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Volume: 19 Issue: 2 February 2021

FULL TEXT

ARTICLE
Value of Plasmatic Villin-1 in the Prediction of Early Graft Dysfunction in Kidney Transplant Recipients: Diagnostic Accuracy Test

Objectives: One of the complications of kidney transplant is delayed graft function. Villin-1 has been detected in urine of patients with acute kidney injury. In addition, it is redistributed during acute kidney injury from the brush borders of the proximal tubular cells toward the basolateral membrane, which positions villin-1 closer to the renal vasculature, suggesting that it could be also released in the blood and thus can be a novel biomarker for delayed graft function.

Materials and Methods: In this diagnostic accuracy test multicenter study, 41 patients undergoing kidney transplant and attending renal transplant clinics were assigned into 2 groups according to serum creatinine levels during the first 2 days posttransplant: delayed graft function group and normal graft function group. We measured plasmatic villin-1 in comparison to serum creatinine levels at the time of declamping (time 0) and at 1, 3, 5, 7, 12, 24, 48, 72, 96, and 120 hours after declamping.

Results: Statistically significant differences were noted in comparisons between groups at same time points with regard to plasmatic villin-1 levels; also, plasmatic villin-1 started to increase above reference range in patients with end-stage renal disease at 5 hours after declamping; a peak was shown at hour 7 in the delayed graft function group, which decreased but did not reach the reference range until 120 hours after declamping.

Conclusions: Plasmatic villin-1 is a promising novel biomarker for detection of early graft dysfunction in kidney transplant recipients.


Key words : Biomarker, Delayed graft function, Normal graft function, Renal transplantation

Introduction

Kidney transplant is the treatment of choice for patients with end-stage renal disease (ESRD) as it improves survival and quality of life compared with dialysis. A main complication is delayed graft function (DGF). Of 65 studies that mentioned a definition for DGF, 18 unique definitions were presented. These definitions were commonly related to need for dialysis posttransplant (n = 49, 75%), failure of serum creatinine to decrease (n = 10, 14%), or a combination of these 2 definitions (n = 6, 11%).1,2

Delayed graft function incidence depends on its definition, the risk profiles of the donor and the recipient, and the transplant center. Over the past decade, there have been important advances in the field of transplantation, particularly in immunosup­pression and organ allocation strategies. These advances have led to reduced DGF incidence; however, incidence is expected to increase in the future because of increasing use of kidneys from extended criteria and donation after cardiac death donors, in which their use has shown higher rates of DGF versus standard criteria donors.3 Continued improvements in immunosuppressive treatment and therapeutic monitoring have led to improved graft outcomes and patient survival. However, there remains a desire to improve outcomes even further by focusing on long-term survival rates.4

A variety of factors may influence long-term graft survival, including factors related to both the acute transplant period and the long-term use of immuno­suppressive therapy. A rapidly expanding number of tools have become available that may aid in the prediction and modification of graft survival. Tremendous research interest has been directed at the rapidly expanding fields of genomics and proteomics and the potential to generate new biomarkers with the aim of identifying issues early and modifying therapy accordingly.5

Delayed graft function occurs to some extent almost always in deceased kidney transplants due to renal ischemia-reperfusion but may also occur in some living donor allografts, commonly causing varying degrees of early renal allograft impairment that predisposes patients to acute and chronic rejection. Therefore, early predictive allograft dys­function biomarkers could identify patients who may benefit from early initiation of treatment. Several biomarkers of renal injury have been identified, but the utility of these biomarkers is largely confined to research studies, whereas widespread clinical applicability is so far limited. This is partly because the use of serum creatinine as the comparator has several limitations and restricts the full interpretation of biomarker performance.6,7

Candidate biomarkers should ideally be approp­riately sensitive and specific, obtained relatively easily, and have undergone robust validation ideally in multiple international centers. In the case of renal transplantation, biomarkers are available from serum, urine, peripheral blood mononuclear cells, and tissue.5 Currently available biomarkers for acute kidney injury (AKI) are hampered by the inability to distinguish between histological AKI (ie, intrinsic kidney damage) and functional AKI. Quantification of the extent of tubular injury or necrosis is not possible without an invasive tissue biopsy. Although several proteins are released into the blood or urine during kidney injury, it is unclear whether these are markers of necrosis or of possible reversible cellular injury. Detection of a plasma protein released only on tubular damage would be valuable in both clinical and experimental settings. Villin-1 is such a potential selective marker.8

