Meta-analysis of molecular response of kidney to ischemia reperfusion injury for the identification of new candidate genes

Lipocalin-2 induces mitochondrial dysfunction in renal tubular cells via mTOR pathway activation

Mitochondrial dysfunction is a critical process in renal epithelial cells upon kidney injury. While its implication in kidney disease progression is established, the mechanisms modulating it remain unclear. Here, we describe the role of Lipocalin-2 (LCN2), a protein expressed in injured tubular cells, in mitochondrial dysfunction. We show that LCN2 expression decreases mitochondrial mass and function and induces mitochondrial fragmentation. Importantly, while LCN2 expression favors DRP1 mitochondrial recruitment, DRP1 inhibition antagonizes LCN2's effect on mitochondrial shape. Remarkably, LCN2 promotes mitochondrial fragmentation independently of its secretion or transport iron activity. Mechanistically, intracellular LCN2 expression increases mTOR activity, and rapamycin inhibits LCN2's effect on mitochondrial shape. In vivo, Lcn2 gene inactivation prevents mTOR activation and mitochondrial length decrease observed upon ischemia-reperfusion-induced kidney injury (IRI) in Lcn2+/+ mice. Our data identify LCN2 as a key regulator of mitochondrial dynamics and further elucidate the mechanisms leading to mitochondrial dysfunction.

Deep learning of 2D-Restructured gene expression representations for improved low-sample therapeutic response prediction

Clinical outcome prediction is important for stratified therapeutics. Machine learning (ML) and deep learning (DL) methods facilitate therapeutic response prediction from transcriptomic profiles of cells and clinical samples. Clinical transcriptomic DL is challenged by the low-sample sizes (34-286 subjects), high-dimensionality (up to 21,653 genes) and unordered nature of clinical transcriptomic data. The established methods rely on ML algorithms at accuracy levels of 0.6-0.8 AUC/ACC values. Low-sample DL algorithms are needed for enhanced prediction capability. Here, an unsupervised manifold-guided algorithm was employed for restructuring transcriptomic data into ordered image-like 2D-representations, followed by efficient DL of these 2D-representations with deep ConvNets. Our DL models significantly outperformed the state-of-the-art (SOTA) ML models on 82% of 17 low-sample benchmark datasets (53% with >0.05 AUC/ACC improvement). They are more robust than the SOTA models in cross-cohort prediction tasks, and in identifying robust biomarkers and response-dependent variational patterns consistent with experimental indications.

Identification of the Subtypes of Renal Ischemia-Reperfusion Injury Based on Pyroptosis-Related Genes

Ischemia-reperfusion injury (IRI) often occurs in the process of kidney transplantation, which significantly impacts the subsequent treatment and prognosis of patients. The prognosis of patients with different subtypes of IRI is quite different. Therefore, in this paper, the gene expression data of multiple IRI samples were downloaded from the GEO database, and a double Laplacian orthogonal non-negative matrix factorization (DL-ONMF) algorithm was proposed to classify them. In this algorithm, various regularization constraints are added based on the non-negative matrix factorization algorithm, and the prior information is fused into the algorithm from different perspectives. The connectivity information between different samples and features is added to the algorithm by Laplacian regularization constraints on samples and features. In addition, orthogonality constraints on the basis matrix and coefficient matrix obtained by the algorithm decomposition are added to reduce the influence of redundant samples and redundant features on the results. Based on the DL-ONMF algorithm for clustering, two PRGs-related IRI isoforms were obtained in this paper. The results of immunoassays showed that the immune microenvironment was different among PRGS-related IRI types. Based on the differentially expressed PRGs between subtypes, we used LASSO and SVM-RFE algorithms to construct a diagnostic model related to renal transplantation. ROC analysis showed that the diagnostic model could predict the outcome of renal transplant patients with high accuracy. In conclusion, this paper presents an algorithm, DL-ONMF, which can identify subtypes with different disease characteristics. Comprehensive bioinformatic analysis showed that pyroptosis might affect the outcome of kidney transplantation by participating in the immune response of IRI.

Title: Bioinformatic Identification of Genes Involved in Diabetic Nephropathy Fibrosis and their Clinical Relevance

Tubulointerstitial fibrosis is an important pathological feature of diabetic nephropathy that is associated with impaired renal function. However, the mechanism by which fibrosis occurs in diabetic nephropathy is unclear. Differentially expressed genes were identified from transcriptome profiles of renal tissue from diabetic patients and unilateral ureteral obstruction mice and intersected to obtain genes that may be involved in diabetic fibrosis. Biological function analysis and protein-protein interaction network analysis were performed. ROC curve and Pearson correlation analysis between hub genes were performed and glomerular filtration rate estimated. Finally, the RNA levels of hub genes were measured using real-time PCR. A total of 283 genes were identified as potentially involved in diabetic nephropathy fibrosis. TYROBP, CTSS, LCP2, LUM and TLR7 were identified as aberrantly expressed hub genes. Immune cell infiltration analysis demonstrated higher numbers of cytotoxic lymphocytes, B lineage cells, monocyte lineage cells, myeloid dendritic cells, neutrophils, and fibroblasts in the diabetic nephropathy group. The areas under ROC curves for TYROBP, CTSS, LCP2, LUM and TLR7 were 0.9167, 0.9583, 0.9917, 0.93333, and 0.9583, respectively (P < 0.001), and their correlation coefficients with estimated glomerular filtration rate were - 0.8332, - 0.752, - 0.7875, - 0.7567, and - 0.7136, respectively (P < 0.001). The RNA levels of TYROBP, CTSS, LUM and TLR7 were upregulated in high-glucose-treated human renal tubular epithelial cells (P < 0.005). Our study identified TYROBP, CTSS, LCP2, LUM and TLR7 as potentially involved in diabetic nephropathy fibrosis. Furthermore, TYROBP, CTSS, LUM and TLR7 may be associated with epithelial-mesenchymal transition of tubular epithelial cells.

The Importance of CXCL1 in the Physiological State and in Noncancer Diseases of the Oral Cavity and Abdominