Non-HLA Antibodies to Immunogenic Epitopes Predict the ... · CLINICAL RESEARCH Non-HLA Antibodies to Immunogenic Epitopes Predict the Evolution of Chronic Renal Allograft Injury

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Non-HLA Antibodies to Immunogenic Epitopes Predictthe Evolution of Chronic Renal Allograft Injury

Tara K. Sigdel, Li Li, Tim Q. Tran, Purvesh Khatri, Maarten Naesens, Poonam Sansanwal,Hong Dai, Szu-chuan Hsieh, and Minnie M. Sarwal

Department of Pediatrics, Stanford University School of Medicine, Stanford, California

ABSTRACTChronic allograft injury (CAI) results from a humoral response to mismatches in immunogenic epitopesbetween the donor and recipient. Although alloantibodies against HLA antigens contribute to thepathogenesis of CAI, alloantibodies against non-HLA antigens likely contribute as well. Here, we used high-density protein arrays to identify non-HLA antibodies in CAI and subsequently validated a subset in a cohortof 172 serum samples collected serially post-transplantation. There were 38 de novo non-HLA antibodiesthat significantly associated with the development of CAI (P,0.01) on protocol post-transplant biopsies,with enrichment of their corresponding antigens in the renal cortex. Baseline levels of preformed antibodiesto MIG (also called CXCL9), ITAC (also called CXCL11), IFN-g, and glial-derived neurotrophic factor posi-tively correlated with histologic injury at 24 months. Measuring levels of these four antibodies could helpclinicians predict the development of CAI with .80% sensitivity and 100% specificity. In conclusion, pre-transplant serum levels of a defined panel of alloantibodies targeting non-HLA immunogenic antigensassociate with histologic CAI in the post-transplant period. Validation in a larger, prospective transplantcohort may lead to a noninvasive method to predict and monitor for CAI.

J Am Soc Nephrol 23: 750–763, 2012. doi: 10.1681/ASN.2011060596

Despite improvements in short-term graft survivalover the past decades,1 chronic allograft injury(CAI) remains a major challenge in renal and othersolid organ transplants. In addition, the rate of pro-gression of CAI remained relatively unabated overthe last decade, with limited improvements in ex-tending graft survival.2,3 CAI in the graft is the pri-mary reason for accelerated graft loss,4 categorizedby progressive interstitial fibrosis (IF) and tubularatrophy (TA) of the parenchyma,5 that is also asso-ciated with glomerulopathy, fibrointimal hyperpla-sia of arteries, and arteriolar hyalinosis.6 This injuryis believed to be mostly a humoral injury responseto mismatched immunogenic epitopes between thedonor and recipient,7 with current understandingmostly focused on HLA antigens.8 Despite improvedunderstanding of the assessment and monitoring forHLA mismatched epitopes,8 the pathogenicity ofdonor-specific anti-HLA antibodies on CAI remainselusive.9 This is shownwith complete HLAmatchedtransplants exhibiting finite survival due to progres-sive CAI,10 and not infrequently, CAI observed in

HLAmismatched grafts without demonstrable anti-bodies to donor-specific HLA antigens.7 These find-ings strongly suggest that additional pathogenicantibodies drive the humoral axis of injury in CAI,9,11

and may be the final common outcome. The acti-vation or transition of these non-HLA antibodiestoward pathogenicity is likely through the underlyingtriggers of acute rejection, hypoperfusion, ischemiareperfusion, calcineurin toxicity, infection, and re-current diseases.12 Currently, there is no means topredict which transplant patients will develop accel-erated CAI in the allograft. Histologic diagnosis ofCAI is the current gold standard for diagnosing

Received June 21, 2011. Accepted October 28, 2011.

Published online ahead of print. Publication date available atwww.jasn.org.

Correspondence: Dr. Minnie M. Sarwal, Department of Pediat-rics, Stanford University, G306, 300 Pasteur Drive, Stanford, CA94305-5208. Email: [email protected]

Copyright © 2012 by the American Society of Nephrology

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CAI; however, this only detects advanced, established, and oftenirreversible injury. The renal biopsy is also an invasive procedurethat suffers from sampling heterogeneity, is associated with var-ious complications,13 and provides a limited prognostic value.Identification of informative, minimally invasive biomarkers iscritically needed to monitor and predict CAI, and remains acritically important unmet need in solid organ transplantation.

The antibody axis has been implicated in different diseaseconditions, and profiling and measuring the level of IgG an-tibodies against thousands of defined human proteins to iden-tify antibodies against non-HLA antigens have been previouslyattempted in autoimmune diseases14 and CKD.15 In an at-tempt to evaluate clinically relevant de novo, renal-specific,non-HLA antibody responses, we utilized protein arrays andcustomized informatics for studying non-HLA antibody re-sponses in stable grafts16,17 and acute rejection11,18 to inter-rogate previously unidentified non-HLA antibody CAI. Toinvestigate the non-HLA pathogenicity in CAI, we excludedpatients with signs of acute rejection, purely focusing onnon-HLA antibody responses in the absence of any intervalacute rejection episodes. From this cohort, we then excludedpediatric patients with interval episodes of infection, delayedgraft function, or body surface area ,0.75 m2,19 thuscreating a homogenous set of patients without any major con-founders to CAI. This resulted in the removal of 47 patientswith interval acute rejection episodes, 3 patients in intervalinfectious episodes, 3 patients with delayed graft function, aswell as 4 recipients with body surface area ,0.75 m2. Fromthese remaining patients, we carefully selected a subset of 20patients (n=10 CAI versus n=10 without CAI) as the learningset and collected surveillance samples of sera matched to di-agnostic biopsy at 0, 6, and 24 months post-transplantationfrom each patient, thus analyzing 60 serum samples for diag-nosis and prediction of CAI. The increased presence of signif-icant non-HLA antibodies was analyzed for their correlationwith injury progression post-transplant. Finally, from thelarger confounder-controlled cohort, we validated the mostsignificant and relevant antibodies (from discovery) by usingELISAs on 112 unique and independent sera samples from 68patients (Figure 1).

RESULTS

Identification of CAI-Specific Novel Non-HLAAntibodiesCompared with the non-HLA antibody levels before trans-plantation, there was a significant immune responsepost-transplantwith thedevelopmentofCAI.ByusingM-statistics ofthe Prospector Analyzer with the robust linear normalizationmethod published elsewhere,20 we identified a total of 231non-HLA antibodies with statistically significant P values#0.05.Among the 231 changed antibodies, 111 non-HLA antibodiesincreased significantly in the CAI group (P#0.05) (Figure 2Aand Supplemental Table 1). On the basis of a time course

analysis of the most statistically significant (P#0.05) non-HLAantibodies, the CAI-specific non-HLA antibody could be categor-ically divided into an non-HLA showing significant detection ei-ther early (,6months) or late (.6months) post-transplantation.The early responsewas observed to be against non-HLAproteinsinvolved in pathways such as cell-mediated immune response,connective tissue development and function, and EGF signaling.Some of these selected antigens are shown in Table 1. The lateresponding non-HLA proteins were noted to immunologicallyreactive proteins involved in pathways such as cell death, cell-to-cell signaling and interaction, and cellular movement (Figure 2Band Supplemental Figure 1).

We analyzed the antibody response for 12 HLA antigens,including 2HLAclass Imolecules (HLA-B andHLA-C) and 10HLA class II molecules (HLA-DOA, HLA-DOB, HLA-DPA1,HLA-DPB1,HLA-DQA1,HLA-DQB1,HLA-DRA,HLA-DRB1,HLA-DRB3, and HLA-DRB5) in the CAI and non-CAI groups.The signal intensity of antibody detection to these targets is verylow (average ,500 RFU signal intensity). Thus, it seems thatHLA antibody levelsmay be less influenced in the course of CAI,in the absence of interval acute rejection.

