Prognostic value of protein biomarkers in liver transplantation: A systematic review

Liver transplantation is currently the preferred method for the treatment of advanced liver disease and early-stage hepatocellular carcinoma (HCC). Although advances in surgical techniques, immunosuppressive drugs and postoperative management have reduced the incidence of postoperative complications, how to effectively predict or diagnose postoperative complications earlier and reduce their incidence is still a clinical concern. We performed a comprehensive proteomics literature research to identified protein biomarkers in complications after liver transplantation. Seventeen studies met the inclusion criteria including ischemia reperfusion injury (IRI) (n = 4), acute rejection (AR) (n = 4), renal dysfunction (n = 4), HCC recurrence (n = 2), primary graft dysfunction (PGD) (n = 1), infection (n = 1), and liver fibrosis (n = 1). A total of 625 differentially expressed proteins (DEPs) have been reported between postoperative complications and controls, of which 63 have been validated by quantitative protein expression and 26 have been reported by at least two studies and showed consistently changes. The results of the bioinformation analysis show that the immune system, especially the innate immune system and cytokine signaling in immune system, is an important protein-mediated pathway that affects the prognosis of liver transplantation.

Discovery and Validation of a Biomarker Model (PRESERVE) Predictive of Renal Outcomes After Liver Transplantation

BACKGROUND AND AIMS

A high proportion of patients develop chronic kidney disease (CKD) after liver transplantation (LT). We aimed to develop clinical/protein models to predict future glomerular filtration rate (GFR) deterioration in this population.

APPROACH AND RESULTS

In independent multicenter discovery (CTOT14) and single-center validation (BUMC) cohorts, we analyzed kidney injury proteins in serum/plasma samples at month 3 after LT in recipients with preserved GFR who demonstrated subsequent GFR deterioration versus preservation by year 1 and year 5 in the BUMC cohort. In CTOT14, we also examined correlations between serial protein levels and GFR over the first year. A month 3 predictive model was constructed from clinical and protein level variables using the CTOT14 cohort (n = 60). Levels of β-2 microglobulin and CD40 antigen and presence of hepatitis C virus (HCV) infection predicted early (year 1) GFR deterioration (area under the curve [AUC], 0.814). We observed excellent validation of this model (AUC, 0.801) in the BUMC cohort (n = 50) who had both early and late (year 5) GFR deterioration. At an optimal threshold, the model had the following performance characteristics in CTOT14 and BUMC, respectively: accuracy (0.75, 0.8), sensitivity (0.71, 0.67), specificity (0.78, 0.88), positive predictive value (0.74, 0.75), and negative predictive value (0.76, 0.82). In the serial CTOT14 analysis, several proteins, including β-2 microglobulin and CD40, correlated with GFR changes over the first year.

CONCLUSIONS

We have validated a clinical/protein model (PRESERVE) that early after LT can predict future renal deterioration versus preservation with high accuracy. This model may help select recipients at higher risk for subsequent CKD for early, proactive renal sparing strategies.

Protecting the Kidney in Liver Transplant Candidates: Practice-Based Recommendations From the American Society of Transplantation Liver and Intestine Community of Practice

Acute kidney injury (AKI) and chronic kidney disease (CKD) are common in patients awaiting liver transplantation, and both have a marked impact on the perioperative and long-term morbidity and mortality of liver transplant recipients. Consequently, we reviewed the epidemiology of AKI and CKD in patients with end-stage liver disease, highlighted strategies to prevent and manage AKI, evaluated the changing liver transplant waiting list's impact on kidney function, delineated important considerations in simultaneous liver-kidney transplant selection, and projected possible future transplant policy changes and outcomes. This review was assembled by experts in the field and endorsed by the American Society of Transplantation Liver and Intestinal Community of Practice and Board of Directors and provides practice-based recommendations for preservation of kidney function in patients with end-stage liver disease.

Plasma protein biomarkers enhance the clinical prediction of kidney injury recovery in patients undergoing liver transplantation

