CD28 biomarker quantification and expression level profiles in CD4+ T-lymphocytes in solid organ transplantation

Renal graft function in transplanted patients correlates with CD45RC T cell phenotypic signature

Biomarkers that could predict the evolution of the graft in transplanted patients and that could allow to adapt the care of the patients would be an invaluable tool. Additionally, certain biomarkers can be target of treatments and help to stratify patients. Potential effective biomarkers have been identified but still need to be confirmed. CD45RC, one of the splicing variants of the CD45 molecule, a tyrosine phosphatase that is critical in negatively or positively regulating the TCR and the BCR signaling, is one marker already described. The frequency of CD8+ T cells expressing high levels of CD45RC before transplantation is increased in patients with an increased risk of acute rejection. However, single biomarkers have limited predictive reliability and the correlation of the expression levels of CD45RC with other cell markers was not reported. In this study, we performed a fluorescent-based high dimensional immunophenotyping of T cells on a cohort of 69 kidney transplant patients either with stable graft function or having experienced acute transplant rejection during the first year after transplantation or at the time of rejection. We identified combinations of markers and cell subsets associated with activation/inflammation or Tregs/tolerance (HLA-DR, PD-1, IFNγ, CD28) as significant biomarkers associated to transplant outcome, and showed the importance of cell segregation based on the CD45RC marker to identify the signature of a stable graft function. Our study highlights potential reliable biomarkers in transplantation to predict and/or monitor easily graft-directed immune responses and adapt immunosuppression treatments to mitigate adverse effects.

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.

Importance of human leukocyte antigen antibodies and leukocyte antigen/killer-cell immunoglobulin-like receptor genes in liver transplantation

Many mechanisms have been proposed to explain the hypothetical state of hepatic tolerance, which is described by eventual imbalances or deregulation in the balance of cytokines, mediators, effectors, and regulatory cells in the complex milieu of the liver. In this section, we will comment on the importance of donor-specific anti-human leukocyte antigen (HLA) antibodies (DSA) as well as the compatibility and pairings of HLA and killer-cell immunoglobulin-like receptor (KIR) genotypes in the evolution of liver transplantation. Thus, HLA compatibility, viral infections, and HLA-C/KIR combinations have all been linked to liver transplant rejection and survival. There have been reports of increased risk of acute and chronic rejection with ductopenia, faster graft fibrosis, biliary problems, poorer survival, and even de novo autoimmune hepatitis when DSAs are present in the recipient. Higher mean fluorescence intensity (MFI) values of the DSAs and smaller graft size were associated with poorer patient outcomes, implying that high-risk patients with preformed DSAs should be considered for selecting the graft placed and desensitization methods, according to the investigators. Similarly, in a combined kidney-liver transplant, a pretransplant with a visible expression of several DSAs revealed that these antibodies were resistant to treatment. The renal graft was lost owing to antibody-mediated rejection (AMR). The HLA antigens expressed by the transplanted liver graft influenced antibody elimination. Pathologists are increasingly diagnosing AMR in liver transplants, and desensitization therapy has even been employed in situations of AMR, particularly in patients with DSAs in kidney-hepatic transplants and high-class II MFI due to Luminex. In conclusion, after revealing the negative impacts of DSAs with high MFI, pretransplant virtual crossmatch techniques may be appropriate to improve evolution; however, they may extend cold ischemia periods by requiring the donor to be typed.

A Machine Learning Analysis of Prognostic Genes Associated With Allograft Tolerance After Renal Transplantation

In this study, we aimed to identify transplantation tolerance (TOL)-related gene signature and use it to predict the different types of renal allograft rejection performances in kidney transplantation. Gene expression data were obtained from the Gene Expression Omnibus (GEO) database, differently expressed genes (DEGs) were performed, and the gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were also conducted. The machine learning methods were combined to analyze the feature TOL-related genes and verify their predictive performance. Afterward, the gene expression levels and predictive performances of TOL-related genes were conducted in the context of acute rejection (AR), chronic rejection (CR), and graft loss through heatmap plots and the receiver operating characteristic (ROC) curves, and their respective immune infiltration results were also performed. Furthermore, the TOL-related gene signature for graft survival was conducted to discover gene immune cell enrichment. A total of 25 TOL-related DEGs were founded, and the GO and KEGG results indicated that DEGs mainly enriched in B cell-related functions and pathways. 7 TOL-related gene signature was constructed and performed delightedly in TOL groups and different types of allograft rejection. The immune infiltration analysis suggested that gene signature was correlated with different types of immune cells. The Kaplan-Meier (KM) survival analysis demonstrated that BLNK and MZB1 were the prognostic TOL-related genes. Our study proposed a novel gene signature that may influence TOL in kidney transplantation, providing possible guidance for immunosuppressive therapy in kidney transplant patients.