Cross-Mapping CAI-Specific Non-HLA Antibodies toExpression of the Target Proteins in SubcellularCompartments of the KidneyTo triage the selection of non-HLA antibodies to further pursue,we chose to assign physiologic and potentially pathologicrelevance to the significant CAI-specific antibodies, by selectingantibodies with reactivities to kidney-specific antigens. Theassumption is that these de novo antibody responses after kidneytransplantation are more likely against the antigens in the newlytransplanted kidney. To enable this analysis, we performed cross-mapping of kidney and kidney-compartment–specific genes ob-tained frommicrodissected compartments of normal kidney byprofiling these tissues on cDNA microarrays with protoarrayprotein targets, using our published approach of integrated anti-biomics.18,21,22 This analysis revealed that there was an enrich-ment for antigens expressed in the renal cortex (P=0.029). Aspreviously shown, the renal pelvis antigens are highly immuno-genic, and enrichment for pelvis-specific antigens was alsonoted. These antigen lists are shown in Table 2.

CAI-Specific Antibodies Track Injury ProgressionWe took the antibodies that were increased with CAI andperformed Spearman correlation analyses with the ChronicAllograft Damage Index (CADI) and IF/TA scores of eachcorresponding renal biopsy. A total of 34 antibodies and 41antibodies demonstrated a positive correlation with CADIscore (overall P,0.04) and IF/TA (overall P,0.04), respec-tively. The top 20 antibodies are listed in Table 3. Pathwayanalysis suggested that these antigens are involved in cellularmovement, antigen presentation, cell-to-cell signaling and in-teraction, and cell death (P,0.002). Scatter plots for the sixmost significant antibodies (IFNG [IFN-g], MIG, CSNK2A2,CCL21, glial cell-derived neurotrophic factor [GDNF], and

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ITAC) and their correlation with the CADI score are presentedin Figure 3.

Predicting Injury Progression after TransplantationAs shown by our group in a previous publication,15 chronicrenal injury and end stage renal failure result in uncovering ofkidney-specific epitopes, mostly in the renal cortex and therenal pelvis, and the immunologic recognition of these newlydiscovered non-HLA antigens with humoral responses in theform of non-HLA antibodies, specific to chronic renal injury.To evaluate if this repertoire of preformed non-HLA antibod-ies specific to chronic renal failure could predict the subse-quent development of CAI after kidney transplantation, thelevel of these non-HLA antibodies was evaluated at the baseline(day 0 sera) of each patient. Spearman correlation analysis wasperformed to identify the specificities or levels with the pro-gression of CAI on the biopsy performed at 6 months and 24months after transplantation. Interestingly, baseline levels ofthese preformed antibodies to MIG, ITAC, IFNG, GABPA, andGDNF positively correlated (P,0.05) with CADI score at6 months, and baseline levels of four of these five antibodies(MIG, ITAC, IFNG, GDNF), as well as two additional antibod-ies to IL-8 and CCL21, all positively correlated (P=0.04) withCADI score at 24 months (Table 4). As expected for this selec-tion of antibodies, antibody levels at 6 months post-transplantfor IL-8,MIG, IL21, CCL19, LRRK2, CCL21, GDNF, and IFNGalso correlated with CAI at 24 months post-transplantation,suggesting that these antibody levels could also be tracked forprogression of CAI in both the pretransplant period

(preformed) and the post-transplant period(de novo) (Figure 4, A–D) (Table 4).

Univariate and multivariate logistic re-gressions were performed to examine therelationship between the baseline signalintensities of each of the preformed fourantibodies (MIG, ITAC, GDNF, and IFNG)andCADI scores from the protocol biopsiesperformed in these samepatients at 6 and24months post-transplantation. A CADIscore of $3 was used as a cutoff to defineeither severe ($3 CADI score) or mild (,3CADI score) histologic CAI. The receiveroperating characteristic (ROC) curves foreach of these antibodies to predict the de-velopment of CAI are shown for the6-month protocol biopsy (Figure 4E) andthe 24-month protocol biopsy (Figure 4F).When a regression model was built by uni-variate analysis, detection of baseline levelsof preformed antibody to MIG at levels.200 RFU had a significant associationwith the patient developing CAI on theprotocol biopsy at both 6 months (oddsratio, 1.04; 95% confidence limit, 1.003–1.078; P=0.034), and at 24 months post-

transplantation (odds ratio, 1.023; 95% confidence limit,1.001–1.045; P=0.0375). Patients who never developed CAIhad baseline antibody levels to MIG of ,50 RFU.

Validation of Selected Potential Antibody BiomarkersELISAs were developed and optimized to demonstrate thatdiscovery of target non-HLA antibodies by protoarray could bevalidated by ELISA. ELISAs were set up, customized, andperformed for some selected (and significant) targets in whichthe full-length proteins could be commercially obtained fromstock supplies for setting up the reverse ELISAs for antibodymeasurements. These assays were done for MIG, ITAC,CSNK2A2, and PDGFRA. A significant increase in the antibodylevelswere confirmed inCAIby reverse ELISA for all four targets:MIG (P,0.02), ITAC (P,0.014), CSNK2A2 (P,0.0002), andPDGFRA (P,0.0001) (Figure 5, A–D). For further validation,seven independent patients were selected, whowere not used fordiscovery by protoarrays, in whom serial sera andmatched pro-tocol biopsies were available and who had a CAI grade of at least.3 on both the 6-month and the 24-month protocol biopsies.Three of these targets were confirmed by our customized reverseELISA to also show significant increases in this longitudinalanalysis. Antibody levels for patients with CAI at 24 monthswere significantly higher in 24-month sera versus 6-monthsera for CSNK2A2 (P=0.05), ITAC (P=0.05), and MIG(P=0.005) (Figure 5, E and F). In addition, there was a strongcorrelation of two of these antibody levels with CADI scores onthe 24-month protocol biopsies (MIG: r=0.62, P=0.05; ITAC:r=0.62, P=0.05).

Figure 1. Study schematic. A novel approach is used to identify novel non-HLAantibodies through an integrative approach of analyzing sera samples with matchedbiopsies on protein microarray for the discovery step. The validation step is per-formed after filtering the data for highly correlated antibodies for renal graft injury.The highly correlated antibodies are then validated by indirect ELISAs on an in-dependent set of patients for cross-sectional and longitudinal analyses. nCAI, non-CAI; STA, stable.

752 Journal of the American Society of Nephrology J Am Soc Nephrol 23: 750–763, 2012


DISCUSSION

CAI is related to a humoral response driven by alloantibodiesagainst HLA antigens, with recent data also supporting a rolefor immunogenic non-HLA renal antigens. An understandingof the specificities and correlative levels of these antibodies canprovide an understanding of molecular injury triggers in CAIand ameans to noninvasively monitor the development of thisinjury. Despite the contribution of newly available immuno-suppressive drugs in the short-term survival of the trans-planted kidney,3 CAI progresses relentlessly post-transplant,accelerating the risk for graft loss. There is a lack of reliableand robust noninvasive biomarkers to track the health status ofthe transplanted organ, without the requirement of serial pro-tocol biopsies. Elaborating injury mechanisms and developingpredictive, noninvasive monitoring methods for CAI is an im-portant unmet clinical need.2,23 The process of biologic tissueinjury from events such as exposure to calcineurin inhibitoragents, from graft ischemia, or from recipient hypertension,likely results in the alteration of the levels, exposure, or

targeting for various proteins/antigens in the renal allograft.These altered antigens mount specific antibody responses.The ability to recognize these relevant antigens, to measurethese specific antibody levels in the circulation, and to correlatethese levels with histologic CAI in the allograft itself is a power-ful approach to identify noninvasive, clinically relevant sero-logical biomarkers for detecting and predicting CAI. Our initialstudies strongly suggested a pathogenic role for non-HLA anti-bodies after transplantation.11,16,18 From gene expression anal-yses, we reported an increased level of Ig gene transcripts as afunction graft injury.24We thus hypothesized that accumulatedorgan injury in the form of CAI could be associated with aspecific set of circulating non-HLA antibodies that can be de-tected, quantified, and used to follow chronic graft injury.

