after transplantation in Table 2. New antibody reactivities detected after patients with TG (cohort 2) transplantation in patients with stable renal function Number of Number of (cohort 1) Pretransplant <10th Pretransplant <30th Number of Number of Patient Percentile to Percentile to th th Pretransplant <10th Pretransplant <30th Posttransplant >90 Posttransplant >90 a Patient Percentile to Percentile to Percentile Percentile Posttransplant >90th Posttransplant >90th 15 27 Percentilea Percentile 24653 12 1833 3 24 1743 4 30 957 12 43 24Total 64 99 a 58 24Three reactivities are shared between two individual patients. BC016330.1- RAD51-associated protein 1 (RAD51AP1) and NM_032349.1-nudix 64 15 (nucleoside diphosphate-linked moiety X)-type motif 16-like 1 (NUDT16L1) Total 21 107 are shared between patients 2 and 5. BC014394.1-A. T hook DNA-binding aNo common reactivities are shared between any two patients. motif-containing protein 1 is shared between patients 2 and 3.

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Table 4. New reactivities detected after transplantation in the transplant waiting list) and found no difference among the patients with TG (cohort 3) groups (not shown). Number of Number of Representative anti-PECR ELISA results from one patient Pretransplant <10th Pretransplant <30th (Figure 4A, left panel) show that the reactivity titrates with Patient Percentile to Percentile to serum dilution (1:100 to 1:500) and antigen concentration. In Posttransplant >90th Posttransplant >90th patients with TG, reactivity to PECR was stronger than to a a Percentile Percentile control protein (cysteine- and glycine-rich protein 2 [CSRP2]; 13 5Figure 4A, right panel, and Supplemental Figure 3), indicating 23 3specificity. 32 8Post-transplant anti-PECR ELISA results (Figure 4B) for 42 4cohorts 2 and 3 with TG and eight post-transplant, time- 54 17matched stable transplant recipients (cohort 5; Table 1 and 64 8 Supplemental Table 1D) reveal stronger responses in each of 72 6 Ͻ ϭ Total 20 51 the TG cohorts (P 0.01 and P 0.01, respectively). aTwo antigen reactivities are shared between two individual patients. To strengthen our validation, we tested post-transplant se- NM_024068.1-oligonucleotide/oligosaccharide-binding fold containing 2B rum samples from an additional cohort of nine patients with (OBFC2B) is shared between patients 8 and 10 and BC021622.1- TG followed at Mount Sinai Hospital in New York (cohort 4; phosphoinositide-3-kinase, regulatory subunit 3 (p55, gamma) (PIK3R3) is shared between patients 3 and 4. Table 1 and Supplemental Table 1C). We observed stronger reactivity in the separate TG cohort 4 compared with those with stable kidney function (P ϭ 0.04), thus confirming the peptidyl-prolyl--A (PPIA or A), PECR, finding in a validation set (Figure 4B). Using a candidate and serine threonine kinase 6 (AURKA). They are intracellular threshold of 0.5 units (1:100 dilution), we calculated a positive proteins and are detectable within kidney tissue (Table 5). predictive value of 62% with a negative predictive value of PECR is a peroxisomal protein involved in fatty-acid synthesis 100%. At the 1:500 dilution and a lower candidate threshold of and has not been studied in transplantation.33 PPIA is a T cell– 0.4, the positive predictive value was 86%, and the negative signaling molecule that when bound to cyclosporine is inhib- predictive value was 100%. ited from interacting with .34 AURKA is required When we correlated the pathologic grade of TG with the for normal mitosis.35,36 strength of the anti-PECR response in the 21 patients with TG (cohorts 2 to 4), we did not observe a significant relationship Post- and Pretransplant Reactivity to PECR by ELISA (Supplemental Table 1). Nor did we find a relationship be- Strongly Associates with TG tween the presence of pre- or post-transplant anti-PECR im- To validate the data derived from the array, we tested pre- and munity and the cause of the primary kidney failure (Supple- post-transplant sera from each patient for reactivity to the mental Table 1 and Supplemental Figure 4). three candidate antigens, PECR, PPIA, and AURKA by ELISA. To test whether pretransplant anti-PECR antibodies are as- We measured total IgG levels in a subset of 28 patients (nine sociated with the development of late TG, we performed anti- with TG, eight with stable kidney function, and 11 patients on PECR ELISAs on stored sera obtained before transplantation from the patients who ultimately devel- oped this histology (cohorts 2 and 3). The ideal control would be pretransplant sera obtained from time-matched patients to the TG groups (approximately 6 years) with biopsies negative for TG, but such samples were not available (surveillance bi- opsies are not routinely obtained 5 to 10 years post-transplant). Instead we obtained and tested serum samples from a cohort of 37 wait-listed kidney transplant candidates as controls (Figure 4C). We reasoned that because TG occurs in approximately 20% of transplant recipients at 5 years,37 for pre- Figure 3. Microarray analysis identifies three putative biomarkers for transplant glomeru- lopathy. Shown is a Venn diagram depicting the overlapping reactivities in sera from transplant anti-PECR antibodies to be pre- patients with stable kidney function (Cohort 1, left oval) and from two different cohorts of dictive of TG, the strength of the pretrans- patients with TG (cohorts 2 and 3, middle dashed oval and right oval, respectively). plant anti-PECR responses should be Thirty-seven reactivities were found in cohort 2 but not detected in any of the cohort 1 significantly higher in those with docu- patients. Of those 37 reactivities, three were also detected in each of the patients in cohort 3. mented TG than in the randomly selected

