Abstract
Background and Objectives:
Acute kidney injury (AKI) is nearly universally associated with worse outcomes, especially among children after hematopoietic stem cell transplant (HCT). Our objective was to examine urinary immune biomarkers of AKI after HCT to provide insights into novel mechanisms of kidney injury in this population. Studying patients undergoing allogeneic (HCT) provides a unique opportunity to examine immune markers of AKI because the risk of AKI is high and the immune system newly develops after transplant.
Design, setting, participants:
Children (>2 years old) and young adults undergoing their first allogeneic HCT and enrolled in a prospective, observational cohort study at two large children’s hospitals had urine collected pre-HCT and monthly for the first 4 months after HCT. Urine samples at each monthly time point were assayed for 8 immune-related biomarkers. AKI was defined as a 1.5-fold increase in the monthly serum creatinine value which was recorded ±1 day from when the research urine sample was obtained, as compared to the pre-HCT baseline. Generalized estimating equation regression analysis evaluated the association between the monthly repeated measures (urinary biomarkers and AKI).
Results:
A total of 176 patients were included from two pediatric centers. Thirty-six subjects from one center were analyzed as a discovery cohort and the remaining 140 subjects from the second center were analyzed as a validation cohort. AKI rates were 18–35% depending on the monthly time point after HCT. Urine CXCL10 and CXCL9 concentrations were significantly higher among children who developed AKI compared with children who did not (p<0.01) in both cohorts. In order to gain a better understanding of the cellular source for these biomarkers in the urine, we also analyzed in vitro expression of CXCL10 and CXCL9 in kidney cell lines after stimulation with interferon-gamma and interferon-alpha. HEK293-epithelial kidney cells demonstrated interferon-induced expression of CXCL10 and CXCL9, suggesting a potential mechanism driving the key finding.
Conclusions:
CXCL10 and CXCL9 are associated with AKI after HCT and are therefore promising biomarkers to guide improved diagnostic and treatment strategies for AKI in this high-risk population.
Keywords: pediatric hematopoietic stem cell transplantation, acute kidney injury, biomarkers, CXCL10, CXCL9
INTRODUCTION
Acute kidney injury (AKI) is common after hematopoietic cell transplantation (HCT) and associated with poor outcomes.(1–4) When defined as a doubling of the baseline serum creatinine, AKI is reported to occur in 21–50% of children and adults during the first 100 days after HCT, with up to 10% of patients needing acute dialysis.(3,5) AKI is associated with a higher non-relapse mortality rate and an increased risk of chronic kidney disease (CKD) and CKD occurs in >15% of survivors within 2 years after HCT.(6–11)
The role of the immune system in the pathogenesis of AKI has been investigated in animal models and studies in humans.(12) As just one example, the chemokines (C-X-C motif) ligand 10 (CXCL10) and chemokine (C-XC motif) ligand 9 (CXCL9), which are T cell chemoattractant cytokines, were associated with AKI in mouse models and have been shown to be be non-invasive urinary markers of acute cellular rejection after kidney transplant.(13–16) Additionally, these cytokines have been linked to an increased risk of graft versus host disease (GVHD) after HCT.(17)
Studying patients undergoing HCT provides a unique opportunity to examine potential immune markers as the risk of AKI is high and the immune system is altered and newly developing after transplant. Identifying biomarkers of AKI could lead to earlier detection of renal injury. Understanding novel mechanisms for AKI in this high-risk population could lead to targeted therapies to prevent, treat, or slow the progression of kidney injury. Our objective was to identify urine biomarkers associated with AKI, using separate discovery and validation cohorts of children and young adults undergoing HCT at two large children’s hospitals.
METHODS AND MATERIALS
Patient population
We analyzed urine samples collected from a prospective observational study at the Children’s Hospital of Philadelphia (CHOP) and Cincinnati Children’s Hospital Medical Center (CCHMC). The CHOP cohort was examined as a discovery cohort and the CCHMC as a validation cohort. Children and young adults >2 years of age were recruited prior to undergoing their first allogeneic HCT. We excluded patients who were <2 years of age (before the glomerular filtration rate (GFR) reaches adult levels) and those having received a prior HCT. Patients were enrolled prior to administration of conditioning chemotherapy after signing informed consent and assent, as age appropriate. The study was approved by the Institutional Review Boards at both centers.