We undertook a carefully designed study of highly selectedpatients with established histologic CAI, with available serialsera and matched protocol biopsies, and with no confoundinginfluences of delayed graft function, acute rejection, or in-fection on the evolution of chronic injury. Unbiased discoveryof a panel of correlative non-HLA antibodies with CAI was

Figure 2. A cross-sectional analysis of sera samples taken from patients with matched biopsies showing either the presence (n=20) orabsence of CAI (n=20). (A) A volcano plot demonstrates a significant shift in antibody responses CAI. A total of 111 antibodies (Ab) aresignificantly increased (in red dots) in sera collected from renal transplant patients with CAI (n=20) compared with patients without CAI(n=20) (P#0.05), and 40 antibodies are increased in CAI (P#0.01). (B) The dynamics of change of antibody levels of most significantantibodies over the period of 24 months are shown. Ab, antibody.



evaluated from pretransplant and post-transplant sera in thesepatients. Selection of antibody targets was biased for kidneyexpressed antigens, and customized reverse ELISAs were gen-erated to validate the findings in independent sera samplesfrom an independent group of patients with CAI. These resultsdemonstrated, verified, and validated a small panel of newlyidentified non-HLA antibodies that correlate not only withhistologic CAI in thematched sera sample, but that also havecorrelative levels post-transplantation with progressive

CAI and, most importantly, can predict the future de-velopment of CAI by pretransplant sampling for the sameantibody panel.

Irrespective of the initial trigger, it is believed that the path-ophysiology of CAI involves endothelial injury leading to anincreased expression of cytokines and several other immune-related genes, resulting in proliferative processes, remodeling,and scarring of the graft. The increased IgG antibody level ofcytokines IFNG,MIG, and ITAC strengthens the belief that the

Table 1. Early and late responding non-HLA antibodies in CAI

Serial No. Gene Symbol Protein Name P Value

Early response (,6 mo post-transplant)1 CSNK2A2 Casein kinase 2, a2 0.012 CSNK2A1 Casein kinase 2, a1 0.023 KLK6 Kallikrein-related peptidase 6 0.014 PPID Peptidylprolyl isomerase D 0.005 CCDC55 Coiled-coil domain containing 55 0.036 NEK3 NIMA (never in mitosis gene a)–related kinase 3 0.027 CSNK1G3 Casein kinase 1, g3 0.0028 CCL21/6CKINE Chemokine (C-C motif) ligand 21 0.009 BIN1 Bridging integrator 1 0.05

10 MAPRE2 Microtubule-associated protein, RP/EB family, member 2 0.0011 SGK2 Serum/glucocorticoid regulated kinase 2, transcript variant 1 0.0313 GYG2 Glycogenin 2 0.0114 MEF2D Myocyte enhancer factor 2D 0.000615 EGFR L861Q EGF receptor (erythroblastic leukemia viral [v-erb-b]

oncogene homolog, avian), transcript variant 10.002

16 EGFR EGF receptor (erythroblastic leukemiaviral [v-erb-b] oncogene homolog, avian);see catalog number for detailed informationon wild-type or point mutant status

0.00

17 Jo-1/HARS Histidyl-rRNA synthetase (Jo-1) 0.01Late response (.6 mo post-transplant)18 MIG Chemokine (C-X-C motif) ligand 919 GDNF Glial cell-derived neurotrophic factor 0.000120 CSNK1G1 Casein kinase 1, g1 0.0521 BHMT2 Betaine-homocysteine methyltransferase 2 0.0022 PKN1 Serine/threonine-protein kinase N1 0.0023 ATXN3 Ataxin-3 0.0124 MARK4 MAP/microtubule affinity-regulating kinase 4 0.02

Table 2. Compartment-specific enrichment of CAI-specific antibodies cross-mapping of kidney and kidneycompartment–specific genes in between cDNA microarraya

Kidney/Compartment Kidney-Specific Targets CAI Specific (20 np versus 20 P) (P,0.05) P Value

Kidney 261 3 (ACY1, BIN1, CSNK2A1) 0.10Glomerulus 245 7 (FLT1, FLT4, MIG, PDGFRB, PRKCE, KLK6, BHMT2) 0.11Inner cortex 267 3 (ACY1, BHMT2, CLK4) 0.03Outer cortex 433 8 (ACY1, PRKCE, PRKCZ, KLK6, VDR,

SNF1LK2, BHMT2, CLK4)0.13

Outer medulla 42 0 0.41Inner medulla 11 0 0.79Papillary tip 222 4 (PDGFRA, PRKCB1, RARB, AFAP1l2)Pelvis 635 6 (IFNG, JAK3, CCL19, CCL21, WEE1, NDE1) 0.001

aThe cross-mapping was performed using previously published data and methods (18,21,22).



transplanted kidney is under continuous immunologic attack.Similar results were also shown by gene expression analysis onCAI protocol biopsies from the samepatient group.24 IFNG is atype II IFN that is encoded by the IFNG gene25 and is exten-sively produced by a wide range of immune-related cells suchas CD4+ T helper cell type 1 lymphocytes, CD8+ cytotoxiclymphocytes, natural killer cells, B cells, natural killer T cells,and antigen presenting cells.26–30 IFN-g gene polymorphism+874 T/A (rs2430561) has been suggested to be associatedwith AR31,32 and activated T lymphocytes in alloimmune in-jury are a major source of IFNG expression, regulated by IL-12and IL-18.29,33 IFNG is critical in trafficking of specificimmune cells to sites of inflammation by upregulating ex-pression of adhesion molecules and chemokines.34 In thiscontext, our observation of a significant increase in the anti-body level againstMIG and ITAC is important. BothMIG andITAC are chemokine proteins that also serve as chemoattrac-tants for leukocytes, monocytes, neutrophils, and other

mononuclear cells to the site of tissue damage.35 Upregula-tion of these chemokine proteins has been demonstrated tobe correlated with T lymphocyte recruitment during acuteand chronic rejection events. In addition, pretransplant se-rum levels of MIG and CXCL10 have been reported to beassociated with graft failure,36,37 and recently our group hasreported that there are high levels of circulating MIG proteinin the serum of kidney and heart transplant patients at thetime of acute rejection.38

We also observed an increase in the IgG antibodies of anumber of novel antigens that have not been previously reportedto be relevant in organ transplantation. Some of these continueto support the activation of the immune axis as a critical triggerfor CAI, such as antibodies to the Jo-1 antigen, also known ashistidyl-tRNA synthetase, and are responsible for the synthesis ofhistidyl-transfer RNAand themigration of activatedmonocytes,immature dendritic cells, and activated lymphocytes.39 An in-teresting antibody in CAI is the GDNF, which is involved in

Figure 3. CAI-specific antibodies correlate with the severity of CAI at the time of sampling. (Upper panel) IgG antibody level of sixantigens: (A) IFNG, (B) MIG (CXCL9), (C) CSNK2A2, (D) CCL21, (E) GDNF, and (F) ITAC (CXCL11) are shown to be correlated with chronicinjury in terms of CADI score. (Lower panel) Evidence of the presence of four of the corresponding antigens of CAI-specific antibodies:(A) IFNG, (B) ITAC (CXCL11), (C) GDNF, and (D) PDGFRA.



kidney development. Signaling by the secreted protein GDNFthrough the RETreceptor tyrosine kinase and the GDNF familyreceptor a1, a GDNF co-receptor, are involved in kidney devel-opment,40 specifically in metanephros41 and ureteric bud devel-opment.42 GDNF antibodies are increased in CAI and correlatewithhistologicCAI (Figure3), andbaseline/pretransplant antibodylevels are associated with a greater risk of CAI post-transplantation(Figure 4).