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Table 5. Antigen reactivities specific to all cohort 2 and 3 patients with TG Known Tissue Expression Accession Number Protein Known Function Patterna BC005982.1 PPIA Also called cyclophilin A, PPIA is the molecular target of cyclosporine Kidney, vascular smooth muscle A involved in T cell activation. The cyclosporine-cyclophilin A cells, fibroblasts complex inhibits a /-dependent , macrophages53,56 calcineurin, the inhibition of which is thought to suppress organ rejection by halting the production of the pro-inflammatory molecules TNF␣ and -2. PPIs also catalyze the cis-trans isomerization of imidic peptide bonds in oligopeptides and accelerate the folding of proteins.55 BC006423.1 AURKA The -regulated kinase appears to be involved in Kidney, liver, but highest formation and/or stabilization at the spindle pole during expression in lymphoblasts segregation; Aurora A dysregulation has been and endothelial cells, colon associated with a high occurrence of cancer.35,36 adenocarcinoma56 NM018441.2 PECR PECR is a peroxisomal NADPH-specific trans-2-enoyl-CoA reductase CD4/CD8 T cells, B cells, that catalyzes the reduction of trans-2-enoyl-CoAs of varying chain dendritic cells, endothelial lengths from 6:1 to 16:1, having maximum activity with 10:1 cells, smooth muscle, kidney, CoA.33,57 liver, adipocytes56 aTissue expression patterns found by GenBank/GeneCards search and http://biogps.gnf.org; http://www.ncbi.nlm.nih.gov/geoprofiles (GEO ID# GDS899, GDS3397, GDS1453, GDS2534, and GDS1892). controls on the waiting list. We observed that the median anti- dependent fell in three patients posttransplant cohort 4 with PECR reactivity was higher in those destined to develop TG biopsy proven TG. Reactivity was titratable and specific be- (P Ͻ 0.01) compared with the 37 randomly-selected, wait- cause sera from those with anti-PECR immunity did not listed transplant candidates. At a proposed threshold of 0.5, we react to another tested antigen (Figure 4A), limiting the found eight of 12 (75%) patients who eventually developed TG likelihood that the responses represent polyreactive anti- to have anti-PECR immunity. At this same cutoff, eight of 37 bodies38 or low affinity autoantibodies found in normal in- (21%) wait-listed transplant candidates had anti-PECR reac- dividuals.39 tivity (Figure 4C; P ϭ 0.01 by ␹2). In addition to the post-transplant correlations, our analyses To assess whether transplantation affects the anti-PECR re- revealed that sera obtained pretransplant from patients who sponse, we compared pre- and post-transplant results for the ultimately developed TG reacted significantly more to PECR 12 patients with TG in cohorts 2 to 3 (Figure 4D). The median than pretransplant sera from a randomly selected cohort wait- values did not differ (P ϭ 0.43). The response increased in listed transplant candidates (Figure 4C), of whom only a mi- seven of 12 post-transplant. Two patients with negative values nority will develop TG.40 Acknowledging the small sample size pretransplant (Ͻ0.5) became positive post-transplant. Reac- and the need for larger prospective studies, our results raise the tivity fell in three patients post-transplant but did not fall be- possibility that both pre- and post-transplant antibodies to this low the 0.5 threshold. kidney-expressed, non-HLA antigen could be used as a bio- In contrast to the results for anti-PECR antibodies, when we marker for the development of TG. tested sera for anti-PPIA reactivity post-transplant, we did not PECR is a peroxisomal reductase involved in fatty acid observe a correlation between the strength of the response and elongation and to our knowledge has not been previously the presence of TG (Supplemental Figure 5). Nor did ELISAs reported as a target autoantigen in any disease state. Al- for AURKA performed on a subset of 12 patients with TG and though a pathogenic role for PECR in kidney disease is un- 17 patients without TG reveal differences between the groups known, when we performed a GEO database analysis of (not shown). array profiling studies to determine expression profiles for PECR (http://www.ncbi.nlm.nih.gov/geoprofiles), the analysis revealed strong expression in glomerular mesangial DISCUSSION cells and renal tubules (Table 5). Together with reports that intracellular fatty acid accumulation can be a feature of kid- Using a screening microarray, we showed that serum from ney disease,41–45 the glomerular location of PECR makes a two independent cohorts with TG contained IgG reactive to pathogenic role for anti-PECR antibodies plausible. Fatty three non-HLA antigens (Figure 3). ELISAs confirmed re- acid accumulation could aggravate lipid loading of glomer- activity to one of these, PECR, in the two cohorts (Figure 4). ular and tubular cells driven by increased endogenous syn- The post-transplant anti-PECR immunity was stronger thesis and that may contribute to progression of kidney fail- than in recipients with stable kidney function, and the find- ure.41,42 We speculate that upregulated expression and ing was confirmed using post-transplant serum from an in- release of PECR could occur as a consequence of primary