Biomarkers predictive of recovery from acute kidney injury (AKI) after liver transplantation (LT) could enhance decision algorithms regarding the need for liver-kidney transplantation or renal sparing regimens. Multianalyte plasma/urine kidney injury protein panels were performed immediately before and 1 month post-LT in an initial test group divided by reversible pre-LT AKI (rAKI = post-LT renal recovery) versus no AKI (nAKI). This was followed by a larger validation set that included an additional group: irreversible pre-LT AKI (iAKI = no post-LT renal recovery). In the test group (n = 16), six pre-LT plasma (not urine) kidney injury proteins (osteopontin [OPN], neutrophil gelatinase-associated lipocalin, cystatin C, trefoil factor 3, tissue inhibitor of metalloproteinase [TIMP]-1, and β-2-microglobulin) were higher in rAKI versus nAKI (P < 0.05) and returned to normal values with renal recovery post-LT. In the validation set (n = 46), a number of proteins were significantly higher in both rAKI and iAKI versus nAKI. However, only pre-LT plasma OPN (P = 0.009) and TIMP-1 (P = 0.019) levels were significantly higher in rAKI versus iAKI. Logistic regression modeling was used to correlate the probability of post-LT rAKI, factoring in both pre-LT protein markers and clinical variables. A combined model including elevated OPN and TIMP-1 levels, age <57, and absence of diabetes had the highest area under the curve of 0.82, compared to protein-only and clinical variable-only models.

CONCLUSION

These data suggest that plasma protein profiles might improve the prediction of pre-LT kidney injury recovery after LT. However, multicenter, prospective studies are needed to validate these findings and ultimately test the value of such protein panels in perioperative management and decision making.

Protein and peptide biomarkers in organ transplantation

Organ transplantation is the optimal treatment choice for end-stage organ failure in pediatric patients. The ideal maintenance of a transplanted organ requires efficient monitoring tools and an effective individualized post-transplant treatment plan. Currently available post-transplant monitoring options are not ideal because of their invasiveness or their lack of sensitivity and specificity when providing an accurate assessment of transplant injury. Current research on proteins and peptides, including mass spectrometry-based proteomics, can identify novel surrogate protein and peptide biomarkers that can assist in monitoring the graft in order to correctly assess the status of the transplanted organ. In this article, we have critically reviewed current relevant literature to highlight the importance of protein and peptide biomarkers in the field of pediatric organ transplantation, the status of research findings in the field of protein and peptide biomarkers in different organ transplantation and factors that impact and inhibit the progression of protein biomarker discovery in the field of solid-organ transplantation in pediatrics.

Clinical and plasma proteomic markers correlating with chronic kidney disease after liver transplantation

Chronic kidney disease (CKD) occurs frequently after liver transplantation (LT) and is associated with significant morbidity and mortality. Thus, there is a pressing need to identify characteristics and biomarkers diagnostic of CKD to enable early diagnosis allowing preemptive interventions, as well as mechanistic insights into the progression from kidney injury to irreversible kidney failure. We analyzed 342 patients who had baseline glomerular filteration rate (GFR) >60 at the time of LT and are now >3 years post-LT. Risk factors for post-LT CKD were compared between three different groups defined by current GFR: >90 (n = 40), 60-90 (n = 146) and <60 (n = 156) mL/min. Age, cyclosporine use and pre-LT GFR were independently associated with new onset CKD. A subset (n = 64) without viral/immune disease or graft dysfunction underwent multianalyte plasma proteomic evaluations for correlation with CKD. Plasma proteomic analysis of two independent cohorts, test (n = 22) and validation (n = 42), identified 10 proteins highly associated with new onset CKD. In conclusion, we have identified clinical characteristics and a unique plasma proteomic signature correlating with new onset CKD after LT. These preliminary results are currently being validated in a prospective, multicenter study to determine if this signature precedes the onset of CKD and resolves with early interventions aimed at preserving kidney function.

Identification of β2-microglobulin as a urinary biomarker for chronic allograft nephropathy using proteomic methods

PURPOSE

Chronic allograft nephropathy (CAN) remains the leading cause of renal graft loss after the first year following renal transplantation. This study aimed to identify novel urinary proteomic profiles, which could distinguish and predict CAN in susceptible individuals.

EXPERIMENTAL DESIGN

The study included 34 renal transplant patients with histologically proven CAN and 36 patients with normal renal transplant function. High-throughput proteomic profiles were generated from urine samples with three different ProteinChip arrays by surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Following SELDI, a biomarker pattern software analysis was performed which led to the identification of a novel biomarker pattern that could distinguish patients with CAN from those with normal renal function.

RESULTS

An 11.7 kDa protein identified as β2 microglobulin was the primary protein of this biomarker pattern, distinguishing CAN from control patients (receiver operator characteristic [ROC]=0.996). SELDI-TOF-MS comparison of purified β2 microglobulin protein and CAN urine demonstrated identical 11.7 kDa protein peaks. Significantly, higher concentrations of 2 microglobulin were found in the urine of patients with CAN compared with the urine of normal renal function transplant recipients (p<0.001).

CONCLUSIONS AND CLINICAL RELEVANCE

Although further validation in a larger more diverse patient population is required to determine if this β2 microglobulin protein biomarker will provide a potential means of diagnosing CAN by noninvasive methods in a clinical setting, this study clearly shows a capability to stratify control and disease patients.