In conclusion, we identified and validated a panel of cir-culating non-HLA antibodies in renal transplant patients thatcorrelate with established CAI, can be serially measured post-transplant to identify which patients will develop acceleratedCAI over time, and, most importantly, to stratify risk for de-velopment of CAI by measuring this antibody panel even be-fore organ engraftment. The repertoire of the panel suggestsimmunologic “preconditioning” of the recipient as an impor-tant risk factor for CAI progression after engraftment becausethis panel of antibodies is enriched against cell-to-cell signal-ing and interaction as well as cell-mediated immune response,antigen presentation, and cell death (P,0.02). The alteredexpression of these factors may predispose the recipient tocontinued alloimmune injury, which then drives the turnoverof chronic interstitial injury, fibrosis, and TA, with loss of graftfunction over time. Importantly, very similar results are notedby microarray profiling of the very same biopsy samples, fromthe same patient cohort, in which very coordinated expressionof immune-specific genes in the allograft in the early protocolbiopsy can predict the progression of CAI in the later protocolbiopsy sample.24 It is intriguing that the reactive cytokinessuch as MIG, ITAC, and IFNG observed in this study are

also associated with AR in our previous reports.38,43 This ob-servation suggests a common activation of cytokines not onlyas immediate trigger of inflammation and injury in AR butalso as activated cytokines, in the case of CAI (Figure 6). Thefuture direction of this work requires a large-scale validationof these data in a prospective trial to assess the specificity andsensitivity of this antibody panel before transplant to assess therisk of CAI, and perhaps to subsequently titrate the immuno-suppression induction and maintenance strategy for eachtransplant patient on the basis of the risk of post-transplantCAI.

CONCISE METHODS

Patients and SamplesWe analyzed serological response on serum samples that were

collected from renal transplant patients from Lucile Packard Child-

ren’s Hospital, Stanford University, Stanford, California. After exclu-

sion of patients with incidences of acute rejection (antibody mediated

or cellular), infection, delayed graft function, donor pathology, and

C4d-positive peritubular capillary staining on biopsies, 172 sera sam-

ples from98patientswere selected and split into training and verification

groups with a one-third (n=60 sera samples for discovery) to two-thirds

split (n=112 sera samples for validation). The transplant patients in-

cluded in the study were unsensitized patients, with a peak plasma renin

activity,20% and mean recipient and donor HLA match of 3.561.29.

The demographic information of the transplant patients in the learning

and the verification groups is summarized in Table 5. For the discovery

group, a total of 60 sera samples were used. We selected a total of 30

Table 3. CAI-specific antibodies correlate with CADI score and IF-TA scores

Serial No. Gene Symbol Protein Name CADI Score (r, P) IF-TA Score (r, P)

1 IFNG IFN-g 0.68, ,0.0001 0.61, ,0.00012 MIG C-X-C motif chemokine 9 0.61, ,0.0001 0.55, 0.00023 ITAC C-X-C motif chemokine 11 0.51, 0.0009 0.42, 0.0074 CSNK2A2 Casein kinase 2, a prime polypeptide 0.51, 0.0008 0.52, 0.00065 GDNF Glial-derived neurotrophic factor 0.63, ,0.0001 0.58, ,0.00016 BHMT2 Betaine-homocysteine methyltransferase 2 0.47, 0.002 0.54, 0.00037 6CKINE C-C motif chemokine 21 0.56, 0.0002 0.54, 0.00038 CSNK2A1 Casein kinase 2, a1 polypeptide,

transcript variant 20.50, 0.001 0.54, 0.0004

9 J0-1(HARS) Histidyl-rRNA synthetase 0.63, ,0.0001 0.63, ,0.000110 CSNK1G1 Casein kinase 1, g1 0.49, 0.001 0.51, 0.000811 IL21 IL-21 0.57, 0.0001 0.51, 0.000812 CSNK1G3 Casein kinase 1, g3 0.35, 0.026 0.43, 0.00613 IL-8 IL-8 0.43, 0.006 0.48, 0.00214 PRKCE Protein kinase C, « 0.41, 0.009 0.48, 0.00215 FLJ21908 RNA polymerase II-associated protein 3 0.48, 0.002 0.47, 0.00216 WIBG Within bgcn homolog (Drosophila) 0.39, 0.01 0.46, 0.00317 ATXN3 Ataxin-3 0.46, 0.003 0.45, 0.00318 RNAPOL RNA polymerase 0.39, 0.01 0.45, 0.00419 MAPRE2 Microtubule-associated protein,

RP/EB family, member 20.34, 0.03 0.45, 0.004

20 CCL19 chemokine (C-C motif) ligand 19 0.40, 0.009 0.43, 0.006



sera collected at time 0, 6, and 24 months post-transplantation from

10 patients with confirmed CAI by 24 months post-transplantation.

The quality of the graft at the time of transplantation was excellent in

this selected group of patients, with amean Remuzzi score of 0.560.76

at the time of transplantation and a median score of 0. In the overall

group, the mean CADI score was used as a semi-quantitative measure

of the chronic injury grade.44,45 For analytical purposes, an arbitrary

cutoff CADI score,2 was used to score nonsig-

nificant histologic injury progression; a CADI

score $5.0 was used to score significant histo-

logic injury progression. These CAI samples

were compared with 30 sera samples from 10 de-

mographically matched transplant recipients with

stable graft function, with histologically clean pro-

tocol biopsies and minimal to no injury in each of

the 6- and 24-month protocol biopsies. For vali-

dation of discovered antibodies by cross-sectional

analysis, we identified sera samples collected from

demographically matched 31 renal transplant pa-

tients with biopsy CAI and 30 without CAI. The

details are summarized in Table 6. This study was

approved by the Institutional Review Board of

Stanford University and the other participating

centers of the clinical trial.

All 172 study biopsies were blindly analyzed

by a Stanford University pathologist and were

graded by the Banff classification5,46,47 for acute

rejection, and intragraft C4d stains were per-

formed48,49 to assess for acute humoral rejec-

tion.50,51 The histologic lesions of CAI were

extensively identified and a semi-quantitative

score for CAI applied to each biopsy, based on

standardized definitions from the Banff (2),

CADI, (3), and chronic calcineurin inhibitor

toxicity (19) scores. For the semi-quantitative

scoring criteria, chronic lesions are preceded by

“c”; interstitial fibrosis is denoted as “ci” and

scored as ci0–ci3; TA is denoted as “ct” and

scored as ct0–ct3 based on the area of cortical

tubular atrophy; glomerulopathy is denoted as

“cg: and scored as cg0–cg3 based on the extent

of double contours in glomerular capillary loops;

and arteriolar hyalinosis is denoted as “ah”

and scored as ah0–ah3 based on the extent of

PAS-positive hyalinosis. On the basis of the com-

bination of these features, a diagnosis of CAIwas

graded on the basis of severity as grade I (6%–

25% of cortex), grade II (26%–50% of cortex),

and grade III (.50% of cortex). If the biopsy of

the patient showed a CAI score,6% at the time

of serum collection, the sample was considered

as stable. Samples with biopsy scores for CAI

between 6% and 25%were deliberately excluded

to allow for clean separation of CAI samples in

this discovery process.

