Results: Inflammation and local tissue injury correlated with the duration of warm ischemia time. Labile heme concentrations in renal tissue were significantly higher after prolonged (45 min) as compared to short (15 min) IRI. Notably, expression of the inducible heme-degrading enzyme heme oxygenase-1 (HO-1) was up-regulated in kidneys after prolonged, but not after short IRI. C5aR, the pro-inflammatory cytokines IL-6 and TNF-α as well as pERK were up-regulated after prolonged, but not after short ischemia times. Consecutively, neutrophil infiltration and up-regulation of pro-fibrotic cytokines such as CTGF and PAI were more pronounced in prolonged IRI in comparison to short IRI. In vitro stimulation of macrophages with LPS revealed that IL-6 expression was enhanced in the presence of heme. Finally, administration of the heme scavenger human serum albumin (HSA) reduced the expression of pro-inflammatory cytokines, C3a receptor and improved tubular function indicated by enhanced alpha 1 microglobulin (A1M) absorption after IRI.

**81**

Conclusions: Our data show that prolonged duration of warm ischemia time increased labile heme levels in the kidney, which correlates with IRI-dependent inflammation and up-regulation of anaphylatoxin receptor expression.

Keywords: ischemia reperfusion injury, AKI, HO-1, C5aR, C3aR, complement

#### INTRODUCTION

Ischemia reperfusion injury (IRI) is a major complication in solid organ transplantation (1). Cold ischemia time (CIT) for kidney allografts after post mortal donation can reach >20 h which mediates delayed graft function (DGF). In contrast, living donation has only 2–3 h CIT and lower rates of about 5% DGF (2). Notably, prolonged warm ischemia times have been linked to DGF observed in obese recipients who have undergone complicated surgeries (3). Additionally, IRImediated acute kidney injury (AKI) is a frequently encountered complication in other forms of solid organ transplantation such as lung transplantation (4).

The kidney is very sensitive to hemolysis-mediated damage (5). Hemolysis- associated hemoglobin cast nephropathy has been reported in renal biopsies of patients with various conditions such as autoimmune hemolytic anemia, paroxysmal nocturnal hemoglobinuria, transfusion of incompatible blood, disseminated intravascular coagulation (DIC) and in hemoglobinopathies (6). Hemolytic uremic syndrome (HUS) also leads to chronic kidney disease (CKD) and even end stage renal disease (ESRD) (7). Enhanced nephrotoxicity has also been documented in an experimental model of trauma hemorrhage (8). Upon hemolysis extracellular hemoglobin gets oxidized to methemoglobin and releases its prosthetic heme group. This fraction of "free or loosely" bound heme also termed "labile" is biologically active and high levels of labile heme are considered to be cytotoxic and to aggravate inflammation and tissue injury (9, 10). In support of this notion are the findings that the deficiency of the heme-degrading enzyme heme oxygenase-1 aggravates renal injury in different models of nephrotoxicity (11, 12).

In the current study we hypothesized that labile heme contributes to IRI-induced kidney injury. To test this hypothesis we determined labile heme levels in the kidney in a mouse model of renal IRI. Further, we also investigated the correlation between IRI-induced labile heme levels, inflammation and AKI. A panel of early and late inflammatory and histopathological markers after short (15 min) and prolonged (45 min) warm ischemia times were determined. In addition, the effect of administration of human serum albumin (HSA) as a heme scavenger was investigated in the 45 min IRI model.

#### MATERIALS AND METHODS

#### Animals

All experiments were performed with adult male C57Bl/6 mice (11–13 weeks of age, bodyweight 23–28 g). Mice were housed and bred in the Institute of Laboratory Animal Sciences, Hannover Medical School. Mice had free access to drinking water and food. The day/night cycle was 14/10 h. Mice were monitored daily for the physical condition after surgery. The experiments were approved by the local animal protection committee of the Lower Saxony State department for animal welfare and food protection (33.19-42502-04- 14/1657) which are in line with the National Institutes of Health guidelines.

#### Renal Ischemia Reperfusion Injury

Mice were anesthetized with isoflurane (3% induction, 1–2% maintenance), for analgesic treatment butorphanol 1 mg/kg bodyweight was given subcutaneously. IRI was induced by unilateral renal pedicle clamping with a micro aneurysm clip (Aesculap, Germany) for either 15 or 45 min. Afterwards, reperfusion was visually controlled. The contralateral not clipped kidney and sham surgery with opening of the abdominal cavity served as controls. For inhibitor experiments human albumin (Kendrion Biopharma, purity 98%), was diluted by sterile Phosphate Buffered Saline (PBS) to a final dose of 4 mg /mouse given i.v. 10 min before IRI 45 min surgery. The vehicle group received PBS injection.

#### Organ Preservation

Mice were sacrificed at two and 24 h after IRI and organ retrieval was done in deep general anesthesia (5% isoflurane). After midline laparotomy whole body perfusion with ice-cold 0.9% PBS via the left cannulated ventricle resulted in a circulatory arrest. Organs were dissected and fixed in RNA later, 4% paraformaldehyde or shock frozen in liquid nitrogen.

## Renal Morphology and Immunohistochemistry

After paraffin embedding 2µm sections were cut and stained. For overall morphology Perjodic Acid Schiffs (PAS) stain was done. Semi-quantitative scoring for signs of AKI was done: 0 = none or focal AKI, <5% of tubuli affected. 1 = mild AKI, 5–25% of tubuli affected. 2 = moderate AKI, 26–50% of tubuli affected. 3 = severe AKI, 51–75% of the tubuli affected. 4 = very severe AKI > 75% of tubuli affected. Immunohistochemistry was done with the following antibodies: Gr-1+ for neutrophils (Ly-6G/Ly-6C+, Serotec, UK), Alpha 1 Microglobulin (A1M, gift from Dr. Grams Lund University, Sweden) which is a marker of tubular transport and heme oxygenase-1 (HO-1, Enzo life sciences, Switzerland). Neutrophil infiltration was scored semiquantitatively. 0: <5 cells/view field (VF), 1: 5–10 cells/VF, 2: 11–20 cells/VF, 3: 21–50 cells/VF and 4: >50 cells/VF. HO-1 and A1M were semi-quantitatively expressed in percentage of the affected tubuli in 10 different areas. Images were captured with the same magnification. Five to six mice per group were used for all experiments. Analysis was conducted using a Leica imaging microscope at 200-fold magnification. Investigators were blinded to the animal group assignment.

### Pro-inflammatory Cytokine Expression

For cytokine analysis total mRNA was isolated using RNeasy Mini Kit (Qiagen, Hilden, Germany). Then, cDNA was synthetized with Prime Script Reverse Transcriptase reagent (Takara, Japan) from DNase-treated total RNA. qPCR was conducted on a LightCycler 96 (Roche, Penzberg, Germany) using sybrgreen primers. The following primers were used: Interleukin-6 (IL-6, Qiagen, #QT00098875), TNFα (Qiagen, #QT00104006), Monocyte Chemoattractant Protein-1 (MCP-1, Qiagen, #QT00167832), Plasminogen-Aktivator-Inhibitor Type 1 (PAI 1, Bio Tez Berlin-Buch GmbH, fwd: 5′ -ATGTTTAGTGCAACCCTGGC-3′ , rev: 5 ′ -CTGCTCTTGGTCGGAAAGAC-3′ ), Connective tissue growth factor (CTGF, Qiagen, #QT00096131) and HO-1 (Qiagen, #QT00159915). Complement 5a receptor 1 (C5aR1, accessionnumber: NM\_007577, fwd: 5′CAGGTGACCGGGG TGATGATAGC3′ rev: 5′GTAGGCCAGGGACACGCACAGG3′ and Complement 5a receptor 2 (C5aR2, accession number: NM\_001173550, fwd: 5′GCTGCATACAGCACAAGCA3′ , rev: 5′ACCACCACCGAGTATTATGACT3′ ). Complement 3a receptor (C3aR, accession number: NM\_009779, fwd: 5′ -GTG CTT GAC TGA GCC ATG GAG T-3′ , rev: 5′ -CAG CAC CAG CCC ATT GCC TA-3′ ), Hypoxanthine phosphoribosyl transferase (HPRT, Qiagen, #QT00166768) was used as house keeper for normalization. Five to six mice per group were analyzed.

#### Protein Isolation and Western Blotting

Frozen tissue samples were lysed in RIPA lysis buffer on ice, and protein was isolated. Protein quantification was done by BCA assay (Thermo Scientific, USA). Fifty micrograms of protein was loaded on a 10% polyacrylamide gel for electrophoresis. Proteins were blotted to polyvinylidene fluoride membranes (Millipore, Darmstadt, Germany). After blocking in 3% bovine serum albumin (BSA), incubation with primary antibodies was done overnight at 4◦C. The following antibodies were used: pERK (44/42 kDa, 9102S), ERK1/2 (44/42 kDa, 9106S, both from Cell Signaling Technologies, USA). 14-3-3 served as loading control (28 kDa, K-19, Santa Cruz Biotechnology, USA). After washing in PBS horseradish peroxidase (HRP) conjugated secondary antibodies (Dianova, Hamburg, Germany) were incubated for 1 h at room temperature. Proteins were visualized by incubation with SuperSignalTM West Pico Chemiluminescent Substrate (Thermo Fisher Scientific, USA). To enhance signal intensity SuperSignalTM West Femto Maximum Sensitivity Substrate (Thermo Fisher Scientific, USA) was used according to the manufacturer's instructions. Bands were immediately captured by VersaDoc MP 400 System (Bio Rad, USA). Five mice per group were analyzed.

## Determination of Labile Heme With an Apo-Horseradish Peroxidase (Apo-HRP) Assay

Labile heme assay was performed in 96 well plates as previously described (13, 14) with minor adaptations for measurement in tissue samples. Immediately after sacrifice the kidney tissue samples were weighed and minced in 1 ml Hank's Balanced Salt solution (HBSS). The supernatant was centrifuged at 1,500 rpm for 5 min to remove residual tissue aggregates and transferred to a fresh tube and stored at −80◦C or directly applied for the assay. Briefly, 5–20 µl of the supernatant was added in a final volume of 100 µl HBSS reaction mixture containing 0.75µM apo-HRP (BBI Solutions, Gwent, UK) and incubated for 10 min at 4◦C. In parallel hemin standards (0.25–2.5 nM) in a final volume of 100 µl reaction mixture (HBSS + apo-HRP) prepared from a stock solution of 25 nM hemin (Frontier Scientific, Logan, UT, USA) were also incubated. Then, 5 µl of samples and standards were transferred to a new 96 well plate and the assay was initiated by adding 200 µl of TMB substrate. The absorbance at 652 nm was kinetically read for 2–3 min and the time point at which the highest hemin standard gave an absorbance from 1.6 to 2 was chosen for determining the concentration of labile heme in samples. The calculated concentrations of heme were normalized with the tissue weight and expressed as pmol/mg tissue wet weight. Five mice per group were analyzed.

## In vitro Studies With Mouse Bone Marrow Derived Macrophages (BMDM)

Mouse bone marrow cells were differentiated into macrophages using r-MCSF as described previously (15). After 7 days of differentiation macrophages were seeded at a density of 5 × 105 cells in each well of a 6-well plate and allowed to rest overnight. Stimulation with LPS (1µg/ml) was performed in the presence or absence of hemin at the indicated doses in medium containing 1% serum for 16 h. The cells were lysed and processed for RNA isolation.

## Statistical Analysis

For statistical analysis GraphPad prism software (GraphPad Software Inc. 5.0, San Diego, CA) was used. Differences between groups were determined by one way ANOVA or student's t-test if two groups were compared. Data are shown as mean ± standard error (SEM). Significant differences were defined as ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

## RESULTS

## Increased Levels of Labile Heme After Prolonged Renal Ischemia

## Times—Correlation With HO-1 Expression

IRI is worsened by the length of the warm ischemia time (16, 17). To investigate whether labile heme levels are detectable after renal IRI we used an apo-HRP based assay on renal tissue samples subjected to short (15 min) and long (45 min) time periods of warm IRI. Labile heme levels were significantly increased in IRI kidneys with prolonged (45 min) compared to

FIGURE 1 | Labile heme release and complement activation after IRI. In renal tissue labile heme was elevated after 2 h in the 15 min but even more in the 45 min IRI model (A). HO-1 mRNA expression increased significantly after 45 min IRI (F) and also the expression of HO-1 protein on proximal tubular epithelial cells was significantly enhanced in the 45 min IRI group (B–E, bar: 100µm). The anaphylatoxin receptor C5aR1mRNA expression was significantly higher after prolonged ischemia time at 24 h after IRI (G). C5aR2 and C3aR showed enhanced mRNA expression after 15 and 45 min IRI compared to controls but the IRI groups did not differ (H,I) n = 5 mice/group, one way ANOVA. \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001.

(Continued)

FIGURE 2 | (E,F) after IRI were significantly increased in 45 min compared to 15 min IRI. Neutrophil infiltration was mainly observed in the outer medulla and was more prominent after prolonged ischemia time at 24 h after IRI (G–J, bar: 100µm, mean ± SEM. \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001, n = 6 mice/group, one way ANOVA). Co-stimulation experiments with bone marrow-derived mouse macrophages revealed that heme amplified the LPS induced up-regulation of IL-6 mRNA (K, \*p < 0.05 LPS vs. LPS+heme, one way ANOVA).

15 min IRI (**Figure 1A**, ∗p < 0.05). In contrast, labile heme levels in kidney samples after sham surgery or in contralateral non-clipped kidneys which served as controls were markedly lower. To investigate whether the determined levels of labile heme in kidneys after IRI are biologically relevant, we also determined renal expression of HO-1, which is the inducible isoform of the heme-degrading enzyme HO and is highly upregulated by heme (18, 19). Interestingly, HO-1 protein was induced in proximal renal tubuli after prolonged, but not after short ischemia times (**Figures 1B–E**, ∗∗∗p < 0.001). Similarly, HO-1 mRNA expression was significantly up-regulated in 45 min IRI (**Figure 1F**, ∗p < 0.05).