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kidney disease and if presented in a pro- inflammatory environment could result in B cell and/or T cell autoimmunity that could participate in the pathogenesis of allograft injury. Once induced, memory autoimmunity is long lived, high affinity, and rapidly en- gaged after another antigen exposure and resistant to immunosuppression.46,47 Au- toimmunity to islet antigens portends poor outcome after pancreas or islet transplan- tation, anti-cardiac myosin antibodies de- tectable in patients with heart failure persist after transplantation, and their presence increases the risk of severe acute rejec- tion.10–12 Our data indicate that anti-PECR immunity could function analogously in the context of kidney transplantation but will require further study. Whether antibodies reactive to PECR, an intracellular protein, participate in the pathogenesis of chronic injury or are non- participatory bystanders cannot be ascer- tained from our work. Studies by others re- vealed that apoptosis, induced by a variety of mechanisms, can reorient intracellular proteins such that they are expressed on cell surface blebs.48,49 In the context of lupus, this mechanism can result in concentrated and altered presentation of intracellular antigens to the immune system, stimulat- ing autoantibody formation, specifically anti-SSA/SSB antibodies that are patho- genic mediators of congenital heart block, thus providing a context through which Figure 4. Patients with TG specifically have serum antibodies reactive to PECR. such antibodies to intracellular antigens (A) Anti-PECR ELISA. (Left panel) Serum from one representative patient with TG could mediate injury.50 An alternative ex- was diluted 1:100 and 1:500 and tested in an anti-PECR ELISA in which plates were planation for the association between anti- coated with PECR (41 or 14 nM) or without PECR (0 nM). The mean values of PECR immunity and TG is the detected triplicate wells are shown. (Right panel) Sera (1:100 dilutions) from 28 individual IgG is a surrogate for anti-PECR T cell im- patients (20 with TG and eight with stable kidney function) were tested for reactivity munity that mediates the disease. to two PECR and a control protein, CSRP2 at 14 nM. (B) Anti-PECR reactivity TG has traditionally been described29,30 detected post-transplant. Individual ELISA results for anti-PECR reactivity tested at 1:100 dilution (left panels) or 1:500 dilution (right panels) in patients with late TG as an antibody-associated process that af- (cohorts 2, 3, and 4) and stable kidney function (cohort 5). The wells were coated fects 5% of renal transplant recipients per with 14 nM PECR. Arbitrary thresholds for positive values are shown by the dashed year, decreasing allograft half-life by lines (OD 0.5 at 1:100 dilution and 0.4 at 1:500 dilution). (C) Pretransplant anti- 50%.37,40 We and others have previously re- PECR ELISA. Pretransplant sera obtained from patients with late TG (cohorts 2 and ported that TG can occur in the absence of 3) and a randomly selected group of 37 patients on the transplant waiting list were donor-specific anti-HLA antibodies or C4d tested for anti-PECR reactivity (1:100 serum dilution, 14 nM PECR). The dashed staining,51–53 a result supported by the horizontal line represents the threshold of OD 0.5. Medians were compared by findings in this study in which only six of 21 Mann-Whitney U test. (D) Individual pre- and post-transplant anti-PECR reactivity patients with documented TG had detect- by ELISA. Each line represents the pre- and post-transplant serum reactivity for able donor-reactive antibodies. In contrast, PECR for the 12 patients from cohorts 2 and 3 (extracted from panel C). we found that serum from the majority of patients with this pathology contained an- tibodies reactive to PECR. Moreover, of