Serum Sample Collection and StorageBlood samples (4.5 ml) were collected in a 5-ml cryotube and incu-

bated at roomtemperature for30minutes until the clotwas formed.The

sample was then centrifuged at 20003g for 5 minutes using a swinging

bucket rotor. The serum was transferred to another cryotube and was

stored at 280°C until use.

Figure 4. CAI-specific antibodies at the time of transplant correlate with the injuryprogression post-transplant. IgG antibody level of two MIG antibodies at the time oftransplantation is positively correlated with CADI score post-transplantation at (A) 6 and(B) 24 months. IgG antibody level of two ITAC antibodies at the time of transplantationis positively correlated with CADI score post-transplantation at (A) 6 and (B) 24 months.ROC curves for the MIG, GDNF, ITAC, and IFNG antibodies predict development ofCAI. The predictive ability of baseline antibody level to predict injury at (E) 6 months (F)and (B) 24 months post-transplantation is shown in terms of ROC curves and area underthe curve for different antibodies as well as their combined contribution in the pre-diction. Ab, antibody.



Immune Response Biomarker Profiling by ProteinMicroarraysWe used the ProtoArray Human Protein Microarray (v4.0 and v4.1;

Invitrogen,Carlsbad,CA) for this study. The slides contained a total of

approximately 8200 antigens printed on each slide. The proteins

included in the arrays belong to different cellular locationswith awide

variety of functions. For the detection of immune response, we used

manufacturer’s protocol with slight changes. Briefly, the microarray

slides were blocked with 5.0 ml of blocking buffer (100 mM sodium

phosphate pH 7.4, 200 mMNaCl, 0.08% Triton X-100, 25% glycerol,

20 mM reduced glutathione, 1.0 mM DTT, 1% Hammarsten-grade

casein) with gentle agitation in four-well trays for 1 hour at 4°C. After

the blocking step, the blocking buffer was removed by aspiration and

5.0ml diluted serum (1:150) in PBSTbuffer (13PBS, 1%Hammarsten-

grade casein, 0.1% Tween 20) was added onto the plate to incubate for

90 minutes with gentle agitation at 4°C. In the next step, the serum

sample was removed and the plates were washed five times with 5.0

ml of fresh PBST buffer with 5-minute incubations per wash with

gentle agitation. A 5.0-ml portion of secondary antibody (Alexa

Fluor 647 conjugate anti-human antibody) diluted in PBST buffer

was added and the plates were incubated for 90 minutes with gentle

agitation at 4°C. The secondary antibody solution was removed by

aspiration. The plates were then washed five times with 5.0 ml of

fresh PBST buffer, with 5-minute incubations per wash with gentle

agitation. At the end, the slides were dried by centrifugation and

scanned using an Axon GenePix 4000B scanner (Molecular Devices,

Sunnyvale, CA). The data were acquired by using GenePix Pro 6.0

microarray analysis software (Molecular Devices). The slides were

scanned at 635 nm with a photomultiplier gain of 600, a laser power

of 100%, and a focus point of 0 mm. The .gal files were obtained

from a ProtoArray central portal on the Invitrogen website (www.

invitrogen.com/ProtoArray) by submitting the barcode of each pro-

tein microarray.

Statistical AnalysesSignal intensities per spot for each individual array were obtained

using GenePix Pro 6.0 software. We used Prospector Analyzer 5.2

(Invitrogen Inc) to subtract the background and to normalize and to

analyze the GenePix results files for each array. We used a standard

cutoff Z score of 3.0. Individual antigen reactivity was ranked based

on Z score above or below the mean signal for each array. Arrays from

patients of a distinct clinical phenotype were analyzed as a group.

Group analyses (.5 per group as suggested by the manufacturer)

were made by comparing two sets of individual antibody level for

every antigen present on the array usingM-statistics of the Prospector

Analyzer with the robust linear normalization method.20 Differences

in significance were displayed as P values, with #0.05 considered

significant. We performed two-factor ANOVA on the protein array

data using the CADI score and sample time as factors. The ANOVA P

values were corrected for multiple hypotheses using the Benjamini–

Hochberg correction. We found 72 antibodies that were significantly

affected by CADI score but not by time at false discovery rate ,0.2

Table 4. List of antibodies the level (from protein arrays) of which at the time of transplant and 6 months post-transplantcorrelates with CAI progression in the future

Gene Symbol Antigen Name Spearman Correlation (r)P

Value

Antibody level measured at the time of transplantation correlates with 6-mo chronic injuryGABPA GA binding protein transcription

factor, a subunit0.46 4.31E202

MIG Chemokine (C-X-C motif) ligand 9 0.74 2.00E204ITAC Chemokine (C-X-C motif) ligand 11 0.49 2.90E202IFNG IFN-g 0.60 5.50E203GDNF Glial cell-derived neurotrophic

factor0.55 1.12E202

Antibody level measured at the time of transplantation correlates with 24-mo chronic injuryIL-8 IL-8 0.46 3.98E202CCL21 Chemokine (C-C motif) ligand 21 0.49 2.94E202MIG Chemokine (C-X-C motif) ligand 0.71 5.00E204ITAC Chemokine (C-X-C motif) ligand 11 0.54 1.36E202IFNG IFN-g 0.73 3.00E204GDNF Glial cell-derived neurotrophic factor 0.62 3.20E203

Antibody level measured at 6 mo post-transplantation correlates with 24-mo chronic injuryIL-8 IL-8 0.47 3.87E202MIG Chemokine (C-X-C motif) ligand 9 0.46 4.25E202IL21 IL-21 0.51 2.16E202CCL19 Chemokine (C-C motif) ligand 19 0.48 3.30E202LRRK2 Leucine-rich repeat kinase 0.46 4.25E202CCL21 Chemokine (C-C motif) ligand 21 0.47 3.77E202GDNF Glial cell-derived neurotrophic factor 0.60 5.30E203IFNG IFN-g 0.59 6.30E203



http://www.invitrogen.com/ProtoArray

http://www.invitrogen.com/ProtoArray

for CADI score, of which 53 were increased in the CAI group. Hyper-

geometric enrichment, univariate and multivariate analyses, and logis-

tic regression modeling were performed using customized algorithms.

Ingenuity software (version 7.5; Ingenuity Systems Inc, RedwoodCity,

CA) was used to map target antigens to canonical pathways within the

Ingenuity Knowledge Base. Tissue expression of antigens against sig-

nificant antibodies correlated with CAI was examined using the hu-

man protein atlas.52–54

Figure 5. CAI-specific antibodies are validated with immunoassays using indirect ELISA. Levels of four of the CAI-specific antibodies areassayed in CAI sera and their increased presence in biopsy-proven CAI (n=31) is analyzed by comparing their level in renal transplantpatients with biopsy-proven stable graft function (n=30). Levels of (A) CSNK2A2 (P,0.002), (B) MIG (P,0.02), (C) ITAC (P,0.014), and(D) PDGFRA (P,0.0001) are increased. The increased level of antibody level of (E) CSNK2A2 and (F) MIG, along with increased CAI, isobserved from ELISA on independent samples (n=17). Increases in antibody level measured by ELISA, as well as CADI score for boththe antibodies are statistically significant (P,0.05). STA, stable.



Cross-Mapping of Gene IDs of the Compartment-Specific Gene on cDNA Microarray PlatformCross-mapping of kidney and kidney compartment-specific genes in

between cDNAmicroarray was performed using the data published21,22

and the ProteinMicroarray V.1 was conducted using the method pub-

lished earlier by our group18 using AILUN software (http://ailun.

stanford.edu/) to re-annotate probes to the most recent NCBI Entrez

gene identifiers.