In addition, the mRNA expression of anaphylotoxin receptors C5aR1, C5aR2, and C3aR were analyzed as markers of complement activation. The expression of all three receptors was significantly induced after IRI (**Figures 1G–I**, ∗∗∗p < 0.001). Of note, only for C5aR1 expression the difference between 15 min and 45 min IRI reached statistical significance (**Figure 1G**, ∗∗p < 0.05).Taken together, the data show that increased levels of labile heme after prolonged warm ischemia time correlates with up-regulation of the heme-inducible gene HO-1 and the anaphylatoxin receptors in IRI kidneys.

#### Regulation of Inflammation Markers After Short and Prolonged Ischemia Times in Renal IRI

Heme has previously been shown to cause activation of the MAP kinase ERK1/2 (20) and TLR4-mediated up-regulation of proinflammatory cytokines TNF-α and IL-6 (21, 22). Hence, we hypothesized that an increase in labile heme after prolonged IRI will also lead to ERK1/2 activation and up-regulation of TNF-α and IL-6. Accordingly, prolonged IRI but not short IRI caused significant up-regulation of pERK at the 2 h time point (**Figures 2A,B**, ∗∗p < 0.01). Similarly, at this time-point the expression of the pro-inflammatory cytokines IL-6 and TNF-α were also markedly up-regulated after prolonged IRI in comparison to short IRI (**Figures 2C,D**, ∗∗p < 0.01, ∗∗∗p < 0.001). At 24 h expression of pro-fibrotic cytokines were also altered: PAI-1 and CTGF showed significant differences between short and prolonged IRI (**Figures 2E,F**). We also determined renal invasion of neutrophils as a marker of inflammation. Infiltration of neutrophils was most prominent in the outer medulla and Gr1 scores were 3-fold higher after 15 min IRI and 10-fold higher in 45 min IRI kidneys compared to controls at 24 h after IRI (**Figures 2G–J**, ∗∗∗p < 0.001). IRI causes activation of the TLR4 signaling pathway (23) and heme might play a role in amplifying TLR4-mediated inflammatory response. To test if heme can amplify TLR-4 mediated responses we stimulated bone marrow-derived macrophages (BMDM) in vitro with the TLR4 agonist lipopolysaccharide (LPS) in the presence or absence of heme. The LPS-induced up-regulation of IL-6 markedly increased in a dose-dependent manner in the presence of heme (**Figure 2K**, heme at 2.5 and at 5µM, ∗p < 0.05). To summarize, these results indicate that increased labile heme correlates with the increase in inflammatory parameters after prolonged IRI.

## Acute Kidney Injury After Short and Prolonged IRI

At 2 h after short IRI some signs of mild AKI with partial loss of the brush border membrane and tubular dilatation were detected (**Figures 3A,D**). As expected, prolonged IRI resulted in more severe AKI with flattening of the tubular epithelial cells, tubular cell detachment and cast formation. Major tissue damage was observed in the outer medulla where hypoxia is most severe due to the physiological lower oxygen saturation compared to the cortex (24). At 24 h after prolonged IRI the outer medulla had very severe AKI with tubular casts and interstitial inflammation, which was hardly detectable after short term IRI (**Figures 3G–K**).

#### Impairment of Tubular Function After Prolonged IRI

A1M is a circulating protein that is synthesized in the liver, filtered in the glomeruli and reabsorbed by healthy proximal tubular epithelial cells (pTEC). A1M was located in small vesicles in the cytoplasma of 60% of the healthy pTECs in the control groups. Already at 2 h after IRI tubular reabsorption was disturbed and A1M expression was reduced after short and virtually abolished in prolonged IRI (**Figures 4A–C,G**). The reduction of tubular reabsorption was even more pronounced and almost absent after 24 h in the prolonged IRI model. The profound tubular damage caused protein cast formation in the outer medulla which also contained A1M after prolonged IRI (**Figure 4E**).

#### Treatment With the Heme Scavenger Human Serum Albumin Attenuated IRI

Human serum albumin (HSA), which is routinely applied in the clinic for various medical indications, is known to bind heme with high affinity and can therefore be considered as a potent heme scavenger. To investigate whether HSA may interfere with the putative heme-mediated effects of renal IRI, HSA was administered intravenously 10 min prior to prolonged (45 min) IRI. Treatment with HSA blocked the expression of pro-inflammatory cytokines IL-6 and TNFα (**Figures 5A,B**, ∗p < 0.05). Similarly, the expression of the anaphylatoxin receptor C3aR was significantly reduced by albumin treatment (**Figures 5C,D**, ∗p < 0.05). In addition, A1M staining was increased in the HSA treated IRI group (**Figures 5E–G**) indicating improved maintenance

of tubular function by absorption of A1M. To summarize, these results indicate that treatment with albumin may at least partially prevent IRI-mediated inflammatory activation and damage.

## DISCUSSION

Heme release has been proposed to play a role in IRI related kidney injury based on the findings that heme levels and

HO-1 expression in the microsome (heme-rich) fraction of kidneys are increased after IRI (25). However, due to lack of a suitable method it was not possible to distinguish between bound-heme (i.e., heme in hemoproteins) and un-bound or loosely bound heme (i.e., labile heme). In particular, the latter fraction of heme has been proposed to play a detrimental role in pathophysiological conditions (26). In the current study, we extend these earlier findings and report that IRI causes an increase of the labile heme fraction in renal tissue. Importantly, the levels of labile heme correlated with the duration of warm ischemia time and with the severity of inflammation following IRI. Furthermore, treatment with the heme-scavenger albumin reduced the expression of IRI-related inflammatory markers.

reduced in the prolonged IRI group (E, bar: 100µm, mean ± SEM, \*p < 0.05, \*\*\*p < 0.001, n = 6 mice/group, one way ANOVA).

## Source of Labile Heme in the Kidney Following IRI

Kidney after heart has the highest mitochondrial abundance (27) and it is feasible that IRI alters mitochondrial heme synthesis to increase labile heme levels. In support of this notion are the findings that failing human hearts have increased levels of heme accompanied by increased expression of the heme synthesizing enzyme 5′ -aminolevulinate synthase 2 (ALAS2) (28). Moreover, increased heme synthesis led to exacerbated injury after coronary ligation in ALAS2 transgenic mice (29). It remains to be evaluated if ischemic injury also alters heme synthesis in the kidney. Independently, an increase in labile heme levels can also be a result of heme release from unstable hemoproteins such as cytochromes due to mitochondrial damage. Corroborating this

was significantly higher in vehicle treated IRI kidneys compared to control kidneys (C, \*p < 0.05). C3aR mRNA expression was significantly reduced by albumin treatment compared to vehicle (D, \*p < 0.05). The tubular function marker A1M showed higher expression after albumin treatment in proximal tubular epithelial cells after IRI (E–G, bar: 100µm mean ± SEM, \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001, n = 6 mice/group, one way ANOVA). n = 5 mice/group, one way ANOVA.

notion are the findings that inhibitors of cytochrome P450 prevent cell injury by attenuating (heme-derived) iron release and hydroxyl radical formation after reoxygenation of kidney tubular epithelial cells in vitro (30). Alternatively, local hemolysis that occurs during IRI or myoglobin released during tissue injury could also contribute to the pool of extracellular labile heme. We have previously shown that prolonged IRI caused substantial impairment of renal perfusion (31) which may result in trapping and degradation of erythrocytes.

## Underlying Mechanisms of Heme-Mediated Inflammation After IRI

The findings of this study indicate that the increase in labile heme levels correlates with the degree of inflammation after prolonged ischemia time. Heme can promote and aggravate inflammation by diverse mechanisms. In endothelial cells, heme induces the production of various adhesion molecules, including E-selectin, P-selectin, intercellular adhesion molecule 1 (ICAM-1), and vascular cell adhesion molecule 1 (VCAM-1) (32, 33), thus promoting leukocyte infiltration. In accordance with this notion, neutrophil infiltration was substantially increased after prolonged ischemia time. Additionally, heme has also been implicated in the secretion of the neutrophil chemoattractant CXCL2 (34). Neutrophil infiltration was mainly observed in the outer medulla, the area with the lowest oxygen tension and consecutively with the highest extent of hypoxia (24).

Our findings also indicate that renal expression of the anaphylatoxin receptors (C5aR1, C5aR2, and C3aR) is induced by prolonged ischemia. Both C3a and C5a are known to promote IRI (35) and C3aR and C5aR deficient mice are protected from IRI-induced damage (35, 36). As a mediator of complement activation, heme has gained increasing appreciation in recent years. Intravascular hemolysis has been shown to activate the complement system via the alternative pathway, which in turn has been implicated in the pathogenesis of atypical hemolytic uremic syndrome (aHUS) (37, 38). More recently, hememediated complement activation via the alternative pathway has been shown to be involved in the pro-inflammatory activation of leukocytes (39). Noteworthy, it has been reported that kidney biopsies from sickle cell disease nephropathy patients showed deposits of C3 and C5, which was also observed in a mouse model of sickle cell disease (38). It may well be that the increased expression of C5aR1, C5aR2, and C3aR observed in this study are secondary effects of heme-mediated complement activation. Further studies are required to elucidate the interplay of labile heme and anaphylatoxin receptors by using genetically modified mouse models in renal IRI and kidney transplantation (36, 40). Heme has also been proposed to be a danger associated molecular pattern (DAMP) (41) that can amplify TLR4 signaling. Accordingly, the in vitro findings of the current study show that the LPS-induced expression of the pro-inflammatory cytokine IL-6 is aggravated in the presence of heme in bone-marrow derived macrophages which is in accordance with a previous report in peritoneal macrophages after LPS stimulation (21).

## Scavenging Labile Heme as a Therapeutic Strategy Against IRI-Mediated Kidney Injury

In this study treatment with the heme scavenger human serum albumin (HSA) prior to IRI reduced pro-inflammatory cytokine release and C3aR expression in the renal tissue after prolonged IRI. HSA is broadly used in the clinic for the treatment of patients with ascites and chronic liver disease (42, 43) and in the context of plasmapheresis in certain renal diseases (44). However, it is noteworthy that the serum protein hemopexin has a markedly higher binding affinity for heme than albumin. While hemopexin has been shown to counteract heme-mediated complement activation and pro-inflammatory responses in mouse models it has not been approved for therapeutic applications in clinical practice (45, 46). It might well be that preventive strategies using hemopexin could be more beneficial than albumin and future comparative studies are required to understand if heme scavengers can prevent renal IRI-mediated inflammation or delayed graft function after kidney transplantation. Due to the local malperfusion after IRI elaborated strategies to deliver heme scavengers to the kidney might be necessary. In the context of transplantation normothermic machine perfusion strategies (47) might prevent the release of labile heme in allografts. Additionally, the method can also be used for drug delivery to allografts prior to implantation (48). Introducing heme scavengers at the time of ex vivo perfusion either directly or in a targeted fashion using drug-delivery systems such as liposomes (49) might also be a viable therapeutic strategy to counter labile heme.

#### Limitations

Our study focuses on the early time points after IRI and has only a short follow-up of 2 h after albumin treatment. Further experiments are needed to investigate heme-binding strategies in the context of IRI and to investigate long term effects on renal function such as progressive inflammation and renal fibrosis.

In conclusion, our results indicate that prolonged ischemia time after IRI enhances labile heme levels in renal tissue, which contribute to complement activation, inflammation and AKI. Future studies are warranted to understand if scavenging labile heme can attenuate AKI and delayed graft function after kidney transplantation. Developing clinical applicable therapeutic strategies to reduce the burden of labile heme in the ischemic organ might result in improved long term outcome after solid organ transplantation.

## DATA AVAILABILITY STATEMENT

All datasets generated for this study are included in the article/supplementary material.

## ETHICS STATEMENT

The animal study was reviewed and approved by Lower Saxony State department for animal welfare and food protection.

## AUTHOR CONTRIBUTIONS

FG: designed, supervised all aspects of the study and drafted the manuscript. LW, NS, VV, RC, SR, KM, AT, PP, RG, M-SJ, and FG: experimental conduct. FG, LW, VV, and SI: discussion and wrote the manuscript. RC and SR: animal surgeries. IT, JB, NM, KD, MH-L, CK, RL, and HH: discussion of results. All authors participated in the interpretation of data, editing, and approval of the manuscript.

## FUNDING

This study was supported by the German Science Foundation (DFG) grant GU 613/1-1 to FG and DFG grant IM 20/4-1 to SI.

## ACKNOWLEDGMENTS

We thank Herle Chlebusch and Michaela Beese for excellent technical support. We thank Jessica Schmitz for advice on immunostaining protocols.

## REFERENCES

through spleen tyrosine kinase (Syk)-dependent reactive oxygen species generation. J Biol Chem. (2010) 285:32844–51. doi: 10.1074/jbc.M110.146076

in translational mouse models. J Magn Reson Imaging. (2017) 46:1664– 72. doi: 10.1002/jmri.25713

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Wang, Vijayan, Jang, Thorenz, Greite, Rong, Chen, Shushakova, Tudorache, Derlin, Pradhan, Madyaningrana, Madrahimov, Bräsen, Lichtinghagen, van Kooten, Huber-Lang, Haller, Immenschuh and Gueler. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Increasing Time in Therapeutic Range of Tacrolimus in the First Year Predicts Better Outcomes in Living-Donor Kidney Transplantation

Turun Song† , Saifu Yin† , Yamei Jiang, Zhongli Huang, Jinpeng Liu, Zhiling Wang, Linde Li, Jun Zeng, Yu Fan, Xianding Wang, Xingxing Li and Tao Lin\*

*Urology Department, Urology Research Institute, Organ Transplantation Centre, West China Hospital, Sichuan University, Chengdu, China*

Background: The aim of the present study was to investigate the impact of time in therapeutic range TTR on long-term outcomes of living kidney transplants.

#### Edited by:

*Guseppe Grandaliano, University of Foggia, Italy*

#### Reviewed by:

*Ying-Jun Chang, Peking University People's Hospital, China Stanislaw Stepkowski, University of Toledo, United States*

#### \*Correspondence:

*Tao Lin<EMAIL_ADDRESS>
*†These authors have contributed equally to this work and share first authorship*

#### Specialty section:

*This article was submitted to Alloimmunity and Transplantation, a section of the journal Frontiers in Immunology*

Received: *31 August 2019* Accepted: *27 November 2019* Published: *20 December 2019*

#### Citation:

*Song T, Yin S, Jiang Y, Huang Z, Liu J, Wang Z, Li L, Zeng J, Fan Y, Wang X, Li X and Lin T (2019) Increasing Time in Therapeutic Range of Tacrolimus in the First Year Predicts Better Outcomes in Living-Donor Kidney Transplantation. Front. Immunol. 10:2912. doi: 10.3389/fimmu.2019.02912* Methods: We included 1,241 living kidney transplants and randomized them into development and validation cohorts with a ratio of 2:1. The tacrolimus TTR percentage was calculated by linear interpolation with a target range (5–10 ng/ml months 0–3, 4–8 ng/ml months 4–12). The optimal TTR cutoff was estimated by the receiver operating characteristic curve analysis on the basis of acute rejection (AR) within 12 months in the development cohort. Outcomes were analyzed between patients with high TTR and low TTR in the development and validation cohorts, respectively. The TTR was also compared with other tacrolimus measures.