Immune Regulation in Polycystic Ovary Syndrome

A polycystic ovarian syndrome (PCOS) is the most common endocrine disorder affecting females . Furthermore, it is a heterogeneous disease with a variety of etiologies and outcomes. Patients frequently complain about infertility, irregular menstruation, acne, seborrheic dermatitis, hirsutism, and obesity. PCOS can be caused by hypothalamic-pituitary-ovarian axis dysfunction, heredity, or metabolic abnormalities. PCOS is characterized by chronic low-level inflammation, which includes an imbalance in pro-inflammatory factor secretion, endothelial cell dysfunction, and leukocytosis. PCOS is also distinguished by hormonal and immune dysregulation. During PCOS, immune cells and immune regulatory molecules play critical roles in maintaining metabolic homeostasis and regulating immune responses. Because of oligo/anovulation, patients with PCOS have low progesterone levels. Therefore, low progesterone levels in PCOS overstimulate the immune system, causing it to produce more estrogen, which leads to a variety of autoantibodies. This review aims to summarize the immune regulation involved in the pathogenesis of PCOS and pave the way for the development of better PCOS treatment options in the near future.

The Need for Alternatives to Liver Biopsies: Non-Invasive Analytics and Diagnostics

Histology remains essential for the diagnosis and management of many disorders affecting the liver. However, the biopsy procedure itself is associated with a low risk of harm to the patient and cost to the health services; samples may not be adequate and are subject to sampling variation. Furthermore, interpretation often depends on the skill of the pathologist. Increasingly, new techniques are becoming available that are altering the indications for liver biopsy. Many diseases of the liver can be diagnosed and managed using serological and radiological techniques; the degree of fibrosis and fat can often be assessed by serological or imaging techniques and the nature of space occupying lesions defined by serology, imaging and use of liquid biopsy. However, these techniques, too, are subject to limitations: sensitivity and specificity is not always adequate for diagnosis or management; some techniques are expensive and often also require expert interpretation. Although there may be less need for liver biopsy today, histology remains the gold standard as well as an essential tool for the diagnosis and management of many conditions, especially where there are multiple pathologies, or where a diagnosis cannot or has not been made by alternative approaches. Until less invasive techniques become more reliable and accessible, liver histology will remain a key investigation.

Identification of peripheral CD154+ T cells and HLA-DRB1 as biomarkers of acute cellular rejection in adult liver transplant recipients

Decreasing graft rejection and increasing graft and patient survival are great challenges facing liver transplantation (LT). Different T cell subsets participate in the acute cellular rejection (ACR) of the allograft. Cell-mediated immunity markers of the recipient could help to understand the mechanisms underlying acute rejection. This study aimed to analyse different surface antigens on T cells in a cohort of adult liver patients undergoing LT to determine the influence on ACR using multi-parametric flow cytometry functional assay. Thirty patients were monitored at baseline and during 1 year post-transplant. Two groups were established, with (ACR) and without (NACR) acute cellular rejection. Leukocyte, total lymphocyte, percentages of CD4+ CD154+ and CD8+ CD154+ T cells, human leukocyte antigen (HLA) mismatch between recipient-donor and their relation with ACR as well as the acute rejection frequencies were analysed. T cells were stimulated with concanavalin A (Con-A) and surface antigens were analysed by fluorescence activated cell sorter (FACS) analysis. A high percentage of CD4+ CD154+ T cells (P = 0·001) and a low percentage of CD8+ CD154+ T cells (P = 0·002) at baseline were statistically significant in ACR. A receiver operating characteristic analysis determined the cut-off values capable to stratify patients at high risk of ACR with high sensitivity and specificity for CD4+ CD154+ (P = 0·001) and CD8+ CD154+ T cells (P = 0·002). In logistic regression analysis, CD4+ CD154+ , CD8+ CD154+ and HLA mismatch were confirmed as independent risk factors to ACR. Post-transplant percentages of both T cell subsets were significantly higher in ACR, despite variations compared to pretransplant. These findings support the selection of candidates for LT based on the pretransplant percentages of CD4+ CD154+ and CD8+ CD154+ T cells in parallel with other transplant factors.