1174 Journal of the American Society of Nephrology J Am Soc Nephrol 22: 1168–1178, 2011 www.jasn.org CLINICAL RESEARCH seven transplants from our cohorts in which C4d staining was University transplant program (Columbus, OH). Donor-specific reported to be positive within the glomeruli, sera from all seven anti-HLA reactivity was detected in one of five patients by Luminex in contained anti-PECR antibodies and only three of seven con- the Spanish cohort and in three of seven patients in the Ohio State tained donor-specific antibody. cohort by GenProbe single-antigen testing (see Table 1 and Supple- We acknowledge that the pathology of kidney allografts mental Table 1, A through E) for detailed demographics. with TG, including those studied herein, also includes some We obtained post-transplant serum from nine patients at Mount elements of interstitial fibrosis and tubular atrophy. Although Sinai Medical Center with biopsy-proven (Banff 1997) TG (cohort 4) we do not have access to time-post-transplant–matched serum and from eight patients with stable kidney function (cohort 5) time samples from patients with biopsy proven Interstitial Fibrosis/ matched to cohort 4. Donor specific antibodies were determined by Tubular Atrophy (IF/TA) without TG as a control, the litera- Luminex single-antigen testing. ture54 supports the idea that allografts from the stable patients have some degree of IF/TA, yet our data indicate that these Protein Microarray Methods clinically stable patients do not have serum reactivity to PECR. We used the ProtoArray microarray platform versions 4.1 and 5.0 The microarray data indicate that transplantation alters an- (Invitrogen, Carlsbad, CA), which contain duplicate spots of ap- tibody repertoires (Figure 2), but we found essentially no over- proximately 9000 glutathione S--tagged human pro- lap among the patients with TG with regard to de novo non- teins printed on a nitrocellulose slide. The antigens include a se- HLA antibodies. The findings support results by another lection of intra- and extracellular proteins of known function, group suggesting that autoimmune profiles induced by trans- multiple proteins derived from open reading frames of unknown plantation are unique to the recipient.26 significance, and human immunoglobulins (see http://www. Our study highlights the strengths and limitations of large invitrogen.com/site/us/en/home/Products-and-Services/Applications/ throughput protein microarray screening for identifying Protein-Expression-and-Analysis/Biomarker-Discovery/Proto transplant associated biomarkers. Whereas the data indicate Array.html for details). The proteins expressed on the array were that such studies can be informative, high false-positive selected by the manufacturer and not chosen for their putative rates (only one of three antigens identified was informative) relationship to transplantation immunology. and cost of array experiments require careful selection of As per manufacturer instructions, the microarrays were stored at well-defined cohorts and novel analytical methods to en- Ϫ20°C and were equilibrated for 15 minutes at 4°C immediately be- hance signal to noise. Further data mining and reanalysis of fore use. After a 1-hour block in 50 mM Hepes (pH 7.5), 200 mM previously published studies in publicly available databases NaCl, 0.08% Triton X-100, 25% glycerol, 20 mM reduced glutathi- using such analytical approaches may provide additional one, 1ϫ Synthetic block, 1 mM dTT, (pH 7.5), deionized water valuable information. (www.Invitrogen.com), serum diluted 1:500 in wash buffer (1ϫ PBS, 0.1% Tween 20, 1ϫ Synthetic block, deionized water) was added and incubated for 90 minutes. The arrays were washed five times with CONCISE METHODS wash buffer at room temperature, followed by incubation with an AlexaFluor 647-conjugated anti-human IgG (1 ␮g/ml) (Invitrogen) for 90 minutes at 4 °C. After an additional five washes at room tem- Human Subjects and Sera perature, the arrays were dried and scanned with an Axon 4300A All serum samples were collected with informed consent and ethics (Axon, Toronto, CA). Scanned images from individual arrays were approval by all local institutional review boards. After collection, all of converted into digital signals, which were analyzed. The raw data files the serum samples were stored in aliquots at Ϫ80°C. are available upon request from the authors. We obtained and tested two different serum samples from four normal healthy controls 12 months apart. The median age of the Bioinformatics Analysis of Protein Microarray Results normal subjects was 37.5 years (age, 23 to 50). Although the manufacturer provides an analysis tool, Prospector An- We obtained pretransplant sera from 37 patients participating in alyzer, the limitations of the program are that data can only be com- the Clinical Trials in CTOT01 observational pared from arrays of the same lot and version. We therefore per- trial (www.ctot.org). In six of these patients, we also obtained serum formed an independent analysis using internally developed software samples 1 year post-transplant. Unvalidated clinical data from this on the R platform (http://www.r-project.org/). We determined strict ongoing trial indicated that these six patients had stable renal function signal thresholds, quality checked each array by examining true positive with serum creatinine Յ1.8 mg/dl at 1 year and no serum anti-HLA and true negative signal distributions, summarized protein expression antibodies at 1 year, and none experienced an episode of acute cellular from replicate spots, and normalized intensities using IgG and buffer rejection. These six stable patients are termed cohort 1. signals. Software and analysis algorithms are available upon request from We obtained pre- and post-transplant serum samples from two the authors. An overview of our analysis strategy follows. independent cohorts of patients diagnosed with biopsy proven TG All of the arrays contained 300ϩ buffer spots (no antigen) and 300 (Banff 1997 criteria). Samples from five patients (cohort 2) were ob- anti-IgG-positive controls. GPR (GenePix Result) files were gener- tained at the Hospital 12 de Octubre (Madrid, Spain), and samples ated and read, and the raw signal values were converted to log2 scale. from seven patients (cohort 3) were obtained from the Ohio State Noise channel values (between antigen spots) were discarded. Using