Results: The optimal TTR cutoff value was 78%. In the development cohort, patients with TTR > 78% had significantly higher rejection- and infection-free survival. TTR < 78% was an independent risk factor for AR (OR: 2.97, 95%CI: 1.82–4.84) and infection (OR: 1.55, 95%CI: 1.08–2.22). Patient and graft survival were significantly higher in those with TTR>78%, and TTR<78% was associated with graft loss (OR: 3.2, 95%CI: 1.38–7.42) and patient death (OR: 6.54, 95%CI: 1.34–31.77). These findings were confirmed in the validation cohort. Furthermore, we divided all included patients into a high and low TTR group. TTR was more strongly associated with patient and graft survival than mean level, standard deviation, and intrapatient variability (IPV).

Conclusions: Increasing the TTR of tacrolimus in the first year was associated with improved long-term outcomes in living kidney transplants, and TTR may be a novel valuable strategy to monitor tacrolimus exposure.

Keywords: tacrolimus, time in therapeutic range, kidney transplantation, development and validation, acute rejection, infection, graft loss, patient death

## INTRODUCTION

Tacrolimus-based regimens are the most commonly used immunosuppressive therapies, preventing T-cell and antibody-mediated rejection after kidney transplantation (1); however, a narrow therapeutic index limited their clinical application. Overexposure can result in toxicity and severe infection, and underexposure can lead to graft rejection (2, 3). Therapeutic drug

**93**

monitoring to maintain the intensity and stability and a constant tacrolimus trough level allows for the achievement of optimal immunosuppression. Mean level, intrapatient variability (IPV), and variability of the standard deviation of the tacrolimus trough level are associated with acute rejection (AR) and graft loss (4–6). However, these indexes did not consider whether the tacrolimus trough level achieved a target therapeutic window and exposure time. As failure to maintain the tacrolimus trough level in target ranges is a risk factor for inferior short- and long-term outcomes (7, 8), it seems more practical and clinically relevant to develop a new indicator to combine the tacrolimus trough level with variation and the corresponding maintaining time.

Percent time in therapeutic range (TTR), defined as the percentage of time within the therapeutic range over time, takes stability, intensity, and constancy into consideration simultaneously. TTR is a validated method for assessing effective warfarin therapy and has been used as a tool to risk stratifying (9, 10). Limited studies have investigated the use of TTR in transplantation, but a low tacrolimus TTR was associated with significantly increased acute cellular risk in lung transplants (11) and de novo donor-specific antibodies (dnDSAs) in kidney transplants (12). These facts indicated that the tacrolimus TTR might have potential as a prognostic indicator in organ transplantation, but evidence of its impact on the long-term outcomes of living kidney transplants is lacking. The present study investigated whether patients with a high tacrolimus TTR had better clinical results than those with a low tacrolimus TTR.

## METHODS

#### Patient Population

The clinical data of patients who received a living-related kidney transplant at West China Hospital between August 2007 and April 2017 were retrospectively analyzed. The Ethics Committee of West China Hospital approved the study. Patients who were <18 years of age, with an initial calcineurin inhibitor (CNI) other than tacrolimus, tacrolimus switch or withdrawal in first 12 months, receiving an ABO-incompatible kidney transplant, with organ transplant history, a follow-up of <1 year, or with three or more consecutive missing measures of tacrolimus trough level, according to our monitoring protocol, were excluded.

#### Data Collection

We retrieved information from medical records, including patient age, sex, body mass index at the time of transplantation, duration of pretransplantation dialysis, organ transplant history, panel reactive antibody (PRA), human leukocyte antigen (HLA) mismatch, induction therapy, delayed graft function (DGF), and cold ischemic time. DGF was defined as the need for dialysis in the first week after transplantation. AR, infection, graft loss, and patient death were the clinical outcomes of interest. AR was diagnosed clinically based on a 50% or more significant increase in serum creatinine levels within 3 days that was not explained by some other cause and that was confirmed by biopsy when necessary. AR was treated primarily with bolus doses of methylprednisolone and with antithymocyte globulin if refractory. Infection was defined as any infectious symptoms needing medication intervention, including wound, pulmonary, urinary tract, and skin infections. Re-establishment of long-term dialysis therapy or estimated glomerular filtration rate (eGFR) of <15 ml/min was considered as graft loss. Allograft survival was censored at the earliest of the following events: loss to follow-up or patient death. The definition of graft failure did not include patient death with a functioning graft. Renal function was assessed by eGFR, calculated using the Modification of Diet in Renal Disease (MDRD) equation for Chinese and adjusted for body surface area (13).

#### Immunosuppression Regimen

The immunosuppression therapy used at our hospital has been previously described (14). Briefly, rabbit antihuman thymocyte immunoglobulin (ATG) (1 mg/kg administered for 3–7 days) or monoclonal anti-CD25 monoclonal antibody (IL-2R antibody) (20 mg on days 0 and 4 post-transplant) were used as induction therapy. Maintenance immunosuppressive therapy consisted of tacrolimus, mycophenolate mofetil/enteric-coated mycophenolate sodium (MMF/EC-MPS), and corticosteroids. Tacrolimus was initiated at 1.5 mg bid on day two posttransplantation and maintained at 5–12 ng/mL. The tacrolimus trough level was measured by the enzyme multiplied immunoassay technique (EMIT, Dade-Behring, NY, USA) in blood samples collected weekly during months 0–3, every 2 weeks during months 4–6, and monthly thereafter in the first year. Tacrolimus trough levels were obtained before breakfast and dose administration in the morning. Any tacrolimus levels that were <2 or > 15 ng/mL were individually reviewed and excluded if they were not valid. MMF was started on the night before the operation at 1,000 mg and maintained at 1,000 mg bid. The area under the curve (AUC) for mycophenolate mofetil was 30–70 mg/h·L −1 . EC-MPS 720 mg was administrated the night before the operation and at 720 mg bid after that. The EC-MPS AUC was not measured. Methylprednisolone 500 mg was administered intravenously during the surgery, and 300 mg was given daily for the next 3 days. It was then replaced by 60 mg of prednisone, which was tapered by 10 to 5–10 mg/day for maintenance.

#### Time in Therapeutic Range

We randomized all patients into development and validation cohorts with a ratio of 2:1. The process was finished by SPSS 24.0 software. First, SPSS gave each individual a random number. Then, these number were ranked in order from large to small. Last, the first 2/3 was used as the developed cohort and the latest 1/3 was used as the validation cohort. The tacrolimus TTR percentage was calculated by linear interpolation as described by Rosendaal in the development cohort (15). The linear relationship between each tacrolimus trough level and the TTR was calculated by summing the time during which the value fell within the target tacrolimus range of 5–10 ng/ml during months 0–3 and 4–8 ng/ml during months 4–12. The tacrolimus TTR was compared with the tacrolimus standard deviation (SD), mean, and the IPV. The IPV was calculated by dividing SD by the mean level (16).

*ATG, antithymocyte globulin; BMI, body mass index; eGFR, estimated glomerular filtration rate; DGF, delayed graft function; HLA, human leukocyte antigen; PRA, panel reactive antibody.*

*aContinuous data are presented as mean* ± *standard deviation (SD), and categorical data as percentage of the total, unless otherwise noted.*

#### Statistical Analysis

Descriptive statistics were used to describe the baseline characteristics of the patients in the development and validate cohorts. Categorical variables were compared using the χ 2 -test or Fisher's exact test; continuous variables were compared using a Student's t-test. A receiver operating characteristic (ROC) curve was built from the calculated TTR value in development cohort to determine the optimal TTR cutoff value that can discriminate patients with or without AR in the first year best. The area under the ROC curve with sensitivity and specificity was computed, and the TTR with the greatest AUC is the optimal cut-off value (17).

Time to AR, infection, graft loss, and recipient death was analyzed by the Kaplan–Meier method, and between-group differences were assessed for significance by the log-rank test. Cox Proportional regression was used to identify predictors of AR, infection, graft loss, and patient death. Variables with p < 0.1 in the univariate analysis were included in the multivariate analysis. The statistical analysis was performed using SPSS 24.0 (IBM Corp., Armonk, NY, USA). P < 0.05 was considered significant.

#### RESULTS

From August 2007 to April 2017, 2,048 patients received a living related kidney transplant in West China Hospital, Sichuan University. A total of 807 patients were excluded: follow-up time was <1 year (N = 227); CNI was not tacrolimus (N = 275);

lost in the follow-up (N = 82); organ transplantation history (N = 15); ABO-incompatible kidney transplantation (N = 38); and consecutive missing of tacrolimus trough level 3 times or more (N = 170). A total of 1,241 patients were included with 827 in the development cohort and 414 in the validation cohort. The process of enrollment of patients is shown in the flow chart (**Supplementary Figure 1**). The clinical characteristics of the development cohort and validation cohort are shown in **Table 1**. The median follow-up for the entire cohort was 42 months [interquartile range (IQR): 26–59 months]; 42 months (IQR: 26–59 months) for the development cohort, and 42 months (IQR: 25–59 months) for the validation cohort.

The optimal cutoff value for TAC TTR was 78% (AUC = 0.733; sensitivity = 66.3%; and specificity = 69.1%) (**Figure 1**). We thus divided patients in the development and validation cohort into a high TTR group and low TTR group. Baseline characteristics between the high and low TTR groups in both cohorts are summarized in **Table 2**. All variables were comparable between high and low TTR groups in the development cohort; however, in the validation cohort, patients in the low TTR group received kidneys from older donors (P = 0.02) and had more HLA mismatches (P = 0.02). There was no difference in the tacrolimus trough levels between high and low TTR groups within the first year in the development and validation cohort. No difference was detected in renal function between the two groups during the follow-ups in the development cohort, while the high TTR group in validation cohort had a litter higher eGFR in first 3 years (mean difference 4∼5 ml/min/1.73 m2 ) (**Figure 2**).

#### Graft Survival

In the development cohort, more patients experienced graft loss (15/283, 5.3%) in the low TTR group than those in the high TTR (9/544, 1.7%) (P < 0.001). The Kaplan–Meier curve indicated

TABLE 2 | Characteristics between the high and low TTR groups in development and validation cohorts.

*ATG, antithymocyte globulin; BMI, body mass index; eGFR, estimated glomerular filtration rate; DGF, delayed graft function; HLA, human leukocyte antigen; PRA, panel reactive antibody.*

development cohort; (B) Tac concentration in the validation cohort; (C) eGFR in the development cohort; (D) eGFR in the validation cohort. Tac, tacrolimus.

that the graft survival in the high TTR group was significantly higher than that in the low TTR group (**Figure 3C**). The 3- and 5-year graft survival was 97.5 and 96.6% as well as 93.5 and 92.3% for the high and low TTR group, respectively. Lower TTR was an independent graft-loss contributor in the multivariate analysis (OR: 3.2, 95%CI: 1.38–7.42). A younger age also seemed to be protective for graft survival (OR: 0.95, 95%CI: 0.90–1.00) (**Table 3**).

Similarly, in the validation cohort, more patients have experienced graft loss (6.2 vs. 2.6%, P = 0.069) in the low TTR group. Kaplan-Meier estimation indicated graft survival in high TTR group was significantly higher than that in low TTR group (**Figure 4**). Lower TTR was associated with a higher risk of graft loss (OR: 5.09, 95%CI: 1.28–23.65). Also, younger recipients (OR: 0.87, 95%CI: 0.78–0.96) and lower PRA (OR: 0.07; 95%CI: 0.01– 0.56) were found to have independent protective effects on graft survival (**Table 4**).

## Recipient Survival

In the development cohort, during the follow-up, 7 (2.5%) and 2 deaths (0.4%) were recorded in the low TTR group and high TTR group (P = 0.016), respectively. The Kaplan–Meier estimation found that the high TTR group had significantly better patient survival than that of low TTR group (**Figure 3D**). The 3- and 5 year graft survival was 99.2 and 99.2% as well as 97.2 and 94.8% for the high and low TTR group, respectively. Lower TTR was an independent risk factor for graft loss in the multivariate analysis (OR: 6.54, 95%CI: 1.34–31.77) (**Table 3**).

In the validation cohort, a similar trend was observed with more patients experiencing patient death (4.1 vs. 0.7%, P = 0.043) in the low TTR group. Lower TTR was associated with a higher risk of patient death (OR: 6.8, 95%CI: 1.34–34.61) (**Table 4**). The Kaplan–Meier estimation indicated patient survival in the high TTR group was significantly higher (**Figure 4**).

## Acute Rejection

In the development cohort, 44 patients (15.5%) developed AR in the low TTR group compared to 32 (5.9%) in the high TTR group (P < 0.001). Patients without developing DGF (OR: 0.21, 95%CI: 0.06–0.77) were also observed to develop less AR. A multivariate analysis indicated that TTR ≤ 78% was an independent risk factor for AR (OR: 2.97, 95%CI: 1.82–4.84) (**Table 3**). Rejectionfree survival was significantly higher in the high TTR group than that in the low TTR group (**Figure 3**).

In the validation group, similar results were observed. There were significantly more patients experiencing AR (12.4 vs. 2.6%, P < 0.001) in the low TTR group. Multivariate regression showed that TTR ≤ 78% was associated with a higher incidence of AR (OR: 2.97, 95%CI: 1.82–4.84) (**Table 4**). The Kaplan–Meier estimation indicated that rejection-free survival was significantly higher in the high TTR group than that in the low TTR group (**Figure 4**).

## Infection

For the development cohort, a total of 148 patients developed infection at least once with 63 (22.3%) in the low TTR group and 85 (15.6%) in the high TTR group (P = 0.018). Low TTR was associated with a higher risk of infection in the multivariate analysis (OR: 1.55, 95%CI: 1.08–2.22) (**Table 3**). The Kaplan– Meier estimation revealed that the infection-free survival was significantly higher in the high TTR group than that in the low TTR group (**Figure 3**).