Villin-1 is part of the cytoskeleton of the microvilli of epithelial brush borders of enterocytes and the kidney’s proximal tubular cells. Villin-1 has been detected in urine of patients with AKI. In addition, villin-1 in the proximal tubular cells appears to be redistributed during AKI from the brush borders toward the basolateral membrane. This redistribution positions villin-1 closer to the renal capillaries, suggesting that it could be also released in the blood. The detection of villin-1 in blood would be preferred because collection of urine is not straightforward in cases of anuric or oliguric AKI. In addition, because villin-1 is a large (92.5 kDa) cytoskeletal protein, its release in the blood could mark tubular necrosis rather than release through active exocytosis.9

Materials and Methods

All data in this study were in accordance with the ethical standards of Ain Shams University Research Committee and with the 1964 Helsinki Declaration and its later amendments. The study was approved by the Ethics Committee of Ain Shams University (reference number: 339/2017). No organs were obtained from prisoner ESRD patients undergoing kidney transplant and/or attending renal transplant clinics at Ain Shams University Specialized Hospital, International Medical Center, and Nile Badrawi Specialized Hospital in Egypt.

Of 70 patients with ESRD undergoing kidney transplant and attending the renal transplant clinics at Ain Shams University Specialized Hospital, International Medical Center, and Nile Badrawi Specialized Hospital in Egypt from July 2017 to July 2019 and reviewed for eligibility criteria for study enrollment, 29 patients were not been included (27 patients were not eligible and did not meet the inclusion criteria and 2 patients developed serious complications leading to death in the early postoperative period). After signed informed consent for participation in our study, the 41 eligible patients were assigned into 2 groups according to correlation with serum creatinine levels in the first 2 days posttransplant: DGF group, where patients developed DGF (n = 19), and normal graft function (NGF) group (n = 22).

Exclusion criteria were age less than 18 years, combined transplant with another organ, having cardiomyopathy (ejection fraction < 30), and a history of recent (within 1 month preoperatively) infectious diseases or inflammatory disorders. None of the transplant donors were from a vulnerable population, and all donors or next of kin provided freely given written informed consent.

Two additional groups were added to our study design while processing the results to establish a normal range of plasmatic villin-1 in healthy adults and ESRD patients: 130 healthy adults from the normal population (65 men and 65 women) and 130 patients with chronic kidney disease stage V (ESRD) (65 men and 65 women). In the normal population, the reference range was from 0.08 to 0.35 ng/mL in men and from 0.055 to 0.35 ng/mL in women; in the ESRD population, the reference range was from 0.38 to 1.4 ng/mL in men and from 0.28 to 1.1 ng/mL in women.

All patients received triple immunosuppressive therapy of rabbit antithymocyte globulin, methyl prednisolone, and tacrolimus. Rabbit antithymocyte globulin was routinely administered in highly sensitized patients as an induction therapy. The initial dose of methylprednisolone was 500 to 1000 mg, which was gradually reduced to oral prednisolone (5-10 mg/day) during the first 8 to 12 weeks after transplant. Initial tacrolimus was oral administration at 0.1 mg/kg twice daily. Subsequent doses were adjusted to maintain a target trough concentration of 8 to 10 μg/L for the first 6 months, 6 to 8 μg/L for 6 to 12 months, and 4 to 6 μg/L for more than 12 months posttransplant. Mycophenolate mofetil was given at 1 to 2 grams per day.

Recipient and donor evaluations were based on complete history (age, sex, body mass index, cause of ESRD, comorbidities, duration of hemodialysis, donor relations, previous transplant, and previous sensitization) and full physical examination. All patients received a living donor kidney transplant from a family member who was willing and able to give their kidney.

Intraoperative monitoring included ischemia time (in minutes), urine output volume (amount of diuresis in mL/h in the first 2 days posttransplant), and incidence of posttransplant need for dialysis.

Laboratory investigations
During the preoperative period, laboratory inves­tigations included routine laboratory investigations, panel reactive antibody (PRA) formation, HLA typing, and final crossmatch.