Clinical data
Clinical data were abstracted from the electronic medical record to a structured case report form. Data elements included indication for transplantation, age, gender, conditioning chemotherapy, type of transplant, and development of acute GVHD. GVHD was diagnosed clinically.(18) AKI was defined as an increase in the serum creatinine, obtained clinically at the same time of the monthly research urine sample (±1 day), at least 50% above the pre-conditioning baseline.(19) The baseline, pre-HCT GFR was estimated with serum creatinine using the Chronic Kidney Disease in Children (CKID) formula.(20) Patients who developed AKI at a specific time point were assumed to resolve their AKI and could potentially develop recurrent episodes of AKI during the study period. We reviewed the medical records of the participants developing AKI at each center, focusing on BK polyomavirus viremia, BK-associated hemorrhagic cystitis, intravenous cidofovir and calcineurin inhibitor use to identify potential causes of AKI. Subjects at CCHMC (validation cohort) were systematically screened for thrombotic microangiopathy (TMA) as part of clinical care, which was not routinely performed in the discovery cohort (CHOP), and was also included as a potential cause of renal dysfunction in the CCHMC patients.
Sample collection and biomarker measurements
We included urine samples collected at baseline (pre-HCT conditioning) and monthly during the first 100 days (months 1, 2, 3, and 4 after stem cell infusion, Figure 1). These monthly urine samples were centrifuged, aliquoted, and stored at −80°C for later testing. Eight urinary markers were selected for testing to examine various pathways of the immune system.
Figure 1: Cohort design.
Each participant had a pre-hematopoietic cell transplant (HCT) visit including urine sample collection and baseline serum creatinine and then monthly samples starting a month after HCT. Time 0 is the day of stem cell infusion.
CXCL10 and CXCL9 are T cell chemoattractant cytokines (21,22), C-C motif chemokine ligand 2 (CCL2) which regulates migration and infiltration of monocytes and macrophages.(23–25) Tumor necrosis factor-like weak inducer of apoptosis (TWEAK) is an inflammatory marker produced by a broad range of cells.(26–28) Vascular cell adhesion protein 1 (VCAM-1) is involved in leukocyte migration and has been implicated in the pathophysiology of certain autoimmune diseases, atherosclerosis, and allograft rejection. (29–31) Interleukin 18 (IL-18) and neutrophil gelatinase-associated lipocalin (NGAL) have been validated as markers of AKI in multiple patient populations, including children.(32–35) Finally, we tested the urine samples for human epidermal growth factor receptor 2 (HER-2), a proliferation marker studied in immune-mediated kidney disease as a marker for lupus.(36)
The biomarker analyses were performed blinded to the clinical data. Biomarker concentrations were measured by commercial enzyme linked immunosorbent assay (ELISA, R&D Systems, Minneapolis, Minnesota) in accordance with manufacturer instructions with the exception of the coating buffer which was replaced with a bicarbonate buffer for stability purposes. Urine creatinine was tested using the Jaffe method with a standardized kit (Cayman Chemical, Ann Arbor, Michigan). Urine biomarker results were reported both as absolute concentrations and as values standardized to urine creatinine to normalize for differences in urine concentration. Urine was diluted 1:8 for NGAL and IL-18 measurements and 1:30 for urine creatinine measurements. No other biomarker measurements required urine dilution.