Furthermore, in the validation group, we confirmed the results that more patients experienced infection episodes (24.1 vs. 13.8%, P = 0.008) in the low TTR group. TTR ≤ 78% was associated with a higher incidence of infection (OR: 2.00, 95%CI: 1.19–3.34) in the multivariate regression (**Table 4**). Infection-free survival in the Kaplan–Meier curve was significantly higher in the high TTR group than that in the low TTR group (**Figure 4**).

## Comparison to Other Tacrolimus Measures

Multivariate regression was also used to examine alternative measures for the characterization of tacrolimus exposure. We separated 1,241 patients into high and low TTR groups by TTR cut-off value. In 1,241 patients overall, increasing the TTR by 10% was associated with reduced patient death (OR = 0.73, 95%CI: 0.63–0.86) and graft loss (OR = 0.53, 95%CI: 0.36–0.80) (**Table 5**). Increasing IPV was an independent risk factor for graft loss, and all alternative tacrolimus measures were predictors for patient death. However, none of the tacrolimus measures were significantly associated with patient and graft survival in the high TTR group. In the low TTR group, increasing TTR by 10% remained independently protective for both patient (OR = 0.60, 95%CI: 0.40–0.93) and graft survival (OR = 0.51, 95%CI: 0.28– 0.92). Only increasing IPV was associated with a higher incidence of graft loss (OR = 1.04, 95%CI: 1.01–1.07).

## DISCUSSION

To the best of our knowledge, this is the first study to assess the effect of tacrolimus TTR on long-term outcomes in living kidney transplantation. In the current study, we found that a TTR above 78% was not only associated with improved graft survival but also with reduced risk of AR and infection. Tacrolimus TTR was more strongly associated with patient and graft survival than mean level, standard deviation (SD), and IPV.

The first reported use of TTR was for the therapeutic use of warfarin, a drug with considerable inter- and intra-patient variability and a narrow therapeutic index, much like tacrolimus. The warfarin TTR cut-off value was arbitrarily determined as 75% (10) or was recommended by European guidelines as being 70% or greater (18). Two studies investigating the use of tacrolimus TTR also arbitrarily set the TTR threshold as 30% in lung transplant (11) or 60% in kidney transplant (12). Although they found that increasing tacrolimus TTR was associated with improved clinical outcomes, the optimal TTR was not determined. The primary aim of maintaining the tacrolimus within the therapeutic range is to control rejection, and so we utilized the ROC curve to estimate the optimal TTR value based on the AR episodes in the first year. The cut-off value was 78%, and the AUC was 0.733. Though the AUC value was fair, the TTR of 78% can differentiate patients with increased risk of graft failure and patient death in the development group very well. Additionally, we further validated the TTR cut-off value and its

TTR Predicts Kidney Transplant Outcomes

TABLE 3 | Univariate and Multivariate

 analysis of clinical

characteristics

 for acute rejection, infection, and patient and graft survival in development

 cohort.

*ATG, antithymocyte globulin; BMI, body mass index; eGFR, estimated glomerular filtration rate; DGF, delayed graft function; HLA, human leukocyte antigen; PRA, panel reactive antibody; TTR, time in therapeutic range.*

TTR Predicts Kidney Transplant Outcomes

*ATG, antithymocyte globulin; BMI, body mass index; eGFR, estimated glomerular filtration rate; DGF, delayed graft function; HLA, human leukocyte antigen; PRA, panel reactive antibody; TTR, time in therapeutic range.*

TABLE 5 | Adjusted Cox regression models for patient and graft survival using different measures of tacrolimus exposure.

*IPV, intra-patient variability; TTR, time in therapeutic range.*

role as an informative predictor in the validation cohort. Of note was the fact that, to accurately estimate TTR, we excluded cases with three or more consecutive missing values of tacrolimus. As the TTR was calculated by the Rosendaal method, which assumed a linear relationship exists between each measured value, that linear interpolation method was used to estimate the missing values (15). When there are three or more consecutive missing values, it is not reliable to apply interpolation, and this is due to the limitation of this technique.

We found that a higher tacrolimus TTR was strongly associated with better graft survival and rejection-free survival. These observations were consistent with the findings from previous kidney transplant and lung transplant analyses, which used the TTR to characterized tacrolimus exposure (11, 12). Notably, we did not find any difference in mean tacrolimus trough level between the high and low TTR groups. However, the high TTR group had much lower SD (1.9 vs. 1.4) and IPV (24.1 vs. 34.2%) of tacrolimus levels than that in low TTR group. Together with the facts that increasing SD and IPV of tacrolimus levels are independent risk factors for rejection and graft loss (6, 19), a higher TTR can thus predict better outcomes.

Interestingly, we found that TTR > 78% was associated with reduced infection, which was corroborated by the lung transplant study that found that increasing the TTR by 10% was associated with a decreased likelihood of infection (OR 0.81, 95%CI: 0.67– 0.97) (11). We previously found that the increasing tacrolimus trough level at the first month was associated with infection, and those that had a tacrolimus trough level >7.15 ng/ml experienced a much higher incidence of infection (20). In the high TTR group, of 9,756 tacrolimus measures in 12 months, 8.0% had level >8 ng/ml, significantly lower than that in the low TTR group (14.4%, p < 0.001). Similar findings were confirmed in the first 3 months (3.2 vs. 6.4%, p < 0.001), indicating that the low TTR group had more patients with over-immunosuppression. Thus, the low TTR group may have a higher incidence of infection. However, when infection is diagnosed, a dose reduction is usually required. That erratic change of the tacrolimus level will result in a lower TTR.

The effects of several tacrolimus exposure characteristics have been investigated in kidney transplantation. A single measurement of an increased tacrolimus trough level soon after a kidney transplant has been associated with a decreased risk of AR and biopsy-proven AR (21, 22). However, a single timepoint measurement may not be meaningful because tacrolimus trough levels are produced by dynamic rather than stable metabolic processes. Recently, a pooled analysis across four randomized trials found that the average tacrolimus level in first 12 months <4.0 ng/ml was associated with an increased incidence of BPAR (HR = 6.33, p < 0.00001) (7). Sapir-Pichhadze et al. conducted a retrospective cohort investigation of kidney transplants, examining the effect of the SD of tacrolimus levels on the composite endpoint (late allograft rejection, glomerulopathy, and total graft loss). They found that, for every 1-unit increase in SD, there was a 27% increase in the adjusted hazard of the composite endpoint (HR 1.27, 95%CI: 1.03–1.56) (6). Additional study using the mean level and SD to characterize tacrolimus exposure yielded similar findings (23, 24). Importantly, we found that the tacrolimus TTR was more strongly associated with patient and graft survival than mean level and SD. A subgroup analysis of the high TTR group found the predictive effect of all alternative measures disappeared. SD may poorly characterize levels that are consistently above or below the target range, and mean value cannot differentiate erratic changes between high and low levels, but TTR accounts for the concentration, variability, and the time between levels simultaneously. Together with our finding that a higher TTR can eliminate a large part of SD (1.4 vs. 1.9, p < 0.001), we found that that the TTR may better characterize exposure compared to the mean value and SD.

Increasing the IPV of tacrolimus is also a risk factor for inferior graft survival. In a retrospective analysis of 310 adult kidney transplants, an IPV >30% independently related to death censored graft loss (HR = 2.613, 95%CI: 1.361–5.016) and dnDSAs (HR = 2.925, 95%CI: 1.473–5.807) (25). However, we found the high TTR group had a much lower IPV than that in low TTR group (24 vs. 34%, p < 0.001), and tacrolimus TTR is more strongly associated with patient and graft survival than IPV, indicating that the TTR may be a better index of tacrolimus monitoring. What's more, the real-time clinical utility of IPV is limited because it cannot be generally computed at the bedside nor making clinical decisions based on the result. The ease of estimating TAC TTR supports its use as a riskstratification and decision-making tool. Additionally, high IPV is mainly due to non-adherence (26), and the utilization of TTR may also stratify those with a high non-attendance rate in the outpatient clinic. As suggested by studies involving Warfarin, a less frequent dose change and better adherence contributed to a higher TTR level (27). Interventions to minimize the nonadherence, including the timing and dosing, may also improve tacrolimus TTR in kidney transplants and consequently better long-term allograft outcomes. In addition, a high-fat meal and administration of CYP3A4-interfering medications had a significant impact on the rate of TAC absorption and metabolism (28, 29), and so avoiding these factors may improve the TTR as well.

There are several limitations when interpreting our results. First, due to its retrospective nature, we could only establish an association between the TTR and the clinical outcomes. These findings should be confirmed with a prospective assessment. Second, tacrolimus was measured at discrete time points, and missing values were estimated by linear interpolation method. Though we excluded those with three or more consecutive missing values, estimated tacrolimus values may not have accurately reflected the real exposures. Third, the cut-off value of the TTR and its predictive role were based on our target range, whether the TTR remains associated with patient and graft survival in other tacrolimus target ranges was unknown. Finally, we only analyzed living kidney transplants; these observations therefore need to be externally validated in other transplant categories, such as deceased donor and ABO-incompatible kidney transplants.

#### CONCLUSION

Tacrolimus TTR monitoring was predictive in achieving well-managed tacrolimus-based immunosuppression in living kidney transplants. Future prospective investigations should be conducted to confirm these findings.

#### REFERENCES

#### DATA AVAILABILITY STATEMENT

The datasets analyzed in this article are not publicly available. Requests to access the datasets should be directed to<EMAIL_ADDRESS>
#### ETHICS STATEMENT

The studies involving human participants were reviewed and approved by the Ethical Committee of West China Hospital, Sichuan University. The patients/participants provided their written informed consent to participate in this study.

#### AUTHOR CONTRIBUTIONS

TS, SY, and TL participated in research design. TS and SY participated in the writing of the paper. YJ, ZH, JL, ZW, XL, and JZ participated in the data collection and data wash. YF, SY, TS, XW, and LL participated in data analysis.

#### FUNDING

This study was supported by the Natural Science Foundation of China under Grant Nos. 81870513, 81470980, and 81600584; the 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University under Grant No. ZY2016104; Youth researcher funding of Sichuan University under Grant No. 2017SCU11042; and Research funding of the Sichuan health and family planning commission under Grant Nos. 17PJ159, 18PJ434, and 18PJ453.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu. 2019.02912/full#supplementary-material

Supplementary Figure 1 | A flow chart to describe the enrollment of patients.

superior one-year outcomes in lung transplant recipients. Am J Transplant. (2018) 18:1527–33. doi: 10.1111/ajt.14723

sensitized renal transplant recipients. Transplantation. (2014) 97:986–91. doi: 10.1097/TP.0000000000000149

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Song, Yin, Jiang, Huang, Liu, Wang, Li, Zeng, Fan, Wang, Li and Lin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Phenotypic and Transcriptomic Lymphocytes Changes in Allograft Recipients After Intravenous Immunoglobulin Therapy in Kidney Transplant Recipients

Caroline Pilon1,2,3, Jeremy Bigot 2,3, Cynthia Grondin1 , Allan Thiolat 2,3, Philippe Lang2,3,4 , José L. Cohen1,2,3, Philippe Grimbert 1,2,3,4 and Marie Matignon1,2,3,4 \*

1 APHP (Assistance Publique-Hôpitaux de Paris), Hôpital H. Mondor-A. Chenevier, Centre d'Investigation Clinique Biothérapie, Créteil, France, 2 Université Paris-Est, UMR\_S955, UPEC, Créteil, France, 3 Inserm, U955, Equipe 21, Créteil, France, 4 APHP (Assistance Publique-Hôpitaux de Paris), Hôpital H. Mondor-A. Chenevier, Nephrology and Transplantation Department, Créteil, France

#### Edited by:

Guseppe Grandaliano, University of Foggia, Italy

#### Reviewed by:

Paolo Cravedi, Icahn School of Medicine at Mount Sinai, United States Nicolas Degauque, INSERM U1064 Centre de Recherche en Transplantation et Immunologie, France Ondrej Viklicky, Institute for Clinical and Experimental Medicine (IKEM), Czechia

> \*Correspondence: Marie Matignon<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Alloimmunity and Transplantation, a section of the journal Frontiers in Immunology

Received: 22 September 2019 Accepted: 08 January 2020 Published: 24 January 2020

#### Citation:

Pilon C, Bigot J, Grondin C, Thiolat A, Lang P, Cohen JL, Grimbert P and Matignon M (2020) Phenotypic and Transcriptomic Lymphocytes Changes in Allograft Recipients After Intravenous Immunoglobulin Therapy in Kidney Transplant Recipients. Front. Immunol. 11:34. doi: 10.3389/fimmu.2020.00034 High dose intravenous immunoglobulin (IVIG) are widely used after kidney transplantation and its biological effect on T and B cell phenotype in the context of maintenance immunosuppression was not documented yet. We designed a monocentric prospective cohort study of kidney allograft recipients with anti-HLA donor specific antibodies (DSA) without acute rejection on screening biopsies treated with prophylactic high-dose IVIG (2 g/kg) monthly for 2 months. Any previous treatment with Rituximab was an exclusion criterion. We performed an extensive analysis of phenotypic and transcriptomic T and B lymphocytes changes and serum cytokines after treatment (day 60). Twelve kidney transplant recipients who completed at least two courses of high-dose IVIG (2 g/kg) were included in a median time of 45 (12–132) months after transplant. Anti-HLA DSA characteristics were similar before and after treatment. At D60, PBMC population distribution was similar to the day before the first infusion. CD8+ CD45RA+ T cells and naïve B-cells (Bm2+) decreased (P = 0.03 and P = 0.012, respectively) whereas Bm1 (mature B-cells) increased (P = 0.004). RORγt serum mRNA transcription factor and CD3 serum mRNA increased 60 days after IVIG (P = 0.02 for both). Among the 25 cytokines tested, only IL-18 serum concentration significantly decreased at D60 (P = 0.03). In conclusion, high dose IVIG induced limited B cell and T cell phenotype modifications that could lead to anti-HLA DSA decrease. However, no clinical effect has been isolated and the real benefit of prophylactic use of IVIG after kidney transplantation merits to be questioned.