In the postoperative period, laboratory investi­gations included measurement of serum creatinine levels at time 0 (the time of declamping of the renal graft vessels) and at 12, 24, and 48 hours after declamping and estimated glomerular filtration rate within the first 5 days after transplant. This was calculated according to the Modification of Diet in Renal Disease (MDRD) formula: estimated glome­rular filtration rate = 186 × (serum creatinine) - 1.154 × (age) - 0.203 × (0.742 if female) × (1.210 if black).

Other postoperative laboratory investigations included daily measurement of hemoglobin, alanine aminotransferase, aspartate aminotransferase, calcium, and phosphorus levels in the first 5 days post­transplant. Tacrolimus trough level was also measured once weekly in the first month and twice monthly in the second month and then monthly in the next 6 months. Plasmatic villin-1 levels were measured at time 0 and at 1, 3, 5, 7, 12, 24, 48, 72, 96, and 120 hours after declamping and at the time of rejection.

Sample collection and measurement of laboratory parameters
Serum samples of 41 patients who underwent kidney transplant (enrolled in the 2 study groups) were collected at different time points starting at the time of declamping (time 0) and at 1, 3, 5, 7, 12, 24, 48, 72, 96, and 120 hours after declamping.

The patients had regular follow-up meetings at the nephrology and renal transplant clinics for 2 years to establish incidence of rejection in both groups, which was guided by rising serum creatinine levels and renal biopsy-based diagnosis.

Plasmatic villin-1 levels were measured by enzyme-linked immunosorbent assay (ELISA) (human villin-1 ELISA kit; Bioassay Technology Laboratory, Shanghai, China) with standard curve ranging from 10 to 2000 ng/L and sensitivity of 5.52 ng/L.

Outcome assessment
Delayed graft function was defined as creatinine level of more than 1.5 mg/dL on day 2 post­transplant, whereas excellent renal allograft function was defined as serum creatinine level of less than 1.5 mg/dL on day 2 posttransplant.

All acute rejection episodes were biopsy proven and classified according to Banff criteria. Acute rejections were classified as acute cellular rejection or antibody-mediated rejection. Biopsies that revealed borderline changes were excluded. For patients with more than 1 episode of acute rejection, only the first rejection was included in our statistical analyses. Renal function was assessed with the use of glomerular filtration rate, estimated by MDRD formula.

Statistical analyses
To evaluate prospective diagnostic power, receiver operating characteristic curves, including area under the concentration curve data, were generated at 48 hours after kidney transplant. Demographic information was summarized using frequency (percentage) or mean ± standard deviation value, depending on data type. Absolute and relative frequencies are presented for nominal variables.

Chi-square tests with Fisher exact tests were used to compare categorical variables, and 1-way analysis of variance was used to compare continuous variables. We used the t test to test parametric variables between groups and the Mann-Whitney U tests for nonparametric cases. For all analyses, P < .05 was defined as statistically significant.

Results

The demographic and clinical details of the included patients are shown in Table 1. Both groups were comparable concerning recipient sex, age, BMI, diabetes status, hypertensive status, and the presence of other comorbidities, such as bronchial asthma, ischemic heart disease, chronic liver disease, and prior cerebrovascular stroke with no statistically significant differences between both groups. Com­parisons of HLA typing, positive versus negative PRA, and duration on hemodialysis also showed no significance difference between groups.

The DGF and NGF groups showed no significant differences in several recipient risk factors (previous blood transfusion, retransplant, and donor type) and in histopathology of native kidneys, except for significant difference seen in the positivity of crossmatches (P = .22). All recipients received kidneys from living donors, with no differences in demo­graphic data and comorbidities between groups.

We stablished reference ranges for the plasmatic villin-1 for both men and women, which were 0.08 to 0.35 and 0.055 to 0.35 ng/mL, respectively, in the normal population and 0.38 to 1.4 and 0.28 to 1.1 ng/mL, respectively, in the ESRD population, with significant difference shown between the DGF and NGF groups.

Significant differences were shown in com­parisons of urine output, serum creatinine levels, and plasmatic villin-1 levels between both groups (P < .001), as shown in Table 2. Plasmatic villin-1 started to increase above the reference range in ESRD patients at 5 hours after declamping, with a peak at 7 hours after declamping (Figure 1).

No significant correlations were shown between plasmatic villin-1 and serum creatinine levels at different points during the first 48 hours after declamping (Table 3).