In vitro studies
Tubular kidney cells (HK2 cells), epithelial cells (HEK293), and mesangial human kidney cell lines were purchased from ATCC or generously provided by Dr. Lawrence Holzman. Kidney cell lines were grown using appropriate media (Keratinocyte Serum Free Media for HK2 cells and Dulbecco’s Modified Eagle’s media for HEK293 and mesangial cells). Cells were incubated at 37°C in a humidified atmosphere of 95% air and 5% carbon dioxide, and sub-cultured every 3–5 days by trypsinization until an appropriate number of cells were achieved. Cells were plated in 6 well plates at a density of 250,000/mL cells per well. Cells used for experiments were from passage numbers 10–13. Cells were stimulated with tumor necrosis factor alpha (10 ng/mL), interferon alpha (500 ng/mL), and interferon gamma (50 ng/mL) for 1, 4, and 24 hours. After stimulation, TriReagent was used to lyse cells for RNA extraction. RNA was purified using a Direct-zol RNA Miniprep Kit (Zymo Research). We used Advantage RT-for PCR kit (Clontech) to synthesize cDNA. Commercial primers were purchased from Applied Biosystems for each marker (CXCL10-ID Hs01124251_g1 and CXCL9-ID Hs00171065_m1). Two housekeeping mRNA controls were used (18S and GAPDH) and results were normalized to 18S. All experiments were repeated 3 times and averaged. Results are presented as normalized to the mock-treated samples.
Statistical analysis
Continuous variables are presented as mean and standard deviation (SD) or median and interquartile range (IQR), as appropriate based on their distribution. Categorical variables are presented as frequencies and percentages and compared using chi-square or Fisher’s exact tests, as appropriate. The associations between AKI (defined above as an elevated serum creatinine at a monthly post-HCT time point) and biomarker concentrations at that same monthly time point were analyzed using both the raw biomarker concentrations and the values adjusted for urine creatinine. To compare biomarker concentrations over time and to account for the longitudinal nature of the data with repeated monthly urine measures and corresponding repeated monthly serum creatinine values, we used a generalized estimating equation (GEE) regression analysis. Statistically significant urinary markers were included in multivariate GEE models to test the effect of confounders including age, acute GVHD, and underlying diagnosis. Odds ratios (OR) were reported to define the association with AKI and biomarker concentrations. Biomarker levels were examined both as continuous variables and quartiles, biomarkers which were significantly associated with AKI were further analyzed by plotting their distribution and testing binary cutoffs associated with AKI. A two-sided Bonferroni adjusted p value <0.00625 (0.05/8) was considered statistically significant given multiple biomarkers. For the in vitro analyses including the kidney cell lines, data were analyzed using t tests. Analyses were performed using STATA14 statistical software package (Stata Corporation, College Station, Texas, USA).
RESULTS
Clinical characteristics of the discovery and validation cohorts
A total of 176 patients were included in the study. At the Children’s Hospital of Philadelphia (CHOP) (discovery cohort), 36 patients ages 4–18 years (median 13 years, IQR 8 to 16 years) had urine specimens collected between the years 2015–2017. At Cincinnati Children’s Hospital Medical Center (CCHMC) (validation cohort), 140 patients ages 2–32 years (median 10 years, IQR 6 to 14 years) had urine specimens collected between the years 2013–2018. As noted, research urine samples were collected pre-transplant and at monthly intervals up to 4 months after HCT.
The characteristics of the patient cohorts are shown in Table 1. The demographics among both cohorts were comparable including renal function at baseline (pre-HCT) in the first 100 days after HCT. Indication for transplantation, donor source, and use of a myeloablative protocol were significantly different among the two cohorts. More specifically, the median pre-HCT serum creatinine-estimated GFR was 134 ml/min/1.732 (IQR 107 to 168 ml/min/1.732) at CHOP and 128 ml/min/1.732 (IQR 106 to 153 ml/min/1.732) at CCHMC. Primary disease as well as donor cell origin were different among the two cohorts with malignancy being the most common indication for transplantation among the CHOP cohort 26/36 (72%) and bone marrow failure in 46% (65/140) of subjects in the CCHMC validation cohort. AKI rates ranged between 19–35% at each monthly time point after HCT (Figure 2). The highest rate of AKI was seen at the one-month time point after transplant. We assessed clinical variables potentially related to AKI. AKI at each monthly time point was not significantly associated with acute GVHD, age, or gender.
