Osteopontin level correlates with acute cellular renal allograft rejection

Monitoring of Serological, Cellular and Genomic Biomarkers in Transplantation, Computational Prediction Models and Role of Cell-Free DNA in Transplant Outcome

The process and evolution of an organ transplant procedure has evolved in terms of the prevention of immunological rejection with the improvement in the determination of immune response genes. These techniques include considering more important genes, more polymorphism detection, more refinement of the response motifs, as well as the analysis of epitopes and eplets, its capacity to fix complement, the PIRCHE algorithm and post-transplant monitoring with promising new biomarkers that surpass the classic serum markers such as creatine and other similar parameters of renal function. Among these new biomarkers, we analyze new serological, urine, cellular, genomic and transcriptomic biomarkers and computational prediction, with particular attention to the analysis of donor free circulating DNA as an optimal marker of kidney damage.

The Most Promising Biomarkers of Allogeneic Kidney Transplant Rejection

Clinical transplantology is a constantly evolving field of medicine. Kidney transplantation has become standard clinical practice, and it has a significant impact on reducing mortality and improving the quality of life of patients. Allogenic transplantation induces an immune response, which may lead to the rejection of the transplanted organ. The gold standard for evaluating rejection of the transplanted kidney by the recipient's organism is a biopsy of this organ. However, due to the high invasiveness of this procedure, alternative diagnostic methods are being sought. Therefore, the biomarkers may play an essential predictive role in transplant rejection. A review of the most promising biomarkers for early diagnosis and prognosis prediction of allogenic kidney transplant rejection summarizes novel data on neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), C-X-C motif chemokine 10 (CXCL-10), cystatin C (CysC), osteopontin (OPN), and clusterin (CLU) and analyses the dynamics of changes of the biomarkers mentioned above in kidney diseases and the mechanism of rejection of the transplanted kidney.

Association of serum osteopontin with first hospitalization and all-cause mortality after kidney transplantation

Objective:

Osteopontin (OPN) is involved in vascular calcification and atherosclerosis. We evaluated the association between serum OPN levels and the first postoperative hospitalization and all-cause mortality in patients who received kidney transplantation (KT).

Materials and Methods:

Seventy KT recipients were enrolled in this study from January to April 2012. The primary end point was first postoperative hospitalization or death. All patients were monitored in the outpatient clinics until June 30, 2017. Serum OPN level was measured by enzyme-linked immunosorbent assay.

Results:

During follow-up (median length, 65 months), 47 first postoperative hospitalizations and 8 deaths occurred. In comparison with serum median OPN levels, serum OPN level was positively associated with KT duration (P = 0.048), serum blood urea nitrogen (BUN; P = 0.043), and serum creatinine levels (P = 0.045) but negatively associated with estimated glomerular filtration rate (eGFR; P = 0.049). Hospitalized KT recipients had a higher prevalence of diabetes mellitus (DM) (P = 0.032), BUN (P = 0.002), and serum OPN level (P = 0.001) but lower eGFR (P = 0.030) than did patients not hospitalized. KT recipients who died had higher serum level of creatinine (P = 0.009) and OPN (P = 0.001) but lower eGFR (P = 0.036) than did surviving patients. Multivariate Cox analysis adjusted for age, gender, DM, hypertension, eGFR, KT duration, and steroid used showed that serum OPN level was associated with both first postoperative hospitalization (P = 0.049) and all-cause mortality (P = 0.017).

Conclusions:

Serum OPN level is a potential biomarker for first postoperative hospitalization and all-cause mortality in KT recipients.

Prediction of acute renal allograft rejection by combined HLA-G 14-bp insertion/deletion genotype analysis and detection of kidney injury molecule-1 and osteopontin in the peripheral blood

INTRODUCTION

Acute renal rejection usually fails to be diagnosed before the increase in the serum creatinine levels, and the resultant damage to the renal tissues occur in varying degrees. We hypothesized that the combined detection of human leucocyte antigen-G (HLA-G) 14-bp insertion/deletion genotypes and kidney injury molecule-1 (KIM-1) and osteopontin (OPN) levels in serum might facilitate the prediction of acute renal allograft rejections in kidney transplant recipients.

METHODS

HLA-G 14-bp insertion/deletion genotypes and the serum KIM-1 and OPN levels of 77 kidney transplant recipients were determined and compared before operation and on days 1, 4, and 7 after the operation (32 in acute rejection [AR] group and 45 in stable allograft function [STA] group). These 3 indicators were combined to establish a model for the early prediction of AR.

RESULTS

The KIM-1 levels in the serum of patients were significantly higher in the AR group than in the STA group. The area under the receiver operator characteristics (ROC) curve (AUC) of KIM-1 for the prediction of rejection was maximized on the1st day after operation, with a sensitivity of 84.4% and a specificity of 86.7%. The OPN levels in the serum of patients were significantly higher in the AR group than in the STA group only before operation and on the 7th day after operation. The AUC of OPN for the prediction of rejection was maximized on 7th day after operation, with a sensitivity of 68.8% and a specificity of 88.9%. The HLA-G + 14-bp allele frequency was also significantly higher in the AR group than in the STA group. The results of these three indicators were converted into a qualitative method. If any two of the three indicators show as positive, it was diagnosed as acute rejection, and it has the highest ability to predict acute rejection with a sensitivity and specificity of 84.38% and 91.11%, respectively.

CONCLUSIONS

The HLA-G 14-bp insertion/deletion genotype and KIM-1 and OPN levels in the patients' serum were significantly different between the AR and STA groups. The power of predicting acute renal allograft rejection could be improved by combined these three biomarkers.