Peripheral blood transcriptome sequencing reveals rejection-relevant genes in long-term heart transplantation

Role of Interleukin 1 Receptor 2 in Kidney Disease

The interleukin 1 (IL-1) family plays a significant role in the innate immune response. IL-1 receptor 2 (IL-1R2) is the decoy receptor of IL-1. It is a negative regulator that can be subdivided into membrane-bound and soluble types. IL-1R2 plays a role in the IL-1 family mainly through the following mechanisms: formation of inactive signaling complexes upon binding to the receptor auxiliary protein and inhibition of ligand IL-1 maturation. This review covers the roles of IL-1R2 in kidney disorders. Chronic kidney disease, acute kidney injury, lupus nephritis, IgA nephropathy, renal clear cell carcinoma, rhabdoid tumor of kidney, kidney transplantation, and kidney infection were all shown to have abnormal IL-1R2 expression. IL-1R2 may be a potential marker and a promising therapeutic target for kidney disease.

The tip of the iceberg for diagnostic dilemmas: Performance of current diagnostics and future complementary screening approaches

Genetic testing is currently the leading edge of clinical care when it comes to diagnostics. However, many questions remain unanswered even when employing next-generation sequencing techniques due to our inability to decode genetic variations and our limited repertoire of available diagnoses. Accordingly, diagnostic yields for current genomic screenings are <50% and fail to provide the whole picture, leaving the remaining patients without a definitive diagnosis. Human phenotypic/disease expression is explained by alterations not only at the genome, but also at the transcriptome, proteome and metabolome levels. These "higher" complexity levels represent at wealth of information, and diagnostic screenings tests at these levels have been shown to significantly improve diagnostic yields in specific populations compared to conventional diagnostic workup or gold standards in use (7-30% increase in diagnostic yields, depending on the population, approach and gold standard being compared against). However, these are not yet routinely available to clinicians. Due to their dynamic and modifiable nature, tapping into data from different omics will improve our understanding of the pathophysiological bases underlying (many yet to characterize) human disorders. We herein review how alterations at these levels (e.g. post-transcriptional and post-translational) may be pathogenic, how such tests may be implemented and in which situations they are of significant utility.

Identification of Candidate Biomarkers for Transplant Rejection from Transcriptome Data: A Systematic Review

BACKGROUND

Traditional methods for rejection control in transplanted patients are considered invasive, risky, and prone to sampling errors. Using molecular biomarkers as an alternative protocol to biopsies, for monitoring rejection may help to mitigate some of these problems, increasing the survival rates and well-being of patients. Recent advances in omics technologies provide an opportunity for screening new molecular biomarkers to identify those with clinical utility.

OBJECTIVE

This systematic literature review (SLR) aimed to summarize existing evidence derived from large-scale expression profiling regarding differentially expressed mRNA and miRNA in graft rejection, highlighting potential molecular biomarkers in transplantation.

METHODS

The study was conducted following PRISMA methodology and the BiSLR guide for performing SLR in bioinformatics. PubMed, ScienceDirect, and EMBASE were searched for publications from January 2001 to January 2018, and studies (i) aiming at the identification of transplant rejection biomarkers, (ii) including human subjects, and (iii) applying methodologies for differential expression analysis from large-scale expression profiling were considered eligible. Differential expression patterns reported for genes and miRNAs in rejection were summarized from both cross-organ and organ-specific perspectives, and pathways enrichment analysis was performed for candidate biomarkers to interrogate their functional role in transplant rejection.

RESULTS

A total of 821 references were collected, resulting in 604 studies after removal of duplicates. After application of inclusion and exclusion criteria, 33 studies were included in our analysis. Among the 1517 genes and 174 miRNAs identifed, CXCL9, CXCL10, STAT1, hsa-miR-142-3p, and hsa-miR-155 appeared to be particularly promising as biomarkers in transplantation, with an increased expression associated with transplant rejection in multiple organs. In addition, hsa-miR-28-5p was consistently decreased in samples taken from rejected organs.

CONCLUSION

Despite the need for further research to fill existing knowledge gaps, transcriptomic technologies have a relevant role in the discovery of accurate biomarkers for transplant rejection diagnostics. Studies have reported consistent evidence of differential expression associated with transplant rejection, although issues such as experimental heterogeneity hinder a more systematic characterization of observed molecular changes. Special attention has been giving to large-scale mRNA expression profiling in rejection, whereas there is still room for improvements in the characterization of miRnome in this condition.

PROSPERO REGISTRATION NUMBER

CRD42018083321.

Bioinformatic analysis of peripheral blood RNA-sequencing sensitively detects the cause of late graft loss following overt hyperglycemia in pig-to-nonhuman primate islet xenotransplantation

Clinical islet transplantation has recently been a promising treatment option for intractable type 1 diabetes patients. Although early graft loss has been well studied and controlled, the mechanisms of late graft loss largely remains obscure. Since long-term islet graft survival had not been achieved in islet xenotransplantation, it has been impossible to explore the mechanism of late islet graft loss. Fortunately, recent advances where consistent long-term survival (≥6 months) of adult porcine islet grafts was achieved in five independent, diabetic nonhuman primates (NHPs) enabled us to investigate on the late graft loss. Regardless of the conventional immune monitoring methods applied in the post-transplant period, the initiation of late graft loss could rarely be detected before the overt graft loss observed via uncontrolled blood glucose level. Thus, we retrospectively analyzed the gene expression profiles in 2 rhesus monkey recipients using peripheral blood RNA-sequencing (RNA-seq) data to find out the potential cause(s) of late graft loss. Bioinformatic analyses showed that highly relevant immunological pathways were activated in the animal which experienced late graft failure. Further connectivity analyses revealed that the activation of T cell signaling pathways was the most prominent, suggesting that T cell-mediated graft rejection could be the cause of the late-phase islet loss. Indeed, the porcine islets in the biopsied monkey liver samples were heavily infiltrated with CD3+ T cells. Furthermore, hypothesis test using a computational experiment reinforced our conclusion. Taken together, we suggest that bioinformatics analyses with peripheral blood RNA-seq could unveil the cause of insidious late islet graft loss.