Keywords: kidney transplantation, high-dose intravenous immunoglobulin, donor specific antibodies, lymphocytes phenotype, immunomodulation

## INTRODUCTION

Intravenous immunoglobulin (IVIG) is the most highly used therapies for immunodeficiencies, autoimmune, and inflammatory diseases (1). Despite the wide utilization of IVIG, the mechanisms supporting their immunomodulation properties remain not fully elucidated and somewhat controversial. Low-doses IVIG (0.3 g/kg) in common variable immunodeficiency induces proliferation and immunoglobulin synthesis from B cells (2). In the context of autoimmune and inflammatory diseases, dose of IVIG were elevated (2 g/kg) and their mechanisms of action were described to depend on Fc and/or F(ab')2 fragments (3). IVIG inhibit the activation and function of various innate immune cells such as dendritic cells, monocytes, macrophages, neutrophils cells, and NK cells (3) and neutralize activated complement components (3). In addition, IVIG modulate B-cell functions with a significant reduction in serum levels of BAFF (4) and plasma cells. In turns, IVIG enhances and restores the functions of Treg cells, induces apoptosis of activated effector T lymphocytes and down regulates the production of inflammatory cytokines (3). In addition, IVIG inhibits activation of endothelial cells, expression of adhesion molecules and secretion of soluble mediators (5).

In the field of kidney allograft transplantation, a number of preventive treatments in sensitized patients before transplant have been reported including high-dose IVIG and/or anti-CD20 antibody and/or plasmapheresis and/or bortezomib and/or monoclonal antibody to C5 (6–12). In the only randomized double-blinded trial analyzing high-dose IVIG in sensitized kidney allograft recipients, IVIG group displayed lower panel reactive antibody (PRA), higher rate of deceaseddonor transplants, shorter time to transplantation, and similar 2-year graft survival albeit at the expense of higher rate of rejection (8). In another randomized clinical trial, adding rituximab to high-dose IVIG induced a significant decrease in acute antibody mediated rejection (ABMR) and improved kidney allograft function after transplant compared to IVIG alone (12). A retrospective study analyzed the benefit of adding plasmapheresis and rituximab to high-dose IVIG and depicted less microvascular inflammation and histological changes of chronic ABMR in the more intensive treated group compared to a historical cohort of control patients (11). Finally, the accurate role of IVIG in such clinical context remains difficult to establish and analysis of their action on humoral response is difficult to define since IVIG are mostly used in combined therapy strategies. Moreover, in the context of kidney transplant recipients receiving maintenance immunosuppressive drugs, the biological effect of high-dose IVIG treatment on T and B cell phenotype was not evaluated yet. Here, we proposed to analyze in vivo phenotypic and transcriptomic lymphocytes changes in kidney allograft recipients treated monthly with prophylactic high-dose IVIG (2 g/kg) because of de novo anti-HLA DSA (dn DSA) or preexisted DSA.

## PATIENTS AND METHODS

#### Study Design and Patients

We designed a monocentric prospective cohort study of kidney allograft recipients with significant anti-HLA DSA (before transplant (presensitized) or dn DSA) without acute rejection on protocol kidney allograft biopsy. A part of the cohort was treated with prophylactic high-dose IVIG (2 g/kg) monthly during 2 months between January 2013 and January 2014 and none were treated before with Rituximab. Prophylactic treatment was decided because of significant anti-HLA DSA (before transplant (presensitized) or dn DSA). Protocol kidney allograft biopsies were performed in our center to follow kidney allograft recipients with DSA before transplantation and dn DSA as acute ABMR is significantly higher in those patients (13, 14). Demographic and clinical information were collected before and after kidney transplantation. Tolerance of IVIG treatment were collected. Glomerular filtration rate (eGFR) was estimated with MDRD formula (15). Acute rejections were biopsy-proven in all cases and classified according to updated Banff classification (16). Allograft loss was defined with eGFR < 15 ml/min/1.73 m2 or the need for dialysis. This study was reviewed and approved by the Paris-4 institutional review board (CPP-APHP\_2021).

## HLA Typing and Anti-HLA Donor Specific Antibodies Identification

HLA type was determined using high resolution typing for all donors and recipients. Participants were typed for class I loci (A, B, and CW) and class II loci (DR, DQ, and DP). Serum samples were systematically collected before IVIG treatment and 1 month after the last course of high dose IVIG to evaluate HLA sensitization. All serum samples were assessed with Luminex assays to determine the specificity of HLA class I and II IgG donor specific antibodies (DSA) (One Lambda Inc, CA). A baseline mean fluorescence intensity (MFI) value > 500 was considered positive. DSA characteristics analyzed included the absolute number, the highest MFI (MFImax) and the sum of MFI (MFIsum).

### Human Cell Isolation and Flow Cytometry

Peripheral blood was obtained from patients before each high-dose IVIG infusion (day 0 and day 30) and 1 month after completion of the two courses (day 60). Peripheral blood mononuclear cells (PBMCs) were isolated with lymphocyte separation medium (Laboratoires Eurobio, Les Ulis, France) and resuspended in phosphate-buffered saline (PBS; Life Technologies; Thermo Fisher Scientific, Waltham, MA) with 3% fetal bovine serum (FBS; Gibco, Life Technologies; Thermo Fisher Scientific). PBMCs were stained with various mAb combinations for 20 min at 4◦C in staining buffer (PBS with 3% FBS). The directly conjugated mAbs anti-CD19-V500 (clone HIB19), CD56-APC (clone B159), CD14-PE-Cy7 (clone M5E2), CD3-V450 (clone UCHT1), CD4-PE (clone RPA-T4), CD8-APC (clone RPA-T8), CD45RA-FITC (clone L48), CD45RO-PerCP (clone UCHL1), CD38-PE-Cy7 (clone HB7) were supplied by BD Biosciences (France), IgD-FITC (clone IADB6), CD27-PE (clone IA4CD27) by Beckman Coulter (France), and Foxp3-eF450 (clone PCH101) by eBioscience (Thermo Fisher Scientific). Data were processed using FlowJo soft-ware (FlowJo LLC, Ashland, OR).

The gating strategy of the different cells subsets is presented in **Supplemental Figure 1**.

## RNA Isolation, Preamplification, and Reverse Transcription–Quantitative Polymerase Chain Reaction

Expression levels of 13 genes were analyzed using quantitative polymerase chain reaction (qPCR). Messenger RNA (mRNA) was extracted from PBMCs lysate (day 0, day 30, and day 60) using the RNeasy MiniKit (Qiagen, Hilden, Germany), according to the manufacturer's instructions and quantified on a nanodrop spectrophotometer. Total RNA was then reverse transcribed to complementary DNA (cDNA) with reverse transcriptase (Thermo Scientific, Courtaboeuf, France). Realtime quantitative PCR was performed with 13 commercially available primers and probe sets (Applied Biosystems, Foster City, CA) (HPRT: Hs99999909\_m1, CD19: Hs00174333\_m1, CD32a: Hs00234969\_m1, CD32b: Hs00269610\_m1, BAFF-R: Hs00606874\_g1, BAFF: Hs00198106\_m1, RORγT: Hs01076122\_m1, Tbet: Hs00203436\_m1, GATA-3: Hs00231122\_m1, CD3: Hs00174158\_m1, TGFβ1: Hs00998133\_m1, Fas: Hs00236330\_m1, FasL: Hs00181225\_m1, CD4: Hs01058407\_m1). This mechanistically informative panel of 13 mRNAs was designed based on our single center experience and as informed from the literature (17–19). The 2−11ct method was used to calculate the abundance of mRNAs in the samples and relative to reference controls. All samples were tested in duplicate in 96-well plates with the 7900HT fast real-time PCR system (Applied Biosystems). HPRT1 was used as an endogenous control to normalize RNA amounts.

#### Cytokine Detection in Serum

Serum were harvested after centrifugation of whole blood (collected without any additives) from each patient at day 0, 30 and 60, and stored at −80◦C. Cytokines were quantified using the Cytokine 25-Plex human ProcartaPlex Panel 1B with Luminexbased technology as specified by manufacturer (Thermo Scientific, Courtaboeuf, France). The following cytokines were analyzed: GM-CSF; IFN-α; IFN-γ; IL-1 α; IL-1 β; IL-1RA; IL-2; IL-4; IL-5; IL-6; IL-7; IL-9; IL-10; IL-12 p70; IL-13; IL-15; IL-17A; IL-18; IL-21; IL-22; IL-23; IL-27; IL-31; TNF-α; TNF-β/LTA.

#### Statistical Analysis

Each patient was his own control. Continuous variables were expressed in mean Standard Deviation (SD) or median Interquartile Range (IQR) as appropriate. Categorical variables were expressed in N (%). Statistical analyses were adapted to data distribution (Mann–Whitney test, and unpaired or paired t-test). A P-value below than 0.05 was considered to be significant. Statistical analyses were performed using GraphPad Prism software (GraphPad Software, La Jolla, CA).

## RESULTS

## Patients Characteristics

A total of 21 patients were included in the study. Among those, 12 were treated with prophylactic high-dose IVIG and 9 were not. All patients from treatment group completed at least two courses of high-dose IVIG (2 g/kg). Reason of prophylactic IVIG treatment was anti-HLA DSA detection

without acute ABMR lesions on protocol biopsy. Clinical characteristics and transplant courses are depicted in **Table 1**. DSA characteristics are presented in **Table 2**. Both groups were comparable (**Supplemental Table 1**).

Regarding IVIG treated patients, median delay of treatment was 45 (12–132) months after kidney transplant. Among the N = 8 patients receiving induction therapy, N = 4 were treated with thymoglobulin and N = 4 with RIL-2 antibody. One patient was treated 1 month before IVIG. Three patients presented with one episode of acute T cell mediated rejection, 24, 51, and 67 months before high dose IVIG treatment. All of them received steroids. The one occurring 24 months before was also treated with thymoglobulin. Delay from acute rejection to IVIG treatment and immunophenotyping analysis seemed to be reasonable as it was always more than 1 year. None of them received Rituximab before high-dose IVIG infusions. Delay between thymoglobulin and IVIG treatment was more than 12 months in all but one patient. Screening biopsies at the time of anti-HLA DSA detection were available in all patients (**Supplemental Table 2**). Histological analysis was strictly normal in nine patients. Two

biopsies presented with isolated peritubular capillaritis grade 1 with no C4d positive staining nor glomerulitis. Chronic lesions included transplant glomerulopathy (N = 1), grade III IFTA (N = 3), and grade II IFTA (N = 2). DSA characteristics at the time of first IVIG infusion and 60 days after were described in **Table 2**. No difference can be isolated between the DSA before and after treatment (as in IVIG-free group—**Table 2**). One patient developed an acute ABMR 12 months after IVIG treatment completion. Clinical tolerance of high-dose IVIG was good without any adverse events besides benign headache in N = 4 patients. None of them presented with acute kidney injury.

#### PBMC Phenotype Evolution After High Dose IVIG

We first analyzed the 21 patients included treated or not. Results are shown in **Table 3**. No difference could be isolated neither in PBMC population at day 30 and day 60 compared to day 0 (T-cell, B-cell and NK-cell) nor in subtypes.

Then, as shown in **Figure 1** and **Table 4**, we performed a matched analysis in the 12 treated patients and PBMC population distribution was similar whatever time before or after treatment and whatever the population considered: monocytes (CD14), B-cell lymphocytes (CD19), NK cells (CD56), NKT cells (CD3+CD56+) and/or T-cell lymphocytes (CD4 and CD8 among CD3). We next analyzed T-cell lymphocytes: CD45RA+ T cells (probably naive), CD45RO+ T cells (probably memory) and regulatory T cells (CD4+CD25++Foxp3+). Only CD8+ CD45RA+ cells decreased significantly at D60 (**Figure 1C**). We also analyzed T reg subtypes according to Miyara description (20). No changes could be isolated at day 30 and 60. We studied B-cell lymphocytes using Bm1-5 classification (**Figure 1B** and **Table 3**) (21). Two subgroups of B-cells were modified along the treatment. While Bm1 (mature B-cells) increased significantly (P = 0.004), Bm2 (naïve B-cells) decreased significantly (P = 0.012). No significant changes were observed on the other Bcells subsets. Next, we performed a discriminative analysis based on the induction therapy in the treated patients. According to small number of patients in each group (RIL2 antibody-group 2, thymoglobulin—group 1 and no induction—group 0), we analyzed variation considering each patient as his own control. No significant results could be highlighted excepted increase of Bm1 proportion in no induction treatment group at day 60 after treatment (**Supplemental Table 2**).

#### PBMC mRNA Quantification Changes After High Dose IVIG

Transcript levels of molecules involved in inhibitory B-cell profiles (CD32 isoforms and the B-cell scaffold protein ankyrin repeats 1 BANK1), in B-cell survival (the B-cell activating factor BAFF and its receptor: BAFF-R), in T-cell differentiation (Th1, Th2, and Th17) and in apoptosis in the PBMC were analyzed in the treated patients. We justified the choice of targeted genes in **Supplemental Data**. Data were analyzed before treatment, at day 30 and at day 60 after two high dose IVIG infusions (**Table 3**). Levels of RORγt mRNA transcription factor and CD3 mRNA increased significantly 60 days after IVIG treatment beginning (P = 0.02 and P = 0.02, respectively). Correlation coefficient between CD3 transcriptomic and proteomic/cellular analysis was not significant (**Supplemental Figure 2**).

Discriminative analysis according to induction therapy did not reveal significant difference at day 30 and 60 compared to baseline (day 0) (**Supplemental Table 3**).

## Circulating Serum Cytokines Along High Dose IVIG Treatment

Among the 25 cytokines analyzed in patients serum treated with IVIG, 11 where undetectable (IL-1α, IL-2, IL-5, IL-9, IL-10, IL-12p70, IL-13, IL-23, IL-31, IFNα, TNFβ), 9 where sporadically

detected by one or two patients (IL-1β, IL-4, IL-6, IL-15, IL-17A, IL-21, IL-22, IL-27) and 5 were detected in more than 5 patients and are shown in **Figure 2** and **Table 3** (IL-7, IL-1Rα, IL-18, IFNγ, TNFα). Only IL-18 serum concentration significantly decreased at D60 (P = 0.03).

Considering discriminative analysis according to induction therapy, we could not analyze cytokines in each group due to small number of positive patients.