Table 1:
Characteristics of study cohort
| Discovery cohort N = 36 | Validation cohort N = 140 | P value | |
|---|---|---|---|
| Pre-transplant age (years) | 13 (8,16) | 10 (6,14) | 0.7 |
| Male gender | 22 (62%) | 83 (59%) | 0.9 |
| Primary Disease | <0.001 | ||
| Malignancy | 26 (72%) | 38 (27%) | |
| Immunodeficiency | 4 (11%) | 33 (23%) | |
| Bone marrow failure | 4 (11%) | 65 (46%) | |
| Genetic/metabolic | 1 (2 %) | 4 (3%) | |
| Benign hematological | 1 (2 %) | 0 (0%) | |
| Donor | 0.24 | ||
| Unrelated | 26 (72%) | 93 (66.4%) | |
| Related | 10 (28%) | 47 (33.6%) | |
| Donor Source | <0.001 | ||
| Marrow | 10 (28%) | 102 (72%) | |
| Peripheral blood | 26 (72%) | 32 (22%) | |
| Cord blood | 0 (0%) | 1 (1%) | |
| Combined Marrow and Cord | 0 (0%) | 5 (4%) | |
| Pre-transplant eGFR (ml/min/1.73m2) | 134 (107,168) | 127 (106,153) | 0.15 |
| Myeloablative conditioning | 31 (86%) | 91 (65%) | <0.001 |
Data shown as median (inter quartile range) or n (%); eGFR. Estimated glomerular filtration rate
Figure 2: Acute kidney injury rates among discovery and validation cohort.
Acute kidney injury rates among the two cohorts at every time point (baseline, 1, 2, 3, and 4 months after hematopoietic cell transplant)
The specific cause of AKI in these patients could be multifactorial given the multiple potential nephrotoxic exposures after HCT. Nevertheless, we examined potential causes of AKI in the two cohorts (Table 2). BK polyomavirus viremia >0 copies/mL around the time of AKI was more common in the discovery cohort than in the validation cohort, but this difference did not reach statistical significance. However, subjects in the discovery cohort were more likely to have BK polyomavirus-associated hemorrhagic cystitis and received intravenous cidofovir. Conversely, subjects in the validation cohort were more likely to receive a calcineurin inhibitor and had a high risk of TMA.
Table 2:
Potential causes of acute kidney injury in the discovery and validation cohorts
| Discovery (CHOP) AKI N=11 | Validation (CCHMC) AKI N=49 | P-value | |
|---|---|---|---|
| BK viremia >0 copies/mL | 8 (72.7%) | 25/47 (53.2%) | 0.32 |
| BK-associated hemorrhagic cystitis | 6 (54.6%) | 10 (20.4%) | 0.05 |
| Received cidofovir | 5 (45.5%) | 8 (16.3%) | 0.05 |
| Received calcineurin inhibitor | 6 (54.6%) | 43 (87.8%) | 0.02 |
| Developed thrombotic microangiopathy | Not assessed | 21 (42.9%) |
Data shown at n (%) around the time acute kidney injury developed after hematopoietic cell transplant. P-value with Fisher’s exact test.
Discovery cohort biomarker data
In the discovery cohort, raw urine CXCL10 and CXCL9 concentrations were significantly higher among children who developed AKI at a monthly time point (Figure 3). Using the quartiles in the GEE model to determine cutoffs associated with AKI, The OR of developing AKI with a CXCL10 concentration >0 pg/mL was 4.89 (95% CI 1.7–12.7 p=0.003).The OR of developing AKI with a CXCL9 concentration >200 pg/mL was 4.6 (95% confidence interval (CI) 1.7–12.6, p=0.003) at any monthly time point. In the discovery cohort, CXCL10 normalized to urine creatinine was significantly associated with AKI (p=0.002) while CXCL9 normalized to creatinine was not (p=0.07).
Figure 3: Urinary CXCL10 and CXCL9 levels among the two cohorts at monthly intervals after hematopoietic cell transplant HCT.
Concentrations of urinary CXCL10 and CXCL9 at every monthly time point among both cohorts comparing patients who developed acute kidney injury to those who did not. Results presented as median and interquartile range.