Development and Optimization of ELISA Assay forValidation of CAI-Based Non-HLA AntibodyFor validation purposes, we developed antibody ELISA to detect serum

Ig binding to MIG (also called CXCL9), ITAC (also called CXCL11),

CSNK2A2,andPDGFRAfollowingthemethodpublishedpreviously.11,15

In brief, purified proteins, CSNK2A2 (cat# PV3624), PDGFRA (cat#

PV3811), ITAC (cat# PHC1694), and MIG (cat# OHC1604) were ac-

quired from Invitrogen (Carlsbad, CA). A titration with various coated

amounts starting at 30.00, 15.00, 7.5, 3.75, 1.87, 0.94, 0.47, and 0 ng,

respectively, was performed to determine the optimal amount to be

coated onto the immunosorbent 96-well plate. The 96-well microwell

ELISAplateswere coatedwith corresponding protein in 50ml of coating

buffer (15 mM Na2CO3, 30 mM NaHCO3, 0.02% NaN3, pH 9.6). The

subsequent washing and antibody incubation followed themethod pre-

viously published.11,15 The color was developed by using AP-pNPP

Liquid Substrate System for ELISA (Sigma-Aldrich, St. Louis, MO).

Absorptionwas measured at 405 nmwith a SpectraMax 190microplate

reader (Molecular Devices). To control for nonspecific binding, wells

with no proteins coated were served as negative controls.

Validation of CAI-Specific Antibody by ELISAAfter the optimization step, we validated the discovery made by the

protein arrays on 112 sera collected from 78 renal transplant patients.

There were 61 cross-sectional sera samples collected at 1 year post-

transplantation from 31 unique patients with biopsy-confirmed CAI

and 30 unique patients with stable biopsies (non-CAI). In addition,

there were 51 serial (longitudinal) samples from 17 patients with CAI

confirmed on their 6-month and 24-month biopsies, with sera

samples at 0, 6, and 24 months post-transplantation.

Figure 6. A developing picture of involvement of non-HLA antibodies against cytokines and other novel antigens in CAI. Abs, anti-bodies.

Table 5. Demographic data

Characteristic

Discovery Set (60 Sera) Validation Set (112 Sera)

Protein Array Analysis Cross-Sectional ELISALongitudinal ELISA

Non-CAI CAI P Value Non-CAI CAI P Value

Number of patients 10 10 30 31 17Steroid free/steroidbased

4/6 6/4 0.65 12/18 12/19 1.00 6/11

Donor sex (M/F) 8/2 4/6 0.17 18/12 22/9 0.13 9/8Donor age (yr) 24610

(21; 14–47)35.0610(36; 17–54)

0.03 30610(31; 14–47)

30610(31; 14–54)

0.97 29610

Recipient sex (M/F) 5/5 5/5 1.00 13/17 10/21 0.43 10/7Recipient age (yr) 1464

(13; 8–19)1066

(9; 2–19)0.17 1464

(15; 3–19)1265(12; 2–20)

0.08 1066

Living/deceased 4/6 6/4 0.66 14/16 17/14 0.61 7/10



http://ailun.stanford.edu/

http://ailun.stanford.edu/

We coated 15.6 ng of the purified proteins (MIG, ITAC, CSNK2A2,

andPDGFRA)ontoan immunosorbent96-wellplate(NUNCbrandcat#

446612). We followed a previously published protocol developed by our

laboratory.11,15 Briefly, the 96-well microwell ELISA plates were coated

with corresponding protein in 50ml of coating buffer (15 mMNa2CO3,

30mMNaHCO3, 0.02%NaN3, pH 9.6) and incubated overnight at 4°C.

Standard curves were generated using anti-GST tag (mousemonoclonal

IgG) (Millipore, Temecula, CA) andAP-conjugatedAffiniPure goat anti-

mouse IgG (Jackson ImmunoResearch, West Grove, PA). After washing

the plates with TBST buffer five times, the nonspecific protein binding

was blocked by 100ml of 5%drymilk in TBST buffer for 1 hour at room

temperature. After the blocking step, 50-ml serum samples (40-fold di-

luted with 2% milk in TBST buffer) were incubated in the wells for 1

hour at room temperature. The plates were washed five timeswith TBST

buffer and incubated in 50 ml of AP-conjugated AffiniPure mouse anti-

human IgG (Jackson ImmunoResearch). The color was developed by

using AP-pNPP Liquid Substrate System for ELISA (Sigma-Aldrich).

Absorption was measured at 405 nm with a SpectraMax 190

microplate reader (Molecular Devices). Statistical calculation (t test

and Spearman correlation) was performed using GraphPad Prism

software. P,0.05 was considered significant.

ACKNOWLEDGMENTS

We thankDr.MatthewVitalone for critically reading thismanuscript.

We appreciate the support from the Sarwal Laboratorymembers during

the study period and the patients and their families who participated in

this research study. We also thank the Stanford Functional Genomics

Facility at Stanford University for providing scanning facilities for the

protein arrays.

DISCLOSURESNone.

Table 6. Histologic data for the discovery set for protein array analysis

Non-CAI CAI P Value

Histology at implantation (n=10)IF/TA grade .0 0/10 1/10 1.00arteriolar hyalinosis (present/absent) 1/10 1/10 1.00intimal vascular thickening(present/absent)

1/10 0/10 1.00

glomerulosclerosis (present/absent) 1/10 2/10 1.00Remuzzi score 0.260.42 (0; 0–1) 0.860.92 (0.5; 0–2) 0.08

Histology at 6 months (n=10)tubulitis score .0 0/10 0/10 1.00interstitial inflammation score .0 0/10 1/10 1.00vasculitis score .0 0/10 0/10 1.00IF/TA grade .1 0/10 2/10 0.47arteriolar hyalinosis (present/absent) 0/10 0/10 1.00intimal vascular thickening(present/absent)

1/10 4/10 0.30

glomerulosclerosis (present/absent) 0/10 2/10 0.47CADI score 0.660.70 (10.5;0–2) 3.1761.65 (3.5; 1–6) ,0.0001

Histology at 24 months (n=10)tubulitis score .0 0/10 0/10 1.00interstitial inflammation score .0 0/10 0/10 1.00vasculitis score .0 0/10 0/10 1.00IF/TA grade .1 1/10 9/10 0.001arteriolar hyalinosis (present/absent) 0/10 1/10 1.00intimal vascular thickening(present/absent)

3/10 5/10 0.65

glomerulosclerosis (present/absent) 0/10 6/10 0.02CADI score 1.661.6 (1.5; 0–5) 7.161.5 (7;4–9) ,0.0001CADI score slope in first 2 years 0.760.9 (0.6; 20.3 to 2.5) 2.960.6 (3.1; 1.9–3.8) ,0.0001

Schwartz GFRat 6 months 99.2629.5 (93.6; 52–154) 117.0630.5 (102.9; 69.12–164.8) 0.42at 24 months 93.9630.2 (98.6; 62–121) 110.3619.5 (100.1; 97.15–144) 0.38

Absolute GFRat 6 months 73.7621.9 (70.6; 41–109) 66.0613.7 (67.2; 39–81) 0.36at 24 months 78.3649.1 (102; 22–111) 71.7629.9 (87.8; 34–101) 0.82



REFERENCES

1. Hariharan S, Alexander JW, Schroeder TJ, First MR: Impact of first acuterejection episode and severity of rejection on cadaveric renal allograftsurvival. Clin Transplant 10: 538–541, 1996

2. Weir MR, Wali RK: Minimizing the risk of chronic allograft nephropathy.Transplantation 87[Suppl]: S14–S18, 2009

3. Nankivell BJ, Alexander SI: Rejection of the kidney allograft. N Engl

J Med 363: 1451–1462, 20104. Nankivell BJ, Borrows RJ, Fung CL, O’Connell PJ, Allen RD, Chapman