J Am Soc Nephrol 22: 1168–1178, 2011 Non-HLA Antibodies 1175 CLINICAL RESEARCH www.jasn.org only buffer and anti-IgG spot values, we estimated positive and true or X square. P values of Ͻ0.05 were considered statistically significant. negative cutoffs for each array. Modified median-shift normalization Statistical analysis was performed with the SPSS version 18.0 software was performed (the arrays were scaled so that the difference between package (SPSS, Inc., Chicago, IL). the median of the true negatives and the median of the true positives was identical for each array). The signal values for each array were shifted so that the mean anti-IgG (defined as positive) value was iden- ACKNOWLEDGMENTS tical for each array (Figure 1A). All of the reactivities were also as- th signed a percentile rank (0 to 100%). Signals above the 90 percentile The authors acknowledge the efforts of the Clinical Trials in Organ were considered to be significant, corresponding to a normalized sig- Transplantation investigators, including D. Hricik (Case Western, nal value of 1024 on arrays. This value was chosen because it mini- Cleveland, OH), E. Poggio, (Cleveland Clinic, Cleveland, OH), R. mized the false-positive rate. Although the stringent threshold ele- Formica (Yale University, New Haven, CT), K. Newell (Emory Uni- vated the false-negative rate, we chose to sacrifice potential loss of data versity, Atlanta, GA), P. Nickerson and D. Rush (University of Man- so as to limit the numbers of antigenic targets required for expensive itoba, Winnipeg, Canada), and J. Gobel (University of Cincinnati, validation studies. Rank shifts between pre- and post-transplant sam- Cincinnati, OH), for collecting patient samples that were used as part ples were then compared. Patients sharing a clinical phenotype (i.e. of the work and thank Denise Peace for her technical guidance. stable kidney function or TG) were analyzed on the same array ver- This work was supported by National Institutes of Health Grant sion to minimize version to version variability. Normalized signal U19AI063603 awarded to D.R.S. and an American Recovery and Re- values and percentile rank shifts were used as dual methods to strin- investment Act (ARRA) supplement to National Institutes of Health gently stratify differences between groups when the groups were Grant U01AI63594 awarded to P.S.H. tested on different versions of the array. When assessing signal reac- tivities between array versions, only normalized signal intensities/per- centile ranks were studied for antigens with similar amounts spotted DISCLOSURES between versions (within two-fold of each other) to minimize false None. positives.