CCL-2 was elevated among the AKI group compared to the non-AKI group but this did not reach statistical significance in the discovery cohort. Additionally, the other examined urine biomarkers, NGAL, HER-2, VCAM-1, IL18 and TWEAK were not significantly associated with AKI in the discovery cohort (ORs are presented in Table 3).
Table 3:
Association between urinary biomarkers and acute kidney injury after hematopoietic cell transplant among discovery Cohort N=36
| Odds ratio (95% confidence interval) for acute kidney injury using raw value | Odds ratio (95% confidence interval) for acute kidney injury standardized to creatinine | |
|---|---|---|
| **1CXCL10 >0 pg./ml | 4.89(1.76–13.50) * | 4.80(1.76–13.09) * |
| 2CXCL9 >200 pg./ml | 4.6(1.69–12.58) * | 2.68(0.91–7.91) |
| 3NGAL | 1.00(0.999–1.00) | 0.99 (0.99–1.00) |
| 4VCAM | 0.99 (0.99–1.00) | (0.98–1.00) |
| 5CCL-2 | 0.99 (0.99–1.00) | (0.99–1.00) |
| 6IL-18 | 0.99 (0.99–1.00) | 0.99(0.99–1.00) |
| 7TWEAK | 0.99 (0.99–1.00) | 0.98 (0.92–1.05) |
| 8HER | 0.99(0.99–1.00) | 0.93(0.84–1.04) |
Results statistically significant with a p value<0.006
Chemokine (C-X-C motif) ligand 10(CXCL10);
Chemokine (C-X-C motif) ligand 9 (CXCL9),
Neutrophil gelatinase-associated lipocalin (NGAL);
Vascular cell adhesion protein 1 (VCAM-1);
C-C motif chemokine ligand 2 (CCL-2)
Interleukin 18 (IL-18);
Tumor necrosis factor-like weak inducer of apoptosis (TWEAK),
Human epidermal growth factor receptor 2 (HER-2)
OR are presented for the continuous marker analysis (all quartiles not significant besides CXCL9 and CXCL10 presented with cut off values as well.)
Validation cohort biomarker data
In order to confirm the results from the discovery cohort, we utilized a validation cohort of 140 children from a separate center (CCHMC). In this cohort, concentrations of CXCL10 were significantly elevated among children who developed AKI. The OR for developing AKI with a CXCL10 concentration >0 pg/mL was 2.5 (95% CI 1.4–4.55, p=0.002). The OR for developing AKI with a CXCL9 concentration >200 pg/mL was 2.65 (95% CI 1.2–6 p=0.03).
Figure 3 demonstrates urinary CXCL10 and CXCL9 concentrations at each monthly time point. CXCL10 and CXCL9 normalized to urine creatinine were not statistically associated with AKI in the validation cohort. CCL-2 was significantly elevated among the AKI group compared to the non-AKI group (p=0.001). HER2, TWEAK, and VCAM were not associated with AKI. NGAL was higher among children who developed AKI compared with those with no AKI (p=0.017) but this was not significant according to the Bonferroni criterion. IL-18 was significantly lower in the AKI group compared to the no AKI group (p=0.005) (Table 4). These findings demonstrate a robust association of CXCL10 and CXCL9 with AKI in two independent HCT cohorts.
Table 4:
Association between urinary biomarkers and acute kidney injury after hematopoietic cell transplant among Validation Cohort N=140
| Odds ratio (95% confidence interval) for acute kidney injury using raw value | Odds ratio (95% confidence interval) for acute kidney injury standardized to creatinine | |
|---|---|---|
| **1CXCL10 >0 pg./ml | 2.50 (1.4–4.55) * | 2.28(1.24–4.18) * |
| 2CXCL9 >200 pg./ml | 2.65(1.17–6) * | 1.02(0.99–1.05) |
| 3NGAL | 1.00(0.99–1.00) | 1.00 (0.99–1.00) |
| 4VCAM | 1.00 (1.00–1.002) * | 1.00(0.99–1.00) |
| 5CCL-2 | 0.99(0.99–0.99) * | 0.99(0.99–1.00) |
| 6IL-18 | 1.00(0.99–1.00) | 1.01(0.98–1.04) |
| 7TWEAK | 1(1–1) | 2.49(1.05–5.9) |
| 8HER | 0.99 (0.99–1.00) | 0.99 (0.98–1.01) |
Results statistically significant with a p value<0.006
Chemokine (C-X-C motif) ligand 10(CXCL10);
Chemokine (C-X-C motif) ligand 9 (CXCL9),
Neutrophil gelatinase-associated lipocalin (NGAL);
Vascular cell adhesion protein 1 (VCAM-1);
C-C motif chemokine ligand 2 (CCL-2)
Interleukin 18 (IL-18);
Tumor necrosis factor-like weak inducer of apoptosis (TWEAK),
Human epidermal growth factor receptor 2 (HER-2)
OR are presented for the continuous marker analysis (all quartiles not significant besides CXCL9 and CXCL10 presented with cut off values as well.)
