Genomic meta-analysis of growth factor and integrin pathways in chronic kidney transplant injury

Systems biology approaches in solid organ transplantation

PURPOSE OF REVIEW

Organ transplantation research has led to the discovery of several interesting individual mechanistic pathways, molecules and potential drug targets but there are still no comprehensive studies that have addressed how these varied mechanisms work in unison to regulate the posttransplant immune response that drives kidney rejection and dysfunction.

RECENT FINDINGS

Systems biology is a rapidly expanding field that aims to integrate existing knowledge of molecular concepts and large-scale genomic and clinical datasets into networks that can be used in cutting edge computational models to define disease mechanisms in a holistic manner. Systems biology approaches have brought a paradigm shift from a reductionist view of biology to a wider agnostic assessment of disease from several lines of evidence. Although the complex nature of the posttransplant immune response makes it difficult to pinpoint mechanisms, systems biology is enabling discovery of unknown biological interactions using the cumulative power of genomic data sets, clinical data and endpoints, and improved computational methods for the systematic deconvolution of this response.

SUMMARY

An integrative systems biology approach that leverages genomic data from varied technologies, such as DNA sequencing, copy number variation, RNA sequencing, and methylation profiles along with long-term clinical follow-up data has the potential to define a framework that can be mined to provide novel insights for developing therapeutic interventions in organ transplantation.

Expression of fibrosis-related genes in liver allografts: Association with histology and long-term outcome after pediatric liver transplantation

BACKGROUND

Unexplained graft fibrosis and inflammation are common after pediatric liver transplantation (LT).

OBJECTIVE

We investigated the graft expression of fibrogenic genes and correlated the findings with transplant histopathology and outcome.

METHODS

Liver biopsies from 29 recipients were obtained at a median of 13.1 (IQR: 5.0-18.4) years after pediatric LT. Control samples were from six liver-healthy subjects. Hepatic expression of 40 fibrosis-related genes was correlated to histological findings: normal histology, fibrosis with no inflammation, and fibrosis with inflammation. Liver function was evaluated after a subsequent follow-up of 9.0 years (IQR: 8.0-9.4).

RESULTS

Patients with fibrosis and no inflammation had significantly increased gene expression of profibrotic TGF-β3 (1.17 vs. 1.02 p = .005), CTGF (1.64 vs. 0.66 p = .014), PDGF-α (1.79 vs. 0.98 p = .049), PDGF -β (0.99 vs. 0.76 p = .006), integrin-subunit-β1 (1.19 vs. 1.02 p = .045), α-SMA (1.12 vs. 0.58 p = .013), type I collagen (0.82 vs. 0.53 p = .005) and antifibrotic decorin (1.15 vs. 0.99 p = .045) compared to patients with normal histology. mRNA expression of VEGF A (0.84 vs. 1.06 p = .049) was lower. Only a few of the studied genes were upregulated in patients with both fibrosis and inflammation. The gene expression levels showed no association with later graft outcome.

CONCLUSIONS

Altered hepatic expression of fibrosis-related genes is associated with graft fibrosis without concurrent inflammation.

Transcriptome Analysis in Renal Transplant Biopsies Not Fulfilling Rejection Criteria

The clinical significance of renal transplant biopsies displaying borderline changes suspicious for T-cell mediated rejection (TCMR) or interstitial fibrosis and tubular atrophy (IFTA) with interstitial inflammation has not been well defined. Molecular profiling to evaluate renal transplant biopsies using microarrays has been shown to be an objective measurement that adds precision to conventional histology. We review the contribution of transcriptomic analysis in surveillance and indication biopsies with borderline changes and IFTA associated with variable degrees of inflammation. Transcriptome analysis applied to biopsies with borderline changes allows to distinguish patients with rejection from those in whom mild inflammation mainly represents a response to injury. Biopsies with IFTA and inflammation occurring in unscarred tissue display a molecular pattern similar to TCMR while biopsies with IFTA and inflammation in scarred tissue, apart from T-cell activation, also express B cell, immunoglobulin and mast cell-related genes. Additionally, patients at risk for IFTA progression can be identified by genes mainly reflecting fibroblast dysregulation and immune activation. At present, it is not well established whether the expression of rejection gene transcripts in patients with fibrosis and inflammation is the consequence of an alloimmune response, tissue damage or a combination of both.