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1178 Journal of the American Society of Nephrology J Am Soc Nephrol 22: 1168–1178, 2011 Supplemental Tables

Supplemental Table 1A: Characteristics of Kidney Transplant Recipients with Transplant Glomerulopathy (Cohort 2)

Proteinuri Serum Age in Primary a Patient* Years Since Creatinine Years Kidney Biopsy DSA(MFI)*** by Transplant in mg/dl Disease Dipstick or (Range) g/ 24 hr IFTAI, 1** 40 PKD Mild TGP 19 DR(702) 0.66 2.6 (C4d-) IFTAI, mild-moderate 2** 52 Unknown 4 None 3.2 2.01 TGP (C4d-) IFTAIII, IgA Mod TGP 3** 49 15 None 5.59 3.24 Nephropathy (C4d-)

IFTAI, mild-moderate 4** 40 Unknown 3 None 0.42 2.16 TGP (C4d+) IFTA mild, Alport’s TGPmild- 5 57 4 None 2.39 2.12 Syndrome moderate (C4d-) Median 44.5 4 None 2.4 2.2 *Biopsy information not available **Pretransplant anti-PECR reactivity above threshold OD 0.5 ***DSA determined by Luminex single antigen testing

1 Supplemental Table 1B: Characteristics of Kidney Transplant Recipients with Transplant Glomerulopathy (Cohort 3)

Years Primary Proteinuria Serum Age in Biopsy** Since Patient Kidney DSA(MFI)*** by Dipstick Creatinine Years Transpla Disease or g/24h**** mg/dl nt Medullary IFTA III, 1* 64 Cystic Mod TGP 5.2 A24(8312) 0.292g/24h 2.9 Disease (C4d+) IFTA II, Membranous DR53(11238) 2 29 Severe TGP 1.6 Data N/A 2.6 Nephropathy DQ8(9616) (C4d+) IFTAIII, 3* 37 FSGS severe TGP 3.3 None Data N/A 6.0 (C4d+) IFTA II, 4 53 Type II DM Mod TGP 5.4 None 0.054g/24h 1.8 (C4d-) IFTA III, 5 50 Type I DM SevereTGP 5.2 None Data N/A 5.7 (C4+) Congenital IFTA I, 6 37 Hypoplastic mod TGP 13.8 None 0.171g/24h 2.5 Kidney (C4d+) IFTA II, 7* 72 Unknown severe TGP 9.4 DQ3(7426) Data N/A 2.7 (C4d-) Median 49.5 5.4 2.7 *Pretransplant anti-PECR reactivity above threshold OD 0.5 **Pathologic diagnosis based on local readings by Banff ’97 criteria and rescored by Banff ’07 ***DSA determined by GenProbe single antigen detection method ****Data not available for 4 patients

2 Supplemental Table 1C: Characteristics of Kidney Transplant Recipients with Transplant Glomerulopathy (Cohort 4)

Primary Years Serum Age in Proteinuria Patient kidney Biopsy* since DSA(MFI) Creatinine Years by Dipstick disease transplant In mg/dl IFTA II

1 74 HTN Mild TGP, 3 100 2.4 None C4d(-) IFTA I None 2 70 HTN Mild TGP, 5 30 2.5

C4d(-) IFTA II None 3* 41 Amyloid Severe TGP 4 30 2.1

C4d(-) IFTA I A2(1463) 4 66 HTN Mild TGP, 8 30 2.2

C4d(-) IFTA II None 5 55 HTN Mod TGP, 22 >300 4.7

C4d(-) IFTA I None 6* 33 Unknown Mod TGP, 7 >300 1.2

C4d(-) IFTA I 7* 36 SLE Mod TGP, 12 None >300 5 C4d(-) IFTA III A1(4897) 8 60 HTN Mild TGP, 6 30 2.2

C4d(-) IFTA I Multiple anti- 9 66 HTN Mild TGP, 1 HLA >300 1 C4d(-) Reactivities**

Median 60 6 2.2

*Pathologic diagnosis based on local readings by Banff ’97 criteria and rescored by Banff ’07 criteria **>20 individual reactivities with MFI > 2000 were detected but donor HLA typing was not available (transplanted in another country)

3 Supplemental Table 1D: Characteristics of Stable Kidney Transplant Recipients (Cohort 5)

Primary Serum Age in Years since Proteinuria Patient kidney Creatinine Years transplant by dipstick disease (mg/dl) 1 63 HTN 10 Neg 2 2 39 HTN 4 Neg 1.3 3 75 Unknown 7 Neg 1.2 4 41 HTN 7 Neg 0.8 5 65 HTN 7 30 1.1 6 77 HTN 6 Trace 1.1 7 66 DM 6 Neg 1.6 8 53 PKD 3 Neg 1.0 Median 64 6.5 1.15