Discussion

The principal concerns in the early posttransplant period are DGF and acute rejection. Early detection of DGF and acute rejection could have prognostic implications in both the short term and long term for transplant survival. Knowing which pretransplant factor potentially influences these outcomes is essential. Information gained on donor kidneys pretransplant can be used to direct the management of recipients in a way that is specific to the quality of the donor kidney.5 The human urinary proteome contains an extensive number of peptides, with a number having the potential to assess renal injury. Many of these peptides have been studied extensively in the setting of AKI, including neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule type 1, interleukin 8, and liver-type fatty acid-binding protein. All of these are expressed in the setting of AKI prior to a rise in creatinine and can be detected in serum and/or urine. This has led to these peptides being investigated for their potential predictive power in transplant.10

We assessed plasmatic villin-1 levels in study patients at time 0 (time of the declamping of the renal graft vessels) and at 1, 3, 5, 7, 12, 24, 48, 72, 96, and 120 hours after declamping and found highly statistically significant differences between our study groups except at time 0 (P < .001), with area under the receiver operating characteristic curves derived from our logistic regression analyses yielding accuracies of 90.1% and 88.8% at 5 and 7 hours, respectively (Figure 2). These results showed that plasmatic villin-1 has excellent discriminant power as a novel biomarker for early prediction of DGF with a sensitivity of 100% and a specificity of 81.82% at both 5 and 7 hours. So far, there are no studies yet available for comparison with our results as we were the first authors to use the ELISA technique for measuring plasmatic villin-1 levels.

The mean plasmatic villin-1 level (2.603 ± 0.487 ng/mL) started to increase above the plasmatic villin-1 reference range in recipients with ESRD at 5 hours after declamping in the DGF group, reaching a peak at 7 hours after declamping before it started to decline. Further studies with a longer time frame are needed to determine when plasmatic villin-1 levels would reach within the reference range. However, our results contradict those provided by Decuypere and associates, who showed, using Western blot technique, that significantly more villin-1 was detected in the plasma after 60 minutes of ischemia followed by 3 hours of reperfusion.9

In this study, we found no statistically significant differences between the DGF and NGF group recipients and donors with regard to mean age, sex, BMI, and diabetes and hypertension status. These results are in line with other randomized controlled trials performed to study the efficiency of different biomarkers as markers of DGF, including the study from Fonseca and associates on urinary NGAL as a marker of DGF compared with creatinine levels at different points after renal transplant in 40 recipients. Fonseca and associates found that urinary NGAL levels were significantly and positively correlated with serum creatinine at all time points.11 In another study, Mojtahedzadeh and associates, who used serial urine samples at 2, 24, and 48 hours after transplant to investigate interleukin 18 and NGAL levels, subdivided patients into 2 groups (DGF and non-DGF groups) to evaluate the role of urinary biomarkers in predicting DGF.12

Our results showed that there were no significant differences between groups with regard to different types of glomerulonephritis in histopathologic examinations of renal biopsies from recipients (P = .351). The nonsignificant relation between pathology of original kidney disease and incidence of DGF development is in line with a cohort study from Weber and colleagues in 417 patients on DGF and increased rate of renal allograft rejection; the group found no statistically significant relation between the pathology of original renal disease and the development of DGF.13

There were no statistically significant differences between the DGF and NGF groups regarding prevalence of risk factors in recipients (previous blood transfusion, previous renal transplant, peak PRA, and donor type) and regarding previous blood transfusion preoperatively (P = .877). Our results are supported by results from a retrospective study of 347 renal transplant patients who were evaluated from 2009 to 2013 by Nieto‑Rios and colleagues; in their study evaluating effects of cold ischemia on DGF, they found no significant relation between previous blood transfusion and incidence of development of DGF (P = 0.38).14 However, our results are contrary to the results from Salazar Meira and colleagues who showed a highly significant correlation between previous blood transfusion and the development of DGF (P < .001).1

With regard to previous kidney transplant, there was no significant difference between the NGF and DGF groups (P = .915). This result is in line with the findings from Lee and colleagues15who found no statistically significant differences between groups with regard to retransplant (P = .706) but contradicts the results from Weber and colleagues13 who concluded a statistical difference between groups with and without DGF with regard to previous kidney transplant (P < .05).

In our study, all donors in both groups were living donors (100%), with no statistically significant difference between donor type and incidence of DGF (P = .902). This finding is similar to results from Nieto‑Rios and colleagues14 from 2019 and Schutt and colleagues16 from 2017 (P = .56 and .498, respectively).