Immunological biomarkers of tolerance in human kidney transplantation: An updated literature review

The half-life of transplanted kidneys is <10 years. Acute or chronic rejections have a negative impact on transplant outcome. Therefore, achieving to allograft tolerance for improving long-term transplant outcome is a desirable goal of transplantation field. In contrast, there are evidence that distinct immunological characteristics lead to tolerance in some transplant recipients. In contrast, the main reason for allograft loss is immunological responses. Various immune cells including T cells, B cells, dendritic cells, macrophages, natural killer, and myeloid-derived suppressor cells damage graft tissue and, thereby, graft loss happens. Therefore, being armed with the comprehensive knowledge about either preimmunological or postimmunological characteristics of renal transplant patients may help us to achieve an operational tolerance. In the present study, we are going to review and discuss immunological characteristics of renal transplant recipients with rejection and compare them with tolerant subjects.

In vitro intracellular IFNγ, IL-17 and IL-10 producing T cells correlates with the occurrence of post-transplant opportunistic infection in liver and kidney recipients

AIM

To validate intracellular cytokine production functional assay as means of cell-mediated immunity monitoring of post-transplant patients with opportunistic infection (OI).

METHODS

Intracellular cytokine-producing CD4⁺ and CD8⁺ T-cell monitoring was carried out in 30 liver transplant (LTr) and 31 kidney transplant (KTr) recipients from 2010 to 2012. Patients were assessed in our Department of Immunology at the Clinical University ‘Hospital Virgen de la Arrixaca-IMIB’ in Murcia, Spain for one year following transplantation. FACS Canto II flow cytometer was employed to quantify the intracellular production of IL-17, IFNγ and IL-10 cytokines on stimulated CD4⁺CD69⁺ and CD8⁺CD69⁺ T cells and BD FACS DIVA v.6 software was used to analysed the data. Statistical analysis was carried out using SPSS 22.0.

RESULTS

LTr with OI had significantly lower % of CD8⁺CD69⁺IFNγ⁺ T cells at 60 (7.95 ± 0.77 vs 26.25 ± 2.09, P < 0.001), 90 (7.47 ± 1.05 vs 30.34 ± 3.52, P < 0.001) and 180 (15.31 ± 3.24 vs 24.59 ± 3.28, P = 0.01) d post-transplantation. Higher % of CD4⁺CD69⁺IL-10⁺ as well as CD4⁺CD69⁺IL-17⁺ T cells were yet reported at 30 (14.06 ± 1.65 vs 6.09 ± 0.53, P = 0.0007 and 4.23 ± 0.56 vs 0.81 ± 0.14, P = 0.005; respectively), 60 (11.46 ± 1.42 vs 4.54 ± 0.91, P = 0.001 and 4.21 ± 0.59 vs 1.43 ± 0.42, P = 0.03; respectively) and 90 d (16.85 ± 1.60 vs 4.07 ± 0.63, P < 0.001 and 3.97 ± 0.43 vs 0.96 ± 0.17, P = 0.001). Yet, KTr with OI had significantly lower percentage of CD4⁺CD69⁺IFNγ⁺ at 30 (11.80 ± 1.59 vs 20.64 ± 3.26, P = 0.035), 60 (11.19 ± 1.35 vs 15.85 ± 1.58, P = 0.02), 90 (11.37 ± 1.42 vs 22.99 ± 4.12, P = 0.028) and 180 (13.63 ± 2.21 vs 21.93 ± 3.88, P = 0.008) d post-transplantation as opposed to CD4⁺CD69⁺IL-10⁺ and CD8⁺CD69⁺IL-10⁺ T cells which percentages were higher at 30 (25.21 ± 2.74 vs 8.54 ± 1.64, P < 0.001 and 22.37 ± 1.35 vs 17.18 ± 3.54, P = 0.032; respectively), 90 (16.85 ± 1.60 vs 4.07 ± 0.63, P < 0.001 and 23.06 ± 2.89 vs 10.19 ± 1.98, P = 0.002) and 180 (21.81 ± 1.72 vs 6.07 ± 0.98, P < 0.001 and 19.68 ± 2.27 vs 10.59 ± 3.17, P = 0.016) d post-transplantation. The auROC curve model determined the most accurate cut-off values to stratify LTr and KTr at high risk of OI and Cox Regression model confirmed these biomarkers as the most significant risk factors to opportunistic infection.

CONCLUSION

Post-transplant percentages of T-cell subsets differed significantly amongst infected- and non-infected-LTr and -KTr and yet this imbalance was found to contribute towards a worst clinical outcome.