4 Supplemental Table 1E: Anti-PECR immunity and etiology of primary Renal Disease in Waitlisted Transplant Candidates

No Anti-PECR + anti-PECR HTN HTN HTN HTN HTN HTN HTN HTN DM DM DM DM DM Henoch Schonlein purpura DM Tubulointerstitial nephritis DM Unknown DM Unknown MPGN MPGN Chronic GN IgA nephropathy Membranous GN FSGS FSGS FSGS Aplastic/hypoplastic kidneys Wegener's PKD PKD Unknown Unknown Unknown Unknown Unknown Unknown *indicates pre-transplant anti-PECR reactivity above threshold 0.5

5

Supplemental Table 2: Summary of Significantly Changed Reactivities (<10th to <90th Percentile) in Patients with Stable Kidney Function at 12 Months

Cohort 1 Protein ID NM_031468.1 calneuron 1 (CALN1), transcript variant 1 glutathione transferase zeta 1 (maleylacetoacetate isomerase) NM_145870.1 (GSTZ1), transcript variant 1 NM_018127.4 elaC homolog 2 (E. coli) (ELAC2) NM_017799.2 open reading frame 101 (C14orf101) NM_007198.1 proline synthetase co-transcribed homolog (bacterial) (PROSC) ATP synthase, H+ transporting, mitochondrial F0 complex, subunit d NM_006356.1 (ATP5H), nuclear gene encoding mitochondrial protein, transcript variant 1 cytosolic iron-sulfur protein assembly 1 homolog (S. cerevisiae) NM_004804.1 (CIAO1) pantothenate kinase 2 (Hallervorden-Spatz syndrome) (PANK2), NM_153641.1 transcript variant 4 BC064945.1 SCY1-like 1 binding protein 1 (SCYL1BP1) BC062353.1 open reading frame 131 (C1orf131) BC053667.1 lectin, galactoside-binding, soluble, 3 (LGALS3) BC035256.1 adenylate kinase 7 (AK7) BC032008.1 mitochondrial ribosomal protein L50 (MRPL50) BC028212.1 phosphoinositide-3-kinase, regulatory subunit 5, p101 (PIK3R5) BC014264.2 chromosome 19 open reading frame 33 (C19orf33) BC012564.1 transmembrane and coiled-coil domains 3 (TMCO3) BC010850.1 HEAT repeat containing 2 (HEATR2) BC009961.1 potassium channel tetramerisation domain containing 17 (KCTD17) BC002369.1 polo-like kinase 1 (Drosophila) (PLK1) BC000208.1 OTU domain, aldehyde binding 2 (OTUB2)

6 Supplemental Table 3: Summary of significantly changed reactivities(<10th to >90th percentile) in patients with late Transplant Glomerulopathy

Cohort 2 Gene ID Protein Gene ID Protein PREDICTED: Homo sapiens XM_117451.4 hypothetical LOC402617 BC012289.1 KIAA0515 (KIAA0515) (LOC402617) NM_198538.1 Suprabasin NM_003211.1 thymine-DNA glycosylase (TDG) coiled-coil domain containing 84 NM_198489.1 NM_003192.1 folding C (TBCC) (CCDC84) NM_152597.3 Fibrous sheath-interacting protein 1 NM_003165.1 Syntaxin-binding protein 1 open reading mitogen-activated protein kinase 9 NM_152460.2 NM_002752 frame 77 (C17orf77) (MAPK9), transcript variant JNK2-a2 mitogen-activated protein kinase NM_145109.1 kinase 3 (MAP2K3), transcript NM_002315.1 Rhombotin-1 variant B nudix (nucleoside diphosphate NM_001005360. NM_032349.1 linked moiety X)-type motif 16-like 1 Dynamin-2 1 (NUDT16L1) nudix (nucleoside diphosphate NM_032349.1 linked moiety X)-type motif 16-like 1 BC036184.1 Tropomodulin-2 (NUDT16L1) phospholipase A2, group IVD NM_032017.1 serine/threonine kinase 40 (STK40) NM_178034.1 (cytosolic) (PLA2G4D) ADP-ribosylation factor GTPase Intraflagellar transport protein 81 NM_031473.1 NM_175609.1 activating protein 1 (ARFGAP1), homolog transcript variant 2 gasdermin domain containing 1 NM_024736.2 NM_173547.2 tripartite motif-containing 65 (TRIM65) (GSDMDC1) open reading frame NM_023080.1 NM_005595.1 nuclear factor I/A (NFIA) 33 (C8orf33) LINE-1 type transposase domain- NM_019079.2 BC057760.1 MORN repeat-containing protein 3 containing protein 1 NFKB inhibitor interacting Ras-like immunoglobulin kappa constant NM_017595.2 BC056256.1 2 (NKIRAS2), transcript variant 2 (IGKC) survival of motor neuron 2, nuclear receptor subfamily 1, group NM_017411.2 centromeric (SMN2), transcript BC056148.1 D, member 1 (NR1D1) variant d breast cancer EGF-like repeats and discoidin I-like NM_015399.1 suppressor 1 (BRMS1), transcript BC053656.1 domains 3 (EDIL3) variant 1 ARFGAP with coiled-coil, ANK CREB regulated NM_014716.2 repeat and PH domain-containing BC053562.1 coactivator 2 (CRTC2) protein 1 chromosome 13 open reading frame NM_014582.1 odorant binding protein 2A (OBP2A) BC051911.1 24 (C13orf24) NM_006790.1 myotilin (MYOT) BC040020.2 finger protein 280B (SUHW2) RAD51 associated protein 1 cytoplasmic element NM_006479.2 BC035348.1 (RAD51AP1) binding protein 1 (CPEB1) serpin peptidase inhibitor, clade I immunoglobulin kappa variable 1-5 NM_006217.2 BC030814.1 (pancpin), member 2 (SERPINI2) (IGKV1-5) Isocitrate dehydrogenase [NADP] 4D interacting NM_005896.2 BC025406.1 cytoplasmic protein (myomegalin) (PDE4DIP)