JR: The natural history of chronic allograft nephropathy. N Engl J Med

349: 2326–2333, 20035. Solez K, Colvin RB, Racusen LC, Haas M, Sis B, Mengel M, Halloran PF,

Baldwin W, Banfi G, Collins AB, Cosio F, David DS, Drachenberg C,Einecke G, Fogo AB, Gibson IW, Glotz D, Iskandar SS, Kraus E, Lerut E,Mannon RB, Mihatsch M, Nankivell BJ, Nickeleit V, Papadimitriou JC,Randhawa P, Regele H, Renaudin K, Roberts I, Seron D, Smith RN,Valente M: Banff 07 classification of renal allograft pathology: Updatesand future directions. Am J Transplant 8: 753–760, 2008

6. Fletcher JT, Nankivell BJ, Alexander SI: Chronic allograft nephropathy.Pediatr Nephrol 24: 1465–1471, 2009

7. Joosten SA, Sijpkens YW, van KootenC, Paul LC: Chronic renal allograftrejection: Pathophysiologic considerations. Kidney Int 68: 1–13, 2005

8. Mao Q, Terasaki PI, Cai J, Briley K, Catrou P, Haisch C, Rebellato L:Extremely high association between appearance of HLA antibodies andfailure of kidney grafts in a five-year longitudinal study.AmJ Transplant

7: 864–871, 20079. Opelz G Collaborative Transplant Study: Non-HLA transplantation

immunity revealed by lymphocytotoxic antibodies. Lancet 365: 1570–1576, 2005

10. Sumitran-Holgersson S, Wilczek HE, Holgersson J, Söderström K:Identification of the nonclassical HLA molecules, mica, as targets forhumoral immunity associated with irreversible rejection of kidney al-lografts. Transplantation 74: 268–277, 2002

11. Sutherland SM, Li L, Sigdel TK, Wadia PP, Miklos DB, Butte AJ, SarwalMM: Protein microarrays identify antibodies to protein kinase Czetathat are associated with a greater risk of allograft loss in pediatric renaltransplant recipients. Kidney Int 76: 1277–1283, 2009

12. Sarwal MM, Yorgin PD, Alexander S, Millan MT, Belson A, Belanger N,Granucci L,Major C, Costaglio C, Sanchez J, Orlandi P, SalvatierraO Jr:Promising early outcomes with a novel, complete steroid avoidanceimmunosuppression protocol in pediatric renal transplantation.Transplantation 72: 13–21, 2001

13. Reichelt O, Müller J, von Eggeling F, Driesch D, Wunderlich H,Schubert J, Gröne HJ, Stein G, Ott U, Junker K: Prediction of renal al-lograft rejection by urinary protein analysis using ProteinChip Arrays(surface-enhanced laser desorption/ionization time-of-flight massspectrometry). Urology 67: 472–475, 2006

14. Roche S, Dauvilliers Y, Tiers L, Couderc C, Piva MT, Provansal M,Gabelle A, Lehmann S: Autoantibody profiling on high-density proteinmicroarrays for biomarker discovery in the cerebrospinal fluid.J Immunol Methods 338: 75–78, 2008

15. Butte AJ, Sigdel TK, Wadia PP, Miklos DB, Sarwal MM: Protein micro-arrays discover angiotensinogen and PRKRIP1 as novel targets for au-toantibodies in chronic renal disease. Mol Cell Proteomics 10:M110.000497, 2011

16. Li L, Chen A, Chaudhuri A, Kambham N, Sigdel T, Chen R, Sarwal MM:Compartmental localization and clinical relevance of MICA antibodiesafter renal transplantation. Transplantation 89: 312–319, 2010

17. Li L, Sigdel T, Vitalone M, Lee SH, Sarwal M: Differential immuno-genicity and clinical relevance of kidney compartment specific an-tigens after renal transplantation. J Proteome Res 9: 6715–6721,2010

18. Li L, Wadia P, Chen R, Kambham N, Naesens M, Sigdel TK, Miklos DB,Sarwal MM, Butte AJ: Identifying compartment-specific non-HLA

targets after renal transplantation by integrating transcriptome and“antibodyome” measures. Proc Natl Acad Sci USA 106: 4148–4153,2009

19. Naesens M, Lee S, Sigdel T, Kambham N, Li L, Sarwal M: Renalstanniocalcin-1 is involved in functional adaptation of adult-sizedkidneys transplanted into pediatric recipients [Abstract 1035]. AmJ Transplant 10[Suppl S4]: 340–341, 2010

20. Sboner A, Karpikov A, Chen G, Smith M, Mattoon D, Freeman-Cook L,Schweitzer B, Gerstein MB: Robust-linear-model normalization to re-duce technical variability in functional protein microarrays. J Proteome

Res 8: 5451–5464, 200921. Higgins JP, Wang L, Kambham N, Montgomery K, Mason V,

Vogelmann SU, Lemley KV, Brown PO, Brooks JD, van de Rijn M: Geneexpression in the normal adult human kidney assessed by comple-mentary DNA microarray. Mol Biol Cell 15: 649–656, 2004

22. Su AI, Cooke MP, Ching KA, Hakak Y, Walker JR, Wiltshire T, Orth AP,Vega RG, Sapinoso LM, Moqrich A, Patapoutian A, Hampton GM,Schultz PG, Hogenesch JB: Large-scale analysis of the human andmouse transcriptomes. Proc Natl Acad Sci USA 99: 4465–4470, 2002

23. Sigdel TK, Lee S, Sarwal MM: Profiling the proteome in renal trans-plantation. Proteomics Clin Appl 5: 269–280, 2011

24. Naesens M, Khatri P, Li L, Sigdel TK, Vitalone MJ, Chen R, Butte AJ,Salvatierra O, Sarwal MM: Microarray expression profiling associatesprogressive histological damage of renal allografts with innate andadaptive immunity. Kidney Int 80: 1364–1376, 2011

25. Naylor SL, Sakaguchi AY, Shows TB, Law ML, Goeddel DV, Gray PW:Human immune interferon gene is located on chromosome 12. J Exp

Med 157: 1020–1027, 198326. Bach EA, AguetM, Schreiber RD: The IFNgamma receptor: a paradigm

for cytokine receptor signaling. Annu Rev Immunol 15: 563–591, 199727. Young HA: Regulation of interferon-gamma gene expression.

J Interferon Cytokine Res 16: 563–568, 199628. Carnaud C, Lee D, Donnars O, Park SH, Beavis A, Koezuka Y, Bendelac

A: Cutting edge: Cross-talk between cells of the innate immune system:NKT cells rapidly activate NK cells. J Immunol 163: 4647–4650, 1999

29. Frucht DM, Fukao T, Bogdan C, Schindler H, O’Shea JJ, Koyasu S: IFN-gamma production by antigen-presenting cells: Mechanisms emerge.Trends Immunol 22: 556–560, 2001

30. Harris DP, Haynes L, Sayles PC, Duso DK, Eaton SM, Lepak NM, JohnsonLL, Swain SL, Lund FE: Reciprocal regulation of polarized cytokine pro-duction by effector B and T cells. Nat Immunol 1: 475–482, 2000

31. Zibar L, Wagner J, Pavlinić D, Galić J, Pasini J, Juras K, Barbić J: Therelationship between interferon-gamma gene polymorphism andacute kidney allograft rejection. Scand J Immunol 73: 319–324,2011

32. Crispim JC, Wastowski IJ, Rassi DM, Mendes-Junior Silva CT, Bassi C,Castelli EC, Costa RS, Saber LT, Silva TG, Donadi EA: Interferon-g +874polymorphism in the first intron of the human interferon-g gene andkidney allograft outcome. Transplant Proc 42: 4505–4508, 2010