#### DISCUSSION

Prophylactic high dose IVIG has been used at the time of transplantation in high immunological risk recipients but analysis of their true action on humoral response is difficult to define since IVIG is mostly used as combined therapy (8, 22). In the context of de novo DSA in kidney allograft recipients, prophylactic use of high dose IVIG did not prevent acute ABMR and had minimal effects on DSA outcome (17). We provided here an extensive in vivo phenotypic and transcriptomic analysis in 12 patients treated with prophylactic high dose IVIG after kidney transplantation in patients with anti-HLA DSA without acute rejection and therefore without any other treatment associated. So more, the absence of acute rejection means the absence of immunological mechanisms activation or subclinical which will not interfere with IVIG actions.

Considering B lymphocytes, we showed first that proportion of naïve B-cells (Bm2) decreased significantly after high dose IVIG. This population was associated before and after transplant with anti-HLA DSA development within the first year after transplant (23, 24). In addition, belimumab, an anti-B lymphocyte stimulator (BLyS) antibody, associated at the time of transplant with standard transplant immunosuppression, decreased significantly naïve B-cells 24 weeks after transplant and de-novo IgG antibody formation (25). High dose IVIG could via the decrease of naïve B-cells (Bm2) limits de-novo IgG DSA formation. However, in our study, no early effect on DSA MFI has been reported. A later analysis merits to be performed in the future to look for a sustained effect on naïve B-cells and DSA.

In our study, high dose IVIG increased significantly, the proportion of memory B cells. Lower proportion of memory B cell before transplant, has been associated with high immunization levels (24) while higher proportion of memory B cell after transplant, has been described in operationally tolerant patients (no DSA and no immunosuppressive treatment) (26). In addition, in patients treated with belimumab proportion of memory B cell increased throughout the treatment with lower de-novo DSA (25). Whether increasing memory B-cell could decrease anti-HLA DSA production in our patients with immunomodulatory effects should be analyzed further.

High dose IVIG on T cell highlighted the decrease of the proportion of CD8+ CD45RA+ T cell after two infusions suggesting decrease of naïve T cell. Decreased frequency of CD8+ CD45RA+ and CD4+ CD45RA+ T cells have never been associated with acute rejection but with infection in older kidney recipients (> 60 years) (27). Increasing naïve T cells after transplantation could decrease memory T cells, interactions between T and B cells and may prevent not only alloantibody formation but also generation of long-lived memory T cells improving allograft survival. It is now well established that CD4+ and CD8+ memory T cells could contribute to allograft rejection and pose a major barrier to tolerance induction (28, 29).

RORγt mRNA transcripts, one nuclear factor involved in Th17 cells generation (30), increased significantly after high dose IVIG but without any changes in Th17 pathway cytokines. However, we did not analyzed RORγt using flow cytometry. Th17 TABLE 4 | PBMC populations distribution, serum cytokines and PBMC mRNA transcripts evolutions after IVIG treatment.

cells and their cytokines, IL-17, IL-22, IFNγ, IL-6 and TNF-α, play a significant role in the development of acute and chronic allograft injury after organ transplantation (31). CD3 mRNA transcripts increased significantly while CD3 cells proportion

plot represent % of positive cells with 5–95% Whiskers. Results were compared with Wilcoxon signed rank test.

remained stable. Only five cytokines could be analyzed because of low expression of cytokines in our patients. IL-18, which is a potent pro-inflammatory cytokine involved in the host defense by upregulating both innate and acquired immune

On the left, % of CD45RA (blanked) vs. % of CD45RO (dark gray) in CD4+ cells. On the right, % of CD45RA (blanked) vs. % of CD45RO (dark gray) in CD8+ cells. Box

responses especially Th1 responses (32), decreased significantly after IVIG high dose infusion. The main role of IL-18 is to crucially stimulate lymphocytes to produce the IFN-γ and regulate macrophages activity (32). However, in our study, serum levels decrease of IL-18 was not followed by a significant effect on serum levels of IFN-γ. Conclusion about transcripts levels modifications and cytokines expression after high dose IVIG could not be formulated.

Recently, Yabu et al. showed that immune profiles could predict response to desensitization therapy in highly HLAsensitized kidney transplant candidates (33). More precisely, authors depicted a combination of transitional B cell and regulatory T cell frequencies before initiation of desensitization therapy that could distinguish responders from non-responders. The response to therapy was assessed by a predefined decrease of 5% or greater in cumulative calculated panel reactive antibodies. So more, one transcript, TRAF3IP3 could also distinguish responders from non-responders. However, we could not isolate responders from non-responders in our cohort because of the small number of patients, the absence of significant changes in DSA and only one acute ABMR episode after treatment.

The major limit of our study was the small number of patients included. However, after kidney allograft transplantation, high dose IVIG are never infused alone. Indications after kidney transplantation include (i) the prevention of acute ABMR in presensitized patients associated with thymoglobulin induction therapy and plasmapheresis and/or rituximab (ii) treatment of acute ABMR associated with plasmapheresis (11). In the first indication, no study evaluating prophylactic treatment in kidney deceased donor recipients is available. So more, prophylactic high doses IVIG are not used in clinical practice in patients with dn DSA and we stopped our pilot study because of failure to prevent acute ABMR (17). Considering clinical data without a net benefit and the cost of high dose IVIG, ∼\$6,500 for a single 140 g IVIG treatment (34), we could not treat more patients and our data in vivo could not be expanded. Meanwhile, we would like to highlight that this is the sole study analyzing high dose IVIG in vivo effect after kidney transplantation.

Taken together, our data (clinical and experimental) suggested that the benefits of high dose IVIG after kidney transplantation are limited. Furthermore, high dose IVIG have been associated with more tubular macrovacuoles and chronic tubulointerstitial changes after kidney transplantation (35, 36). Our results remain to be confirmed in a larger population which could lead to deep modifications of the current use of high dose IVIG in clinical practice after kidney transplantation.

In conclusion, we present here the first study analyzing in vivo prophylactic high dose IVIG effects on T and B cell phenotype in kidney allograft recipients with de novo DSA. Our results trend to suggest that high dose IVIG induce limited modifications in B and T cell phenotype including decrease of naïve B cell and CD8+ T cell and increase of memory B cell. These modifications could lead to immunomodulation and limit anti-HLA DSA production. However, our previously clinical data suggested that kidney allograft recipients with DSA treated preventively with high dose IVIG showed similar AMR rate than non-treated group (17) and no DSA modifications could be isolated in this study.

## DATA AVAILABILITY STATEMENT

The datasets generated for this study are available on request to the corresponding author.

#### ETHICS STATEMENT

The studies involving human participants were reviewed and approved by APHP-Saint Louis. The patients/participants provided their written informed consent to participate in this study.

## AUTHOR CONTRIBUTIONS

CP, JB, CG, PG, and MM: conceptualization, methodology, and data curation. CP: software. CP, JB, CG, PL, JC, AT, PG, and MM: validation and formal analysis. MM: resources and supervision.

## REFERENCES

CP and MM: writing—original draft preparation. CP, JB, AT, JC, PG, and MM: writing—review and editing.

#### FUNDING

The authors declare that this study received funding from CSL Behring. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu. 2020.00034/full#supplementary-material

Am J Transplant. (2007) 7:1185–92. doi: 10.1111/j.1600-6143.2007.0 1752.x

program of proinflammatory IL-17+ T helper cells. Cell. (2006) 126:1121–33. doi: 10.1016/j.cell.2006.07.035

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Pilon, Bigot, Grondin, Thiolat, Lang, Cohen, Grimbert and Matignon. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Immune Cell Infiltrate in Chronic-Active Antibody-Mediated Rejection

Kasia A. Sablik 1 \*, Ekaterina S. Jordanova2 , Noelle Pocorni 2 , Marian C. Clahsen-van Groningen3† and Michiel G. H. Betjes 1†

*1 Department of Nephrology and Transplantation, Erasmus Medical Center, Rotterdam, Netherlands, 2 Department of Gynecology, Center for Gynecologic Oncology, Amsterdam UMC, Amsterdam, Netherlands, 3 Department of Pathology, Erasmus Medical Center, Rotterdam, Netherlands*

Background: Little is known about immune cell infiltrate type in the kidney allograft of patients with chronic-active antibody-mediated rejection (c-aABMR).

Methods: In this study, multiplex immunofluorescent staining was performed on 20 cases of biopsy-proven c-aABMR. T-cell subsets (CD3, CD8, Foxp3, and granzyme B), macrophages (CD68 and CD163), B cells (CD20), and natural killer cells (CD57) were identified and counted in the glomeruli (cells/glomerulus) and the tubulointerstitial (TI) compartment [cells/high-power field (HPF)].

#### Edited by:

*Guseppe Grandaliano, University of Foggia, Italy*

#### Reviewed by:

*Luigi Biancone, University of Turin, Italy Theresa Hautz, Innsbruck Medical University, Austria*

> \*Correspondence: *Kasia A. Sablik<EMAIL_ADDRESS>
*†These authors have contributed equally to this work*

#### Specialty section:

*This article was submitted to Alloimmunity and Transplantation, a section of the journal Frontiers in Immunology*

Received: *06 July 2019* Accepted: *19 December 2019* Published: *04 February 2020*

#### Citation:

*Sablik KA, Jordanova ES, Pocorni N, Clahsen-van Groningen MC and Betjes MGH (2020) Immune Cell Infiltrate in Chronic-Active Antibody-Mediated Rejection. Front. Immunol. 10:3106. doi: 10.3389/fimmu.2019.03106* Results: In the glomerulus, T cells and macrophages were the dominant cell types with a mean of 5.5 CD3+ cells/glomerulus and 4 CD68+ cells/glomerulus. The majority of T cells was CD8+ (62%), and most macrophages were CD68+CD163+ (68%). The TI compartment showed a mean of 116 CD3+ cells/HPF, of which 54% were CD8+. Macrophage count was 21.5 cells/HPF with 39% CD68+CD163+. CD20+ cells were sporadically present in glomeruli, whereas B-cell aggregates in the TI compartment were frequently observed. Natural killer cells were rarely identified. Remarkably, increased numbers of CD3+FoxP3+ cells in the TI compartment were associated with decreased graft survival (*p* = 0.004).

Conclusions: Renal allograft biopsies showing c-aABMR show a predominance of infiltrating CD8+ T cells, and increased numbers of interstitial FoxP3+ T cells are associated with inferior allograft survival.

Keywords: kidney transplantation, pathology, chronic rejection in renal transplant, antibody-mediated allograft rejection, immune cell

## INTRODUCTION

The renal biopsies of patients with chronic-active antibody-mediated rejection (c-aABMR) have defining histomorphological lesions (1). These characteristic lesions include double contours of the glomerular basement membrane (transplant glomeropathy) and/or severe peritubular capillary basement membrane multilayering. In addition, evidence of current or recent antibody interaction with the vascular endothelium is provided by either linear C4d staining in peritubular capillaries or moderate microvascular inflammation [(g + ptc) ≥ 2] (2). The presence of donor-specific antibodies underlies c-aABMR, but the influx of inflammatory cells and rate of loss of renal function may vary substantially.

Previously, different studies have reported on the inflammatory cell types involved in renal allograft rejection. Hidalgo et al. provided evidence for a possible effector role for natural killer (NK) cells in endothelial injury during ABMR (3). In addition, ABMR is associated with both glomerular and interstitial monocyte infiltration (4–7). Mengel et al. showed the importance of inflammatory infiltrates in protocol biopsies, as they were independently associated with allograft survival, regardless of their location (8). Furthermore, activated cytotoxic T cells are known to play an important role in the inflammatory activity and destruction of allograft tissue (9). The increased presence of cytotoxic granules such as granzyme B have been associated with acute rejection (10–12). Similarly, FoxP3+ T cells [T regulatory cells (Tregs)] have been identified as potential crucial players in inflammatory disease and allograft rejection (13–15).

However, the majority of studies has focused on acute rejection (both TCMR and ABMR), and there is currently a lack of data on the presence and clinical relevance of inflammatory cells in renal allografts of patients with c-aABMR.

In the current study, we used multiplex immunofluorescent (IF) staining to assess the inflammatory cell composition in the renal allograft biopsy of patients with c-aABMR. We report on the presence of various T-cell subtypes, B cells, NK cells, and myeloid cells in both glomeruli and the tubulointerstitial (TI) compartment. In addition, the association between location and quantity of the different inflammatory cells with allograft survival was analyzed.

## MATERIALS AND METHODS

#### Study Population and Material

Twenty patients with biopsy-proven c-aABMR between 2010 and 2014 were included in this retrospective study. Sufficient formalin-fixed paraffin-embedded (FFPE) material after diagnostic process was needed to be included for further analysis. Renal transplant biopsies were all for cause and deemed necessary by the treating nephrologist due to a unexplained decline in renal allograft function with or without new onset proteinuria. All stained slides were re-evaluated and scored by two blinded pathologists according to the Banff 15 criteria (16). Donor-specific antibodies (DSA) were retrospectively assessed for all patients. The study was approved by the Medical Ethical Committee of the Erasmus MC (MEC-2019-0308).

#### Staining

For routine diagnostic analysis, 3µm sections were cut from the FFPE tissue and stained by H&E, periodic acid–Schiff– diastase, and Jones according to standardized diagnostic protocol at the Department of Pathology at the Erasmus Medical Center. Immunofluorescence staining was performed on snapfrozen tissue sections [immunoglobulin G (IgG), IgA, IgM, C3, C1q, kappa, and lambda] to exclude immune-complexmediated disease.