Precision medicine: integration of genetics and functional genomics in prediction of bronchiolitis obliterans after lung transplantation

PURPOSE OF REVIEW

Lung transplantation (LTx) can be a life saving treatment in end-stage pulmonary diseases, but survival after transplantation is still limited. Posttransplant development of chronic lung allograft dysfunction with bronchiolits obliterans syndrome (BOS) as the major subphenotype, is the main cause of morbidity and mortality. Early identification of high-risk patients for BOS is a large unmet clinical need. In this review, we discuss gene polymorphisms and gene expression related to the development of BOS.

RECENT FINDINGS

Candidate gene studies showed that donor and recipient gene polymorphisms affect transplant outcome and BOS-free survival after LTx. Both selective and nonselective gene expression studies revealed differentially expressed fibrosis and apoptosis-related genes in BOS compared with non-BOS patients. Significantly, recent microarray expression analysis of blood and broncho-alveolar lavage suggest a role for B-cell and T-cell responses prior to the development of BOS. Furthermore, 6 months prior to the development of BOS differentially expressed genes were identified in peripheral blood cells.

SUMMARY

Genetic polymorphisms and gene expression changes are associated with the development of BOS. Future genome wide studies are needed to identify easily accessible biomarkers for prediction of BOS toward precision medicine.

Validation of systems biology derived molecular markers of renal donor organ status associated with long term allograft function

Donor organ quality affects long term outcome after renal transplantation. A variety of prognostic molecular markers is available, yet their validity often remains undetermined. A network-based molecular model reflecting donor kidney status based on transcriptomics data and molecular features reported in scientific literature to be associated with chronic allograft nephropathy was created. Significantly enriched biological processes were identified and representative markers were selected. An independent kidney pre-implantation transcriptomics dataset of 76 organs was used to predict estimated glomerular filtration rate (eGFR) values twelve months after transplantation using available clinical data and marker expression values. The best-performing regression model solely based on the clinical parameters donor age, donor gender, and recipient gender explained 17% of variance in post-transplant eGFR values. The five molecular markers EGF, CD2BP2, RALBP1, SF3B1, and DDX19B representing key molecular processes of the constructed renal donor organ status molecular model in addition to the clinical parameters significantly improved model performance (p-value = 0.0007) explaining around 33% of the variability of eGFR values twelve months after transplantation. Collectively, molecular markers reflecting donor organ status significantly add to prediction of post-transplant renal function when added to the clinical parameters donor age and gender.

Transcriptomic studies in tolerance: Lessons learned and the path forward

Immunosuppression after solid organ transplantation is a delicate balance of the immune response and is a complex phenomenon with many factors involved. Despite advances in the care of patients receiving organ transplants the adverse effects associated with immunosuppressive agents and the risks of long-term immunosuppression present a series of challenges and the need to weigh the risks and benefits of either over or under-immunosuppression. Ideally, if all transplant recipients could develop donor-specific immunological tolerance, it could drastically improve long-term graft survival without the need for immunosuppressive agents. In the absence of this ideal situation, the next best approach would be to develop tools to determine the adequacy of immunosuppression in each patient, in a manner that would individualize or personalize therapy. Despite current genomics-based studies of tolerance biomarkers in transplantation there are currently, no clinically validated tools to safely increase or decrease the level of IS that is beneficial to the patient. However, the successful identification of biomarkers and/or mechanisms of tolerance that have implications on long-term graft survival and outcomes depend on proper integration of study design, experimental protocols, and data-driven hypotheses. The objective of this article is to first, discuss the progress made on genomic biomarkers of immunological tolerance and the future avenues for the development of such biomarkers specifically in kidney transplantation. Secondly, we provide a set of guiding principles and identify the pitfalls, advantages, and drawbacks of studies that generate genomic data aimed at understanding transplant tolerance that is applicable to all solid transplants.