Compliance with ethical standards in the reporting of donor sources and ethics review in peer-reviewed publications involving organ transplantation in China: a scoping review

OBJECTIVES

The objective of this study is to investigate whether papers reporting research on Chinese transplant recipients comply with international professional standards aimed at excluding publication of research that: (1) involves any biological material from executed prisoners; (2) lacks Institutional Review Board (IRB) approval and (3) lacks consent of donors.

DESIGN

Scoping review based on Arksey and O'Mallee's methodological framework.

DATA SOURCES

Medline, Scopus and Embase were searched from January 2000 to April 2017.

ELIGIBILITY CRITERIA

We included research papers published in peer-reviewed English-language journals reporting on outcomes of research involving recipients of transplanted hearts, livers or lungs in mainland China.

DATA EXTRACTION AND SYNTHESIS

Data were extracted by individual authors working independently following training and benchmarking. Descriptive statistics were compiled using Excel.

RESULTS

445 included studies reported on outcomes of 85 477 transplants. 412 (92.5%) failed to report whether or not organs were sourced from executed prisoners; and 439 (99%) failed to report that organ sources gave consent for transplantation. In contrast, 324 (73%) reported approval from an IRB. Of the papers claiming that no prisoners' organs were involved in the transplants, 19 of them involved 2688 transplants that took place prior to 2010, when there was no volunteer donor programme in China.

DISCUSSION

The transplant research community has failed to implement ethical standards banning publication of research using material from executed prisoners. As a result, a large body of unethical research now exists, raising issues of complicity and moral hazard to the extent that the transplant community uses and benefits from the results of this research. We call for retraction of this literature pending investigation of individual papers.

Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

Bronchiolitis obliterans syndrome (BOS), the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group), and 26 samples at or after BOS diagnosis (diagnosis group). An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group). We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1), T-cell leukemia/lymphoma protein 1A (TCL1A), and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01) and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS.

Identifying low-grade cellular rejection after heart transplantation in children by using gene expression profiling

Endomyocardial biopsy (EMB) remains the gold standard for detecting rejection after heart transplantation but is costly and invasive. This study aims to distinguish no rejection (0R) from low-grade rejection (1R/2R) after heart transplantation in children by using global gene expression profiling in blood. A total of 106 blood samples with corresponding EMB from 18 children who underwent heart transplantation from 2011 to 2014 were analyzed (18 baseline/pretransplantation samples, 88 EMB samples). Corresponding rejection grades for each blood sample were 0R in 39% (34/88), 1R in 51% (45/88), and 2R in 10% (9/88). mRNA from each sample was sequenced. Differential expression analysis was performed at the gene level. A k-nearest neighbor (kNN) analysis was applied to the most differentially expressed (DE) genes to identify rejection after transplantation. Mean age at transplantation was 10.0 ± 5.4 yr. Expression of B cell and T cell receptor sequences was used to measure the effect of posttransplantation immunosuppression. Follow-up samples had lower levels of immunoglobulin gene families compared with pretransplantation ( P < 3E-5) (lower numbers of activated B cells). T cell receptor alpha and beta gene families had decreased expression in 0R samples compared with pretransplantation ( P < 4E-5) but recovered to near baseline levels in 1R/2R samples. kNN using the most DE gene (MKS1) and k = 9 nearest neighbors correctly identified 83% (73/88) of 1R/2R compared with 0R by leave-one-out cross validation. Using a genomic approach we can distinguish low-grade cellular allograft rejection (1R/2R) from no rejection (0R) after heart transplantation in children despite a wide age range.

Assessment of immune status using blood transcriptomics and potential implications for global health

The immune system plays a key role in health maintenance and pathogenesis of a wide range of diseases. Leukocytes that are present in the blood convey valuable information about the status of the immune system. Blood transcriptomics, which consists in profiling blood transcript abundance on genome-wide scales, has gained in popularity over the past several years. Indeed, practicality and simplicity largely makes up for what this approach may lack in terms of cell population-level resolution. An extensive survey of the literature reveals increasingly widespread use across virtually all fields of medicine as well as across a number of different animal species, including model organisms but also animals of economical importance. Dissemination across such a wide range of disciplines holds the promise of adding a new perspective, breadth or context, to the considerable depth afforded by whole genome profiling of blood transcript abundance. Indeed, it is only through such contextualization that a truly global perspective will be gained from the use of systems approaches. Also discussed are opportunities that may arise for the fields of immunology and medicine from using blood transcriptomics as a common denominator for developing interactions and cooperation across fields of research that have traditionally been and largely remain compartmentalized. Finally, an argument is made for building immunology research capacity using blood transcriptomics platforms in low-resource and high-disease burden settings.