Additional quadruple multiplex IF staining was performed on 4µm FFPE sections. Multiplex IF staining was performed using the antibody combination of CD3, CD8, and granzyme B for CD4+ T cells, CD8+ cytotoxic T cells both with or without granzyme B presence (**Figure 1**). Second, CD20 was used as a B-cell marker, and for the identification of macrophages, the pan macrophage marker CD68 was used in combination with CD163 to distinguish the M2 macrophage subtype (profibrotic) (**Figure 2**). Lastly, a combination of CD3, FoxP3, and CD57 was used to identify CD3+FoxP3+ regulatory T cells and NK cells (**Figure 3**). 4′ ,6-Diamidino-2-phenylindole (DAPI) was used in all stainings to visualize the nuclei. Multiplex IF was performed as previously described by Punt et al. (17). In brief, after deparaffinization, ethylenediaminetetraacetic acid (pH 9) antigen retrieval was performed in a microwave. Next, three different combinations of primary antibodies were applied to the slides. The first mixture consisted of the antibodies anti-CD3 (rabbit polyclonal, ab828; Abcam), anti-CD8 (mouse monoclonal IgG2b,

4B11; Novocastra), and anti-Granzyme B (mouse monoclonal IgG2a, GRB-7, DAKO). The second mixture consisted of the antibodies anti-CD3 (rabbit polyclonal, ab828; Abcam), anti-FoxP3 (mouse monoclonal IgG1, 236A/E7, Abcam), and anti-CD57 (mouse monoclonal IgM, HNK-1; developed in Leiden University Medical Center). The third mixture comprised the antibodies anti-CD20 (mouse-IgG2a, L2G, Ventana), anti-CD163 (rabbit, ab100909, Abcam), and anti-CD68 (mouse-IgG1, 123C3, Ventana). The first combination was visualized using a combination of fluorescent antibody conjugates (Molecular Probes, ThermoFisher): goat antirabbit IgG–Alexa Fluor 546, goat antimouse IgG2b–Alexa Fluor 647, and goat antimouse IgG2a–Alexa Fluor 488. The second combination was visualized using goat antirabbit IgG–Alexa Fluor 546, goat antimouse IgG1–Alexa Fluor 647, and goat antimouse IgM–Alexa Fluor 488. The third combination was visualized using goat antimouse IgG2a–Alexa Fluor 546, antirabbit IgG–Alexa Fluor 647, and goat antimouse IgG1–Alexa Fluor 488. The panels were optimized using normal human tonsil and normal renal cortical tissue.

#### Detection and Analysis

Images of the slides were taken for further analysis on a confocal laser scanning microscope in multitrack setting (Zeiss LSM700, Zeiss, Jena, Germany). An LCI Plan-Neofluar 25×/0.8 Imm Korr DIC objective (Zeiss) was used.

If possible, tissue sections were scanned in their entirety. For the glomerular cell counts, all available glomeruli per silverstained tissue were included. The glomerular compartment cell counts were represented as the average number of whole cells per glomeruli. Tubulo-interstitial compartment cell counts were represented as the average number of whole cells per high-power field (HPF, 40×). A blinded and random selection of 3 HPF was analyzed for the TI compartment cell counts. All cells were counted using the Zen 2.3 SP1 software.

#### Statistical Analysis

Normally distributed data are expressed as mean ± SD, nonnormally distributed data as median (interquartile range). All statistical analysis were performed using Graphpad Prism 6 and SPSS software version 24. Statistical significance was calculated using unpaired t-test for continuous variables, Mann–Whitney U-test for ordinal variables, and chi-squared or Fisher exact test for categorical variables. A P < 0.05 was considered statistically significant.

Graft survival curves, starting at time of c-aABMR diagnosis, were censored for death with functioning graft and analyzed by Kaplan–Meier with log-rank test. For the analysis of association of inflammatory cells with allograft survival, both the glomerular and TI compartment cell count were divided dichotomously based on the mean cell count.

TABLE 1 | Main clinical features at time of chronic-active antibody-mediated rejection (c-aABMR) diagnosis.

\**One patient had both HLA class I and HLA class II DSA present.*

#### RESULTS

#### Baseline Characteristics

Clinical and histological characteristics of the included patients are shown in **Table 1** and **Figure 4**. The mean age of the patients was 54 years at the time of transplant biopsy. Mean time point of biopsy post-transplantation was 3.6 years. Patients were predominantly treated with an immunosuppressive regimen using a combination of calcineurin inhibitors (mainly tacrolimus, 80%) and mycophenolate mofetil (90%). Mean follow-up was 3.4 years (range, 0.7–8.3 years) or until graft failure (either retransplantation or return to dialysis). Two patients died with a functioning graft during follow-up.

Forty-five percent of patients were DSA positive at the time of biopsy, 50% showed linear positive C4d staining of the peritubular capillaries, and all biopsies showed microvascular inflammation. Furthermore, all patients had severe double contours of the glomerular basement membrane (cg) present in their biopsy with moderate to severe chronic damage [interstitial fibrosis and tubular atrophy (IFTA)].

## CD3+, CD8+, Granzyme B+ T Cells

First, we analyzed the number of glomerular T cell (CD3+ T cells), CD8+ T cells (CD3+CD8+ T cells), CD4+ T cells (CD3+CD8− T cells), CD8+granzyme B+ T cells, and CD4+granzyme B+ T cells by quadruple immunostaining. **Figure 5** shows the distribution as well as the mean number of inflammatory cells per glomerulus per biopsy. A mean total of 5.5 CD3+ cells were present per glomerulus with a range of 0.8– 9.6 CD3+ cells. CD8+ T cells were predominant, making up 61.7% of CD3+ T cells with a mean of 3.4 cells per glomerulus. A minority of CD8+ T cells (46%) and CD4+ T cell (23%) showed cytotoxic potential as measured by coexpression of granzyme B. Inflammatory cell counts were then performed for the TI compartment (**Figure 6**). Although substantial variations were observed in the number of infiltrating cells among the biopsies, large areas of CD3+ T cells were abundantly present within the TI compartment. The TI showed a mean CD3+ cell count of 116.2 per HPF. The majority of CD3+ T cells present in the TI

glomerulus per biopsy.

represented CD8+ T cells (53.9%) with an average cell count of 62.6 per HPF followed by CD4+ T cells (46.2%) with 53.6 positive cells per HPF. In contrast to the glomeruli, there were hardly any CD8+ granzyme B+ T cells (7% of total CD3+ T cells, 8.2 cells per HPF) and CD4+ granzyme B+ T cells (1.5% of total CD3+ T cells, 1.7 cells per HPF) present.

No significant association was found for the presence of CD3+ T cells and the T-cell subsets in the glomeruli and TI compartment with regard to allograft survival or DSA presence.

## CD3+, FoxP3+ T Cells, and CD57+ NK Cells

The second quadruple multiplex IF staining identified CD57+ NK cells (CD3−), CD3+FoxP3+ regulatory T cells, and CD3+CD57+ T cells.

The glomeruli showed low counts of CD57+ and CD3+CD57+ cells in this multiplex IF staining (**Figure 5**). Almost 40% of biopsies showed no presence of CD57+ or CD3+FoxP3+ cells in the glomeruli. The remaining biopsies showed a mean of 0.67 CD57+, 0.56 CD3+CD57+, and 0.32 FoxP3+ cells per glomerulus. CD3+CD57+ cytotoxic T cells accounted for 6.7% of CD3+ cells in the glomerulus.

The TI compartment, however, showed a much higher presence of CD3+FoxP3+ T cells with an average of 11.5 cells per HPF. These cells accounted for 8.5% of the CD3+ cells. A clear distinction into two groups was noticeable within the biopsies for CD3+FoxP3+ T cells (high vs. low mean cell count). Fifty percent of biopsies had a high mean cell count of 19.6 positive cells per HPF vs. a low mean cell count of 3.4 positive cells per HPF. The increased presence of CD3+FoxP3+ T cells was significantly associated with a decreased allograft survival (**Figure 7A**). Patients with high CD3+FoxP3+ T cell rates had a graft survival of 2.1 vs. 5.3 years in the patients with low FoxP3 presence (p = 0.004).

Similar to what was observed for the glomeruli, the CD57+ cell count in the TI was low with a mean of 1.7 cells per HPF and CD3+CD57+ T cells accounted for only 0.8% of CD3+ cells in this compartment.

## CD68+, CD163+ Macrophages, and CD20+ B Cells

The third multiplex IF staining panel included markers for macrophages (CD68+), M2 macrophages (CD68+CD163+), and B cells (CD20+).

CD20+ cells were sporadically present in glomeruli with a mean number of 0.16 positive cells per glomerulus. Interestingly, 45% of biopsies hardly contained any B cells in the glomeruli. The macrophages (CD68+ cells) represented mean number of almost four cells per glomerulus. The majority (68%) was CD68+CD163+ with a mean positive cell count of 2.3 per glomerulus. A scattered distribution of macrophages was visible with ranges of 0–6 positive cells per glomerulus. No significant association with graft function or DSA presence was found for macrophage or B cell presence in the glomeruli (data not shown).

In contrast to the glomeruli, the TI compartment showed a higher percentage of CD68+ cells (61%) with a mean positive cell count of 13.2 per HPF. CD68+CD163+ macrophages accounted for 39% of macrophages with a mean of 8.4 positive cells per HPF. The presence of total CD68+ and CD68+CD163+ macrophages in the TI compartment showed a near significant inverse association with graft survival (p = 0.08) (**Figure 7B**).

Furthermore, a mean number of 36.8 positive CD20 cells was counted in the tubulointerstitium. However, as with the CD3+FoxP3+ T cells, a clear distribution into two groups was visible. Forty-five percent of the biopsies were found to present CD20+ cells in nodular formation with a mean of 74.5 CD20 positive cells per HPF. The remaining biopsies reached a mean of 3.4 CD20+ cells per HPF. The distribution in B cell was not significantly associated with graft survival (p = 0.13). However, patients with increased numbers of B cells in the TI compartment

had the tendency to have DSA present in the serum at time of biopsy. However, this was not statistically significant (p = 0.078).

#### DISCUSSION

No detailed description on inflammatory cells in renal allograft biopsies showing c-aABMR is currently available. Through multiplex IF staining, we evaluated inflammatory cell presence in glomeruli and TI compartment and related their presence to renal allograft survival. Our study is the first detailed report on the localization and immunophenotypic composition of inflammatory cells in c-aABMR of the renal allograft. Most notably T cells and macrophages were observed within the glomeruli and/or in the TI compartment. Of interest is the increased presence of FoxP3+ T cells in the TI compartment, which is significantly associated with inferior allograft survival.

Renal biopsies showing c-aABMR demonstrated vast areas of inflammatory cells denoting the presence of an ongoing immune-mediated process. Substantial numbers of T cells and macrophages were present in the glomeruli and TI compartment.

The glomerular compartment predominantly comprised of CD8+ cytotoxic T cells (granzyme B+ and CD57+) and M2 macrophages (CD68+ and CD163+), but there was a relatively low amount of single positive CD57+ NK cells in the glomeruli. Previous reports have provided evidence for the presence of NK cell transcriptomes marking NK cells as an important player in the pathogenesis of c-aABMR (3, 18, 19). Our study using multiplex IF staining could not confirm the presence of these cells as only a small number of NK cells were present in allografts within the setting of caABMR. However, Parkes et al. previously demonstrated that over 50% of increased transcripts in CD16a-activated NK cells are also increased in activated CD8+ T cells. The NK and T cells shared transcripts for effector cytokines, chemokines, and other molecules related to effector cell function (18). Of interest was the presence of CD3+CD57+ T cells in the glomeruli. Several biopsies showed infiltrates of CD3+CD57+

T cells, and their presence accounted for 6.7% of CD3+ cells in the glomerulus. Although these cells have not been further phenotyped, they might indicate the presence of terminally differentiated effector CD8+CD57+ cytotoxic T cell, possessing NK cell-like properties. These cells are known to have strong cytotoxic potential with high expression of both granzyme B and perforin. The expression of these cytolytic molecules is considerably higher in CD8+CD57+ T cells than in their CD57− counterpart (20). This type of T cell is presumed to increase in frequency with chronic immune activation as well as during normal aging (21–23). In addition, Björkström et al. proposed that in the setting of chronic immune activation terminal, CD8+ T cells can acquire the ability to express FcγRIIIA (CD16) (24). CD16 expressed on CD8+ T cells functioned independently from the T-cell receptor and was able to generate effector cytokine production as well as degranulation. CD16 function has been well-studied on NK cells and is best characterized for its role in antibody-dependent cellular cytotoxicity (25). The presence of these cells in combination with the high percentage of granzyme B+ T cells found in the glomeruli suggest possible severe cytotoxic damaging effects in the glomerular compartment (26, 27).

The glomerular compartment also contained high numbers of macrophages with widespread distribution in number of CD68+ cells per glomerulus. This finding is in accordance with previous literature in which macrophages were significantly associated with clinical rejection and severity, regardless of type of rejection (5–7). Although not statistically significant, the increased presence of macrophages in the TI compartment showed a possible association with graft survival. In addition, it was van den Bosch et al. who provided evidence for increased glomerular infiltration with CD68+CD163+ macrophages in caABMR compared to ABMR and TCMR (7). In accordance with this finding, CD68+CD163+ macrophages were the predominant subset in the glomeruli (68%), contrary to the TI compartment (39%).

T cells and macrophages were also the main inflammatory cells in the TI compartment but with a different immunophenotypic distribution. The predominant T cells were either CD4+ or CD8+ T cells and of interest was the observation that, in contrast to the glomeruli, relatively few CD8+ T cells expressed granzyme and/or CD57. The areas of the TI compartment with diffuse cellular infiltrates could suggest a possible contributing role for T cells in caABMR. Previously, Mengel et al. identified the importance of inflammatory cell infiltrates in protocol biopsies, specifically in areas of IFTA (8). These areas are now classified as i-IFTA/t-IFTA and have also been incorporated into the latest Banff meeting report (2). Although we did not find an association for T-cell infiltrates with (inferior) graft survival, further study is needed to assess if i-IFTA and t-IFTA play an important role in the outcome of graft with c-aABMR.

Of interest in the TI compartment are the CD3+FoxP3+ cells. We demonstrated that patients with increased FoxP3+ Tregs in the TI compartment had inferior renal allograft survival compared to those with few Tregs in the TI compartment. Initially, FoxP3 was identified as the transcription molecule required for Treg development (28). Its presence in certain autoimmune diseases suggests an important role in immune tolerance (29, 30). Similarly, several studies regarding transplantation have shown upregulation of FoxP3 during episodes of acute rejection (15, 31, 32). However, the significance of FoxP3+ T cell presence remains uncertain as these studies have shown conflicting data on the relation with graft survival (15, 33–35). For instance, Yapici et al. and Veronese et al. found a correlation between decreased graft survival and an increased density of Foxp3-expressing cells in acute rejection (35, 36).

Our data showing increased presence of FoxP3+ Tregs in caABMR might be interpreted as an end result of widespread Tcell activation, rather than the cause of poor allograft survival (34). This is in accordance with Bunnag et al., who presented FoxP3 presence as a time-dependent feature reflecting chronic inflammation and showed association with IFTA, rather than FoxP3 as an independent predictor of outcome (34).