With regard to peak PRA, there was no statis­tically significant correlation between peak PRA and incidence of DGF development (P = .359). This nonsignificant relationship is similar to findings from Schutt and associates (2017)16 and Weber and associates (2018)13 who also found no significant difference between DGF and NGF group recipients and peak PRA pretransplant.

We found no difference between the DGF and NGF groups in mean pretransplant dialysis duration (P = .596). Our results are in contrast to findings from Quintella and associates17 and Weber and associates13 who found a significant difference between both groups with regard to duration on hemodialysis and development of DGF (P = .08 and .05, respectively).

Donor-recipient HLA mismatch was not signifi­cantly different between our study groups (P = .439), which is in agreement with the study from Salazar Meira and associates who also found no significant difference between their 2 study group for peak PRA and donor-recipient HLA mismatch.1 In our study, our groups were significantly different with regard to final crossmatch results (P = .022).

Mean warm ischemia was similar in both of our study groups, which was also reported by Miklusica and colleagues (P = .439).18

In our DGF group, 10.5% had immediate urine production, whereas all recipients in our NGF group had immediate urine production. These findings agree with the study from Olivier and colleagues who also found that the absence of intraoperative diuresis was prognostic for development of DGF in 50% of their study population versus only in 12% when immediate urine production was present (P < .001).19

More patients in our DGF group (15.79%) had intraoperative complications (2 developed intrao­pera­tive excess bleeding and 1 developed pneumothorax), whereas no NGF group recipients developed intra­operative complications (P = .022).

There was a significant difference with regard to need for dialysis postoperatively; 26.32% of recipients in the DGF group received renal replace­ment therapy in the first postoperative week, whereas none of the recipients in the NGF group received hemodialysis postoperatively. In the first 2 years posttransplant, 73.68% of the DGF group developed rejection versus only 18.18% of the NGF group (P < .001). Salazar Meira and colleagues showed similar findings between DGF group recipients and non-DGF group recipients (P = .023).1 In their analyses of the medical records of 1537 patients over 18 years of age who received a kidney transplant from a living donor at a single center, Ozkul and associates reported incidences of acute rejection in DGF cases and non-DGF cases of 85.3% and 16.1%, respectively (P < .001).20 Schutt and associates, in their study of recipients of living donor transplant and their respective donors (n = 111), found significant differences between the DGF group versus the non-DGF group with regard to incidence of rejection during the first year after renal transplant (P = .012).16 However, our results contradict those provided by Hollmen and associates who reported no significant difference between patients with early graft function and those with DGF with regard to incidence of rejection.21

We assessed urine output volume in both groups in the first 2 days, which showed highly significant differences between the DGF and NGF groups (P < .001). These findings are similar to those reported by Hollmen and colleagues, who showed a statistically significant difference between early graft function and DGF groups in urine amount in the first posttransplant day (P < .0001).21

We assessed serum creatinine levels in both groups at time 0 and at 12, 24, and 48 hours after declamping in both groups. The mean serum creatinine level 48 hours after declamping in our study was significantly different between our study groups, similar to that shown by Lee and associates15 with regard to mean final serum creatinine level (P < .001).

The reduction in mean serum creatinine levels was also significant between groups (P < .001); the change in plasma creatinine from pretransplant to day 1 in our study is in line with the finding from Hollmen and associates who reported a statistically significant difference between their DGF and early graft function groups with regard to change in plasma creatinine from pretransplant to day 1.21

Conclusions

Plasmatic villin-1 is a promising novel biomarker for DGF after renal transplant.


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Volume : 19
Issue : 2
Pages : 110 - 117
DOI : 10.6002/ect.2020.0160


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From the Division of Nephrology, Department of Internal Medicine, Ain Shams University, Faculty of Medicine, Cairo, Egypt
Acknowledgements: The authors have not received any funding or grants in support of the presented research or for the preparation of this work and have no declarations of potential conflicts of interest. All data generated or analyzed during this study are included in this published article.
Corresponding author: Nahla Mohamed Teama, Department of Internal Medicine, Ain Shams University, Faculty of Medicine, Ramsis street 38, Abbasia, Postal code: 11566, Cairo, Egypt
E-mail: nahlateama@med.asu.edu.eg