Cell line results
The HCT cohort provided us a unique opportunity to examine mechanisms of AKI in a highly immune suppressed population where potential causes of inflammation were reduced. We hypothesized that the chemokines were being produced by renal cells since at early stages after HCT, few immune competent cells are circulating. Renal cell production of CXCL10 and CXCL9 has not been previously characterized. We investigated the potential for intrinsic renal cell types to produce these chemokines using primary mesangial, tubular (HK2), and epithelial kidney (HEK293) cell lines. CXCL10 and CXCL9 expression in the control cells (stimulated) was low (CXCL10) to undetectable (CXCL9). However, after stimulation with interferon-gamma and interferon-alpha, the HEK293-epithelial kidney cells demonstrated interferon-induced expression of CXCL10 and CXCL9 (Figure 4). CXCL10 and CXCL9 levels were not significantly induced in mesangial cells (results not shown).
Figures 4a, 4b, 4C: CXCL10 and CXCL9 relative expression in HEK293 and HK2 cells. CXCL10 and CXCL9 expression using qPCR in HEK293 and HEK293 cells, respectively.
X-axis presents each stimulus and incubation time (hours) and Y-axis is normalized compared to control (no stimulus); bars represent standard error of the mean, summary of 3 replicates per each experiment *P <0.05
DISCUSSION
We observed that elevated urine levels of CXCL10 and CXCL9 were associated with AKI during the first 100 days after transplant among children and young adults undergoing HCT at two large children’s hospitals. Other urine biomarkers examining immune pathways, including CCL2, TWEAK, HER2, VCAM, and IL-18, were not consistently associated with AKI across the two patient cohorts. The cumulative rate of AKI in our cohort was 35%, similar to previous studies examining AKI in children undergoing HCT.(3)
Although serum creatinine remains the standard to diagnose AKI, its drawbacks include dependence on muscle mass and being insensitive to small, early changes in GFR after kidney injury.(37,38) There have been significant efforts to identify urine biomarkers for AKI. Most prior studies have focused on immunocompetent patient populations. Very few studies have examined markers of AKI, immune or otherwise, after HCT, especially in children. These limited studies have left clinicians without a clear alternative to serum creatinine and have not pointed towards a clear mechanism of AKI after HCT with signals seemingly from inflammatory pathways and renal tubular cells.
Elafin is an antimicrobial protein expressed by a broad range of cell types in response to inflammatory stimuli, similar to CXCL10 and CXCL9, and has been studied in 205 patients undergoing HCT and was found to be associated with AKI in those with concomitant GVHD.(39) Separately, elevated urine levels of elafin are a marker for skin GVHD(40) supporting its role as a marker of inflammation after HCT. Urine NGAL, a tubular marker of kidney injury, has been extensively studied in the cardiac bypass population (where AKI rates can occur in up to 60% of children) and has demonstrated good sensitivity and specificity for AKI.(34) A recent study serially measured urine NGAL in the first 28 days after HCT and found an association with AKI.(41) NGAL was modestly associated with AKI only in our validation cohort.