In addition, the association with inferior graft survival might be related to the potential of these FoxP3+ T cell to easily differentiate into interleukin (IL)-17 producing T helper 17 (Th17) cells, as previously demonstrated in other autoimmune-mediated inflammatory diseases (37). Under normal circumstances, the transcription of FoxP3 in T cells is mainly induced by transformation growth factor-β. However, under proinflammatory conditions involving IL-6, believed to

#### REFERENCES

be present in renal allografts during rejection, T cells from a regulatory pathway can be adapted to an inflammatory pathway resulting in Th17 (38, 39). Th17 possess highly proinflammatory capacities rather than immune-regulatory functions.

This is the first study of this nature, describing inflammatory cell presence in glomeruli and the TI compartment of patients with c-aABMR. However, it does have a small number of samples. The presented data are of great interest and provide further insight into the possible pathogenesis of c-aABMR.

In conclusion, the predominant renal-infiltrating immune cells in renal biopsies of c-aABMR are CD8+ T cells and M2 type macrophages in both the glomeruli and the TI compartment. Interestingly, in c-aABMR, increased numbers of FoxP3-expressing T cells are significantly associated with poor renal allograft survival.

## DATA AVAILABILITY STATEMENT

The raw data supporting the conclusion of this article will be made available upon request. Requests to access the datasets should be directed to Kasia A. Sablik<EMAIL_ADDRESS>
#### ETHICS STATEMENT

The studies involving human participants were reviewed and approved by MEC-2019-0308. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

#### AUTHOR CONTRIBUTIONS

KS: conception and design of the work, acquisition, analysis, and interpretation of data, and writing of the manuscript. EJ: conception of the work, acquisition and analysis of data, and critical revising of the manuscript. NP: acquisition and analysis of data and critical revising of the manuscript. MC: conception and design of the work, acquisition of data, and writing, and critical revising of the manuscript. MB: conception and design of the work, analysis and interpretation of data, and writing and critical revising of the manuscript.

#### ACKNOWLEDGMENTS

The authors wish to thank Thierry vd Bosch, PARTS, Pathology, Erasmus MC, University Medical Center Rotterdam.

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Sablik, Jordanova, Pocorni, Clahsen-van Groningen and Betjes. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Extracellular Vesicles as Mediators of Cellular Crosstalk Between Immune System and Kidney Graft

Marco Quaglia1,2, Sergio Dellepiane1,2,3, Gabriele Guglielmetti 1,2, Guido Merlotti 1,2 , Giuseppe Castellano4 and Vincenzo Cantaluppi 1,2 \*

*1 Nephrology and Kidney Transplantation Unit, Department of Translational Medicine, University of Piemonte Orientale (UPO), Novara, Italy, 2 Center for Autoimmune and Allergic Diseases (CAAD), University of Piemonte Orientale (UPO), Novara, Italy, 3 Division of Hematology/Medical Oncology, Icahn School of Medicine at Mount Sinai Hospital, The Tisch Cancer Institute, New York, NY, United States, 4 Nephrology Dialysis and Transplantation Unit, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy*

Extracellular vesicles (EVs) are known immune-modulators exerting a critical role in kidney transplantation (KT). EV bioactive cargo includes graft antigens, costimulatory/inhibitory molecules, cytokines, growth factors, and functional microRNAs (miRNAs) that may modulate expression of recipient cell genes. As paracrine factors, neutrophil- and macrophage-derived EVs exert immunosuppressive and immune-stimulating effects on dendritic cells, respectively. Dendritic cell-derived EVs mediate alloantigen spreading and modulate antigen presentation to T lymphocytes. At systemic level, EVs exert pleiotropic effects on complement and coagulation. Depending on their biogenesis, they can amplify complement activation or shed complement inhibitors and prevent cell lysis. Likewise, endothelial- and platelet-derived EVs can exert procoagulant/prothrombotic effects and also promote endothelial survival and angiogenesis after ischemic injury. Kidney endothelial- and tubular-derived EVs play a key role in ischemia–reperfusion injury (IRI) and during the healing process; additionally, they can trigger rejection by inducing both alloimmune and autoimmune responses. Endothelial EVs have procoagulant/pro-inflammatory effects and can release sequestered self-antigens, generating a tissue-specific autoimmunity. Renal tubule-derived EVs shuttle pro-fibrotic mediators (TGF-β and miR-21) to interstitial fibroblasts and modulate neutrophil and T-lymphocyte influx. These processes can lead to peritubular capillary rarefaction and interstitial fibrosis–tubular atrophy. Different EVs, including those from mesenchymal stromal cells (MSCs), have been employed as a therapeutic tool in experimental models of rejection and IRI. These particles protect tubular and endothelial cells (by inhibition of apoptosis and inflammation–fibrogenesis or by inducing autophagy) and stimulate tissue regeneration (by triggering angiogenesis, cell proliferation, and migration). Finally, urinary and serum EVs represent potential biomarkers for delayed graft function (DGF) and acute rejection. In conclusion, EVs sustain an intricate crosstalk between graft tissue and innate/adaptive immune systems. EVs play a major role in allorecognition, IRI, autoimmunity, and alloimmunity and are promising as biomarkers and therapeutic tools in KT.

Keywords: extracellular vesicles, acute rejection, ischemia-reperfusion syndrome, autoimmunity, renal transplant, biomarker, miRNA

#### Edited by:

*Guseppe Grandaliano, University of Foggia, Italy*

#### Reviewed by:

*Xiangyang Zhu, Mayo Clinic, United States Francesco Paolo Schena, University of Bari Aldo Moro, Italy*

\*Correspondence: *Vincenzo Cantaluppi<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Molecular Innate Immunity, a section of the journal Frontiers in Immunology*

Received: *06 November 2019* Accepted: *13 January 2020* Published: *27 February 2020*

#### Citation:

*Quaglia M, Dellepiane S, Guglielmetti G, Merlotti G, Castellano G and Cantaluppi V (2020) Extracellular Vesicles as Mediators of Cellular Crosstalk Between Immune System and Kidney Graft. Front. Immunol. 11:74. doi: 10.3389/fimmu.2020.00074*

## INTRODUCTION

Extracellular vesicles (EVs or microparticles) is a general term that refers to membrane structures released by all cell types through different biogenesis pathways; EVs are secreted after fusion of endosomes with the plasma membrane (exosomes), shed from plasma membrane (microvesicles), or released during apoptosis (apoptotic bodies). These three entities differ in size (exosomes, 30–150 nm; shedding microvesicles, 150 nm−1µm; apoptotic bodies, 1–5µm) and partly in content (1–4). In this review, we will employ the umbrella term "EVs" to include all the above-mentioned types of secreted membrane vesicles.

After cellular shedding, EVs are rapidly taken up by neighboring or distant target cells (paracrine and endocrine effects) through a variety of mechanisms, such as endocytosis, phagocytosis/pinocytosis, membrane fusion, and receptor-mediated endocytosis (2).

EVs are involved in a wide range of physiological and pathological processes (4–7), including acute kidney injury (AKI), chronic kidney disease (CKD), thrombotic microangiopathies, and vasculitis (2, 3). EVs play a key role in all these settings by shuttling their bioactive cargo between cells. Most of their effects are mediated by microRNAs (miRNAs), which modulate gene expression in target cells and induce epigenetic reprogramming (3). Additionally, EVs carry a wide variety of immune modulatory molecules (e.g., cytokines, costimulatory/inhibitory molecules, and growth factors). Packing of nucleic acids and other contents into EVs is coordinated by multiple signals from EVs themselves or from cellular/extracellular environment (8–10). For example, TNFα modulates miRNA content of endothelial particles (11). Of interest, most EVs do not express human leukocyte antigens (HLAs) and escape the immune system; moreover, they cross numerous biological barriers (8), including glomerular endothelium basement membrane (12). Homing and uptake of EVs are mediated by signals and receptors on target cells (13) and influenced by local factors such as pH and electric charge (14). After intake, their complex biocargo exerts multiple effects: mRNAs are translated; miRNAs activate or silence protein expression (1, 2, 8); surface receptors are transferred from one cell to another (15, 16) and bacterial, viral, or graft alloantigens can be exchanged among immune cells (17, 18). A detailed analysis of EV general properties has been covered by recent reviews (1, 6, 8) (**Figure 1**).

EVs released from innate immune cells, such as macrophages, dendritic cells (DCs), or natural killer (NK) cells, are involved in the regulation of innate immune response mainly as proinflammatory and paracrine mediators (4, 19). However, their immunomodulatory role is probably far more complex and includes anti-inflammatory and immunosuppressive effects.

The role of innate immunity as a trigger for acute rejection has been the focus of intense research over the last years (20, 21), and the possibility of manipulating EVs as a therapeutic tool or employing them as biomarkers is opening new paths in solid organ transplantation (22).

The aim of this review is to outline the role of EVs in innate immunity by analyzing different aspects of kidney

transplantation (KT) biology. After analyzing EVs as mediators among different innate immune cell types, we will describe the role in complement and coagulation, two pivotal systems in innate immunity, and in other key settings such as allorecognition, ischemia–reperfusion injury (IRI), and the autoimmune component of antibody-mediated rejection. Finally, we will review recent evidence about the role of EVs as potential therapeutic tools and biomarkers in KT.

A general overview of immune-modulating effects of innate cell-derived EVs on different immune system cells or molecular targets is outlined in **Table 1**.

#### NEUTROPHIL-DERIVED EXTRACELLULAR VESICLES

Far from being mere final effectors of the inflammatory response, neutrophils [or polymorphonuclear cells (PMN)] exert several modulating effects on both innate and adaptive immune cells and can migrate to secondary lymphoid organs. These actions are partly mediated by EVs (23).

In general, PMN-derived EVs have anti-inflammatory and immunosuppressive effects, mainly on DCs and macrophages. EVs released from apoptotic PMNs also extend their actions on T-lymphocyte subsets, blunting their activation (24).

Neutrophil-derived EVs can inhibit lipopolysaccharide (LPS)-activated DCs and macrophages by reducing their phagocytic capacity, their maturation, and the release of proinflammatory cytokines (IL-8, IL-10, IL-12, and TNFα) while increasing TGF-β1 excretion. This cytokine plays a key role in suppressing immune response: it promotes anti-inflammatory DC, suppresses CD4+ and CD8+ T cells and induces T reg expansion (25, 26).

#### TABLE 1 | Immune-modulating effects of innate cell-derived EVs on other immune system cells or molecular targets.

EVs released by apoptotic human PMN suppress T-cell proliferation, IL-2 production, and IL-2 receptor upregulation on activated T cells (27). The binding of these EVs to activated T cells seems to occur through Mac-1 (CD11b/CD18), an integrin also involved in immunological synapse formation (28).

The bioactive cargo of PMN-derived EVs includes numerous immune modulatory molecules: annexin V (induction of Tregs) (29), arginase-1 (depletion of arginine with inhibition of Tcell proliferation), lactoferrin (inhibition of DC migration to lymph nodes) (30), myeloperoxidase (inhibition of DCs) (31), elastase (conversion of human immature DCs into TGF-β1 secreting cells) (32), and other proteases such as cathepsin G and proteinase 3, which can inactivate pro-inflammatory cytokines (IL-2, IL-6, and TNFα) (33) and cleave their receptors from the plasma membrane (34). Additionally, PMN EVs regulate inflammatory cell trafficking; leukotriene B4 (LTB4) activates PMN chemotaxis and is particularly enriched in their EVs (35). Conversely, during sepsis, PNM shed C5a receptor 1 into their EVs and reduce their response to complement activation (36).

## MACROPHAGE-DERIVED EXTRACELLULAR VESICLES

In general, macrophage-derived EVs exert pro-inflammatory effects, mainly directed toward DCs, macrophages, PMNs, and T lymphocytes.

Infected macrophages release EVs loaded with pathogens' proteins that can activate other antigen-presenting cells (APCs). Depending on the microenvironment, targeted macrophages activate either M1 or M2 polarization (37), whereas DCs process and present the antigens to T cells, thus promoting allorecognition and adaptive immunity. In addition to microbial or viral antigens, macrophage-derived EVs also carry peptide–major histocompatibility complex (MHC) complexes and costimulatory molecules, further enhancing alloantigen spreading among innate immune cells (38).

The cargo of macrophage-derived EVs includes several molecules with immunomodulatory functions, such as Hsp 70 (pro-inflammatory or tolerogenic effect depending on coexistent signals) (39), IL-1 β (DC migration and expansion of T/B lymphocytes) (40, 41), TNFα, and several chemokines (CCL2, CCL3, CCL4, and CCL5) (44–46). Complement C3 fragments are expressed on EV surface and interact with T cells during antigen presentation (48). Proteins involved in leukotriene synthesis were isolated in human macrophages, converting LTA4 into LTB4 and LTC4 and potentially activating DCs and CD4/CD8 T cells (43). IL-36γ was found in EVs released by infected pulmonary macrophages, with possible impact on DC maturation and T-cell activation [T helper (Th)1 or Th17 development and inhibition of Tregs] (47). Finally miR-223, a regulator of myeloid differentiation, was found in macrophage-derived EVs (42).

Zhang et al. stimulated macrophages in vitro with different protocols and performed an extensive proteomic profiling of their EVs. When the inflammasome complex was activated, EVs had a higher immunogenicity and induced NF-κB signaling in neighboring immune cells, thus amplifying inflammation (44). The inflammasome is a multimeric caspase-activating complex that can modulate a wide range of pathways in response to pathogens and activate both innate and adaptive immunity.

This is relevant to KT because IRI determines tissue damage, release of EVs, and inflammasome activation (44). These aspects will discussed in Extracellular Vesicles in Ischemia–Reperfusion Injury and in the Autoimmune Component of Rejection.

Finally, glucocorticoid therapy and long-term LPS exposure (mimicking chronic infection) can trigger macrophage release of toll-like receptor-2-containing EVs; these particles act as decoy receptors to antagonize toll-like receptor-2 signaling and blunt inflammation (66).

## DENDRITIC CELL-DERIVED EXTRACELLULAR VESICLES: EARLY INFLAMMATORY RESPONSE AND T-LYMPHOCYTE ACTIVATION

## Dendritic Cell Extracellular Vesicle and Innate Immunity