Polyomavirus BK Nephropathy-Associated Transcriptomic Signatures: A Critical Reevaluation

Background

Recent work using DNA microarrays has suggested that genes related to DNA replication, RNA polymerase assembly, and pathogen recognition receptors can serve as surrogate tissue biomarkers for polyomavirus BK nephropathy (BKPyVN).

Methods

We have examined this premise by looking for differential regulation of these genes using a different technology platform (RNA-seq) and an independent set 25 biopsies covering a wide spectrum of diagnoses.

Results

RNA-seq could discriminate T cell–mediated rejection from other common lesions seen in formalin fixed biopsy material. However, overlapping RNA-seq signatures were found among all disease processes investigated. Specifically, genes previously reported as being specific for the diagnosis of BKPyVN were found to be significantly upregulated in T cell–mediated rejection, inflamed areas of fibrosis/tubular atrophy, as well as acute tubular injury.

Conclusions

In conclusion, the search for virus specific molecular signatures is confounded by substantial overlap in pathogenetic mechanisms between BKPyVN and nonviral forms of allograft injury. Clinical heterogeneity, overlapping exposures, and different morphologic patterns and stage of disease are a source of substantial variability in “Omics” experiments. These variables should be better controlled in future biomarker studies on BKPyVN, T cell–mediated rejection, and other forms of allograft injury, before widespread implementation of these tests in the transplant clinic.

The Use of Genomics and Pathway Analysis in Our Understanding and Prediction of Clinical Renal Transplant Injury

The development and application of high-throughput molecular profiling have transformed the study of human diseases. The problem of handling large, complex data sets has been facilitated by advances in complex computational analysis. In this review, the recent literature regarding the application of transcriptional genomic information to renal transplantation, with specific reference to acute rejection, acute kidney injury in allografts, chronic allograft injury, and tolerance is discussed, as is the current published data regarding other "omics" strategies-proteomics, metabolomics, and the microRNA transcriptome. These data have shed new light on our understanding of the pathogenesis of specific disease conditions after renal transplantation, but their utility as a biomarker of disease has been hampered by study design and sample size. This review aims to highlight the opportunities and obstacles that exist with genomics and other related technologies to better understand and predict renal allograft outcome.

Bioinformatics and Drug Discovery

Bioinformatic analysis can not only accelerate drug target identification and drug candidate screening and refinement, but also facilitate characterization of side effects and predict drug resistance. High-throughput data such as genomic, epigenetic, genome architecture, cistromic, transcriptomic, proteomic, and ribosome profiling data have all made significant contribution to mechanismbased drug discovery and drug repurposing. Accumulation of protein and RNA structures, as well as development of homology modeling and protein structure simulation, coupled with large structure databases of small molecules and metabolites, paved the way for more realistic protein-ligand docking experiments and more informative virtual screening. I present the conceptual framework that drives the collection of these high-throughput data, summarize the utility and potential of mining these data in drug discovery, outline a few inherent limitations in data and software mining these data, point out news ways to refine analysis of these diverse types of data, and highlight commonly used software and databases relevant to drug discovery.

Proteomics for rejection diagnosis in renal transplant patients: Where are we now?

Rejection is one of the key factors that determine the long-term allograft function and survival in renal transplant patients. Reliable and timely diagnosis is important to treat rejection as early as possible. Allograft biopsies are not suitable for continuous monitoring of rejection. Thus, there is an unmet need for non-invasive methods to diagnose acute and chronic rejection. Proteomics in urine and blood samples has been explored for this purpose in 29 studies conducted since 2003. This review describes the different proteomic approaches and summarizes the results from the studies that examined proteomics for the rejection diagnoses. The potential limitations and open questions in establishing proteomic markers for rejection are discussed, including ongoing trials and future challenges to this topic.