7 Dual specificity tyrosine-

NM_004714.1 phosphorylation-regulated kinase BC024254.1 abl-interactor 1 (ABI1) 1B NM_003318.3 TTK protein kinase (TTK) BC022996.1 SH3 domain-binding protein 2 transcription factor AP-2 beta RAD51 associated protein 1 NM_003221.1 (activating enhancer binding protein BC016330.1 (RAD51AP1) 2 beta) (TFAP2B) RAD51 associated protein 1 BC011454.1 like 2 (AMOTL2) BC016330.1 (RAD51AP1) nei endonuclease VIII-like 1 (E. coli) N-methylpurine-DNA glycosylase BC010876.1 BC014991.1 (NEIL1) (MPG) Metastasis-associated protein BC006177.1 BC014539.1 secretogranin III (SCG3) MTA1 Fanconi anemia, complementation A.T hook DNA-binding motif- BC004277.1 BC014394.1 group I (FANCI) containing protein 1 Branched-chain-amino-acid A.T hook DNA-binding motif- BC004243.1 BC014394.1 aminotransferase, mitochondrial containing protein 1 solute carrier family 7 (cationic amino transcription factor 19 (SC1) BC002493.1 BC012895.1 acid transporter, y+ system), member (TCF19) 1 (SLC7A1) BC012876.1 Ig lambda chain C regions

Cohort 3 Gene ID Protein NM_201262.1 DnaJ (Hsp40) homolog, subfamily C, member 12 (DNAJC12), transcript variant 2 NM_173194.2 Kv channel interacting protein 2 (KCNIP2), transcript variant 5 NM_024068.1 oligonucleotide/oligosaccharide-binding fold containing 2B (OBFC2B) NM_020299.2 aldo-keto reductase family 1, member B10 (aldose reductase) (AKR1B10) NM_018664.1 Jun dimerization protein p21SNFT (SNFT) NM_016208.1 vacuolar protein sorting 28 homolog (S. cerevisiae) (VPS28), transcript variant 1 NM_016127.4 transmembrane protein 66 (TMEM66) NM_015143.1 Methionine aminopeptidase 1 NM_014038.1 basic leucine zipper and W2 domains 2 (BZW2) NM_005406.1 Rho-associated, coiled-coil containing protein kinase 1 (ROCK1) NM_001551.1 immunoglobulin (CD79A) binding protein 1 (IGBP1) NM_001070.1 tubulin, gamma 1 (TUBG1) BC093990.1 Sin3 histone deacetylase corepressor complex component SDS3 BC041157.1 thromboxane A synthase 1 (platelet, cytochrome P450, family 5, subfamily A) (TBXAS1) BC034488.2 ATP-binding cassette, sub-family F (GCN20), member 1 (ABCF1) BC021622.1 phosphoinositide-3-kinase, regulatory subunit 3 (p55, gamma) (PIK3R3) BC014928.1 MYC-induced nuclear antigen BC000879.1 kynureninase (L-kynurenine ) (KYNU)

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