Comparison of Rejection-Specific Genes in Peripheral Blood and Allograft Biopsy From Kidney Transplant

Biomarkers from subcutaneous engineered tissues predict acute rejection of organ allografts

Invasive graft biopsies assess the efficacy of immunosuppression through lagging indicators of transplant rejection. We report on a microporous scaffold implant as a minimally invasive immunological niche to assay rejection before graft injury. Adoptive transfer of T cells into Rag2-/- mice with mismatched allografts induced acute cellular allograft rejection (ACAR), with subsequent validation in wild-type animals. Following murine heart or skin transplantation, scaffold implants accumulate predominantly innate immune cells. The scaffold enables frequent biopsy, and gene expression analyses identified biomarkers of ACAR before clinical signs of graft injury. This gene signature distinguishes ACAR and immunodeficient respiratory infection before injury onset, indicating the specificity of the biomarkers to differentiate ACAR from other inflammatory insult. Overall, this implantable scaffold enables remote evaluation of the early risk of rejection, which could potentially be used to reduce the frequency of routine graft biopsy, reduce toxicities by personalizing immunosuppression, and prolong transplant life.

Noninvasive Assessment of the Alloimmune Response in Kidney Transplantation

Transplantation remains the optimal mode of kidney replacement therapy, but unfortunately long-term graft survival after 1 year remains suboptimal. The main mechanism of chronic allograft injury is alloimmune, and current clinical monitoring of kidney transplants includes measuring serum creatinine, proteinuria, and immunosuppressive drug levels. The most important biomarker routinely monitored is human leukocyte antigen (HLA) donor-specific antibodies (DSAs) with the frequency based on underlying immunologic risk. HLA-DSA should be measured if there is graft dysfunction, immunosuppression minimization, or nonadherence. Antibody strength is semiquantitatively estimated as mean fluorescence intensity, with titration studies for equivocal cases and for following response to treatment. Determination of in vitro C1q or C3d positivity or HLA-DSA IgG subclass analysis remains of uncertain significance, but we do not recommend these for routine use. Current evidence does not support routine monitoring of non-HLA antibodies except anti-angiotensin II type 1 receptor antibodies when the phenotype is appropriate. The monitoring of both donor-derived cell-free DNA in blood or gene expression profiling of serum and/or urine may detect subclinical rejection, although mainly as a supplement and not as a replacement for biopsy. The optimal frequency and cost-effectiveness of using these noninvasive assays remain to be determined. We review the available literature and make recommendations.

An age-independent gene signature for monitoring acute rejection in kidney transplantation

Acute rejection (AR) remains a significant problem that negatively impacts long-term renal allograft survival. Numerous therapies are used to prevent AR that differ by center and recipient age. This variability confounds diagnostic methods. Methods: To develop an age-independent gene signature for AR effective across a broad array of immunosuppressive regimens, we compiled kidney transplant biopsy (n=1091) and peripheral blood (n=392) gene expression profiles from 12 independent public datasets. After removing genes differentially expressed in pediatric and adult patients, we compared gene expression profiles from biopsy and peripheral blood samples of patients with AR to those who were stable (STA), using Mann-Whitney U Tests with validation in independent testing datasets. We confirmed this signature in pediatric and adult patients (42 AR and 47 STA) from our institutional biorepository. Results: We identified a novel age-independent gene network that identified AR from both kidney and blood samples. We developed a 90-probe set signature targeting 76 genes that differentiated AR from STA and found an 8 gene subset (DIP2C, ENOSF1, FBXO21, KCTD6, PDXDC1, REXO2, HLA-E, and RAB31) that was associated with AR. Conclusion: We used publicly available datasets to create a gene signature of AR that identified AR irrespective of immunosuppression regimen or recipient age. This study highlights a novel model to screen and validate biomarkers across multiple treatment regimens.

Network-based computational approach to identify genetic links between cardiomyopathy and its risk factors

Cardiomyopathy (CMP) is a group of myocardial diseases that progressively impair cardiac function. The mechanisms underlying CMP development are poorly understood, but lifestyle factors are clearly implicated as risk factors. This study aimed to identify molecular biomarkers involved in inflammatory CMP development and progression using a systems biology approach. The authors analysed microarray gene expression datasets from CMP and tissues affected by risk factors including smoking, ageing factors, high body fat, clinical depression status, insulin resistance, high dietary red meat intake, chronic alcohol consumption, obesity, high-calorie diet and high-fat diet. The authors identified differentially expressed genes (DEGs) from each dataset and compared those from CMP and risk factor datasets to identify common DEGs. Gene set enrichment analyses identified metabolic and signalling pathways, including MAPK, RAS signalling and cardiomyopathy pathways. Protein-protein interaction (PPI) network analysis identified protein subnetworks and ten hub proteins (CDK2, ATM, CDT1, NCOR2, HIST1H4A, HIST1H4B, HIST1H4C, HIST1H4D, HIST1H4E and HIST1H4L). Five transcription factors (FOXC1, GATA2, FOXL1, YY1, CREB1) and five miRNAs were also identified in CMP. Thus the authors' approach reveals candidate biomarkers that may enhance understanding of mechanisms underlying CMP and their link to risk factors. Such biomarkers may also be useful to develop new therapeutics for CMP.

Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation

BACKGROUND

Kidney transplantation is the most effective treatment for end-stage renal disease. Allograft rejections severely affect survivals of allograft kidneys and recipients.

METHODS

Using bioinformatics approaches, the present study was designed to investigate immune status in renal transplant recipients. Fifteen datasets from Gene Expression Omnibus (GEO) were collected and analysed. Analysis of gene enrichment and protein-protein interactions were also used.

RESULTS

There were 40 differentially expressed genes (DEGs) identified in chronic rejection group when compared with stable recipients, which were enriched in allograft rejection module. There were 135 DEGs identified in acute rejection patients, compared with stable recipients, in which most genes were enriched in allograft rejection and immune deficiency. There were 288 DEGs identified in stable recipients when compared to healthy subjects. Most genes were related to chemokine signalling pathway. In integrated comparisons, expressions of MHC molecules and immunoglobulins were increased in both acute and chronic rejection; expressions of LILRB and MAP 4 K1 were increased in acute rejection patients, but not in stable recipients. There were no overlapping DEGs in blood samples of transplant recipients.

CONCLUSION

By performing bioinformatics analysis on the immune status of kidney transplant patients, the present study reports several DEGs in the renal biopsy of transplant recipients, which are requested to be validated in clinical practice.