33. Gołab J, Zagozdzon, Stokłosal T, Kami�nski R, Kozar K, Jakóbisiak M:Direct stimulation of macrophages by IL-12 and IL-18—a bridge toofar? Immunol Lett 72: 153–157, 2000

34. Schroder K, Hertzog PJ, Ravasi T, Hume DA: Interferon-gamma: An over-viewof signals,mechanismsand functions. JLeukocBiol75: 163–189, 2004

35. Fischereder M, Schroppel B: The role of chemokines in acute renal al-lograft rejection and chronic allograft injury. Front Biosci 14: 1807–1814, 2009

36. Rotondi M, Netti GS, Lazzeri E, Stallone G, Bertoni E, Chiovato L,Grandaliano G, Gesualdo L, Salvadori M, Schena FP, Romagnani P,Serio M: High pretransplant serum levels of CXCL9 are associated withincreased risk of acute rejection and graft failure in kidney graft recip-ients. Transpl Int 23: 465–475, 2010

37. Lazzeri E, Rotondi M, Mazzinghi B, Lasagni L, Buonamano A, Rosati A,Pradella F, Fossombroni V, La Villa G, Gacci M, Bertoni E, Serio M,Salvadori M, Romagnani P: High CXCL10 expression in rejected kidneys



andpredictive role of pretransplant serumCXCL10 for acute rejection andchronic allograft nephropathy. Transplantation 79: 1215–1220, 2005

38. Chen R, Sigdel TK, Li L, Kambham N, Dudley JT, Hsieh SC, Klassen RB,Chen A, Caohuu T, Morgan AA, Valantine HA, Khush KK, Sarwal MM,Butte AJ: Differentially expressed RNA from public microarray dataidentifies serum protein biomarkers for cross-organ transplant rejectionand other conditions. PLOS Comput Biol 6: 6, 2010

39. Howard OM, Dong HF, Yang D, Raben N, Nagaraju K, Rosen A,Casciola-Rosen L, Härtlein M, Kron M, Yang D, Yiadom K, Dwivedi S,Plotz PH, Oppenheim JJ: Histidyl-tRNA synthetase and asparaginyl-tRNA synthetase, autoantigens in myositis, activate chemokine re-ceptors on T lymphocytes and immature dendritic cells. J ExpMed 196:781–791, 2002

40. Moore MW, Klein RD, Fariñas I, Sauer H, Armanini M, Phillips H,Reichardt LF, Ryan AM, Carver-Moore K, Rosenthal A: Renal and neu-ronal abnormalities in mice lacking GDNF. Nature 382: 76–79, 1996

41. Basson MA, Akbulut S, Watson-Johnson J, Simon R, Carroll TJ, ShakyaR, Gross I, Martin GR, Lufkin T, McMahon AP,Wilson PD, Costantini FD,Mason IJ, Licht JD: Sprouty1 is a critical regulator of GDNF/RET-mediated kidney induction. Dev Cell 8: 229–239, 2005

42. Sainio K, Suvanto P, Davies J, Wartiovaara J, Wartiovaara K, Saarma M,ArumäeU,MengX, LindahlM,PachnisV, SariolaH:Glial-cell-line-derivedneurotrophic factor is required for bud initiation from ureteric epithelium.Development 124: 4077–4087, 1997

43. Sarwal M, Chua MS, Kambham N, Hsieh SC, Satterwhite T, Masek M,Salvatierra O Jr: Molecular heterogeneity in acute renal allograft re-jection identified by DNAmicroarray profiling.NEngl J Med 349: 125–138, 2003

44. Yilmaz S, Tomlanovich S, Mathew T, Taskinen E, Paavonen T, NavarroM, Ramos E, Hooftman L, Häyry P: Protocol core needle biopsy andhistologic Chronic Allograft Damage Index (CADI) as surrogate endpoint for long-term graft survival in multicenter studies. J Am SocNephrol 14: 773–779, 2003

45. Isoniemi H, Taskinen E, Häyry P: Histological chronic allograft damageindex accurately predicts chronic renal allograft rejection. Trans-plantation 58: 1195–1198, 1994

46. Racusen LC, Solez K, Colvin RB, Bonsib SM, Castro MC, Cavallo T,Croker BP, Demetris AJ, Drachenberg CB, Fogo AB, Furness P, GaberLW, Gibson IW, Glotz D, Goldberg JC, Grande J, Halloran PF, HansenHE, Hartley B, Hayry PJ, Hill CM, Hoffman EO, Hunsicker LG, LindbladAS, Yamaguchi Y: The Banff 97 working classification of renal allograftpathology. Kidney Int 55: 713–723, 1999

47. Racusen LC, Halloran PF, Solez K: Banff 2003 meeting report: Newdiagnostic insights and standards.AmJ Transplant 4: 1562–1566, 2004

48. Jianghua C,Wenqing X, HuipingW, Juan J, JianyongW, Qiang H: C4das a significant predictor for humoral rejection in renal allografts. ClinTransplant 19: 785–791, 2005

49. Vargha R, Mueller T, Arbeiter K, Regele H, Exner M, Csaicsich D,Aufricht C: C4d in pediatric renal allograft biopsies: A marker for neg-ative outcome in steroid-resistant rejection. Pediatr Transplant 10:449–453, 2006

50. Crespo M, Pascual M, Tolkoff-Rubin N, Mauiyyedi S, Collins AB,Fitzpatrick D, Farrell ML, Williams WW, Delmonico FL, Cosimi AB,Colvin RB, Saidman SL: Acute humoral rejection in renal allograft re-cipients: I. Incidence, serology and clinical characteristics. Trans-plantation 71: 652–658, 2001

51. Mauiyyedi S, Colvin RB: Humoral rejection in kidney transplantation:new concepts in diagnosis and treatment. Curr Opin Nephrol Hyper-tens 11: 609–618, 2002

52. Pontén F, Jirström K, Uhlen M: The Human Protein Atlas—a tool forpathology. J Pathol 216: 387–393, 2008

53. Berglund L, Björling E, Oksvold P, Fagerberg L, Asplund A, SzigyartoCA, Persson A, Ottosson J, Wernérus H, Nilsson P, Lundberg E,SivertssonA,Navani S,Wester K, KampfC, Hober S, Pontén F, UhlénM:A genecentric Human Protein Atlas for expression profiles based onantibodies. Mol Cell Proteomics 7: 2019–2027, 2008

54. Uhlén M, Björling E, Agaton C, Szigyarto CA, Amini B, Andersen E,Andersson AC, Angelidou P, Asplund A, Asplund C, Berglund L,Bergström K, Brumer H, Cerjan D, Ekström M, Elobeid A, Eriksson C,Fagerberg L, Falk R, Fall J, Forsberg M, Björklund MG, Gumbel K,Halimi A, Hallin I, Hamsten C, Hansson M, Hedhammar M, Hercules G,Kampf C, Larsson K, Lindskog M, Lodewyckx W, Lund J, Lundeberg J,Magnusson K, Malm E, Nilsson P, Odling J, Oksvold P, Olsson I, OsterE, Ottosson J, Paavilainen L, Persson A, Rimini R, Rockberg J, RunesonM, Sivertsson A, Sköllermo A, Steen J, Stenvall M, Sterky F, StrömbergS, Sundberg M, Tegel H, Tourle S, Wahlund E, Waldén A, Wan J,Wernérus H, Westberg J, Wester K, Wrethagen U, Xu LL, Hober S,Pontén F: A human protein atlas for normal and cancer tissues based onantibody proteomics. Mol Cell Proteomics 4: 1920–1932, 2005

This article contains supplemental material online at http://jasn.asnjournals.org/lookup/suppl/doi:10.1681/ASN.2011060596/-/DCSupplemental.





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