We focused on biomarkers with potential immune mechanisms of injury given the dramatic changes in the immune system post-HCT and the potential for targeted intervention. Compared to other patient populations such as cardiac bypass patients, HCT recipients are a unique population as their immune systems are in transition, and AKI can occur prior to, during, or after engraftment. Accordingly, we observed that AKI rates varied at different times post-transplant although the association with CXCL10 and CXCL9 was consistent across the timepoints. These chemoattractant proteins have been studied in other populations including patients with kidney transplant and those with multiple sclerosis, supporting a role for tissue-specific inflammatory states. Lazzeri et al demonstrated CXCL10 expression in kidney biopsies of patients with kidney transplant rejection and pre-transplant serum CXCL10 was predictive of acute rejection and chronic allograft nephropathy(14). In a multi-center study, Menke et al reported that urinary CXCL9 could risk-stratify patients for AKI after kidney transplant(13). CXCL9 has been studied in two additional multicenter studies and has been demonstrated to be elevated in patients developing acute allograft rejection and associated with poorer outcome (42,43).
In a proinflammatory state, CXCL10 and CXCL9 are secreted from a variety of cells including neutrophils, monocytes, epithelial cells, endothelial cells, stromal cells (fibroblasts), and keratinocytes in response to interferon-gamma and alpha. Interferon-gamma is largely produced by lymphocytes in response to various stimuli including viral infection, circulating nucleic acid, and other markers of cell damage whereas interferon-alpha is produced by various leukocytes other than lymphocytes. CXCL10 and CXCL9 are chemoattractant for monocytes, T cells, and NK cells and have important roles in leukocyte homing to inflamed tissues and exacerbating inflammation. We therefore hypothesized that interferon-gamma would be implicated in production of CXCL10 and CXCL9 by kidney cells. Our cell line data demonstrates that CXCL10 and CXCL9 can be produced by renal cells and can be induced by interferons. Our findings suggest a potential role for these biomarkers in the actual inflammatory process after AKI. Innate stimuli may be more pronounced early after HCT, when the adaptive immune system has not yet reconstituted.
Further research is needed to determine if our study findings have the potential to lead to improved care of patients. Our study is limited by the observational design and inclusion of a heterogeneous cohort of children and young adults undergoing HCT for various malignant and non-malignant indications. The differences in AKI rates and biomarker concentrations between the discovery and validation cohorts may be confounded by differences in calcineurin inhibitor use and BK polyomavirus viremia/hemorrhagic cystitis, in addition to other potential causes of AKI including TMA. We defined AKI using serum creatinine but did not have available data on urine output. Our monthly sampling time points likely missed patients with AKI in the interim periods between urine sample collections and our assumption that AKI resolved between monthly time points may have also confounded the findings. Future studies are needed to more closely examine the temporal associations between urine biomarkers and AKI and define the kinetics of the appearance of these biomarkers using more frequent sampling and more frequent recording of serum creatinine after HCT.
In summary, we observed that specific immune urinary biomarkers are elevated in patients developing AKI after HCT. Urine concentrations of the chemoattractant proteins CXCL10 and CXCL9 were significantly associated with AKI in the first four months after HCT in both our discovery and validation cohorts. If immune activation is shown to represent a mechanism of AKI, it would potentially allow for the development of targeted therapeutics to decrease the morbidity and mortality associated with AKI after HCT and other high-risk populations. Immune modulation has yet to be systematically examined as a potential therapeutic strategy for HCT-associated AKI.
Highlights.
Urine CXCL10 and CXCL9 are associated with acute kidney injury among children after HCT
Cell line data demonstrates production of CXCL10 and CXCL9 in the kidney
These promising biomarkers could guide management strategies for AKI in this high-risk population
ACKNOWLEDGMENTS
This work was supported by T32-DK007006–43 and the Gerber foundation research award (to DLE) and K23DK101600 (to BLL). KES is supported by the Wallace Chair of Pediatrics. Cell lines were a gift from Dr. Lawrence Holzman.
DISCLOSURES
BLL and SJ are co-inventors of a patent application under review: Compositions and Methods for Treatment of HSCT-Associated Thrombotic Microangiopathy. United States Patent Number PCT/US2014/055922, 2014. BLL has received consulting fees from Bioporto. SMD and SJ have received research support from Alexion Pharmaceuticals.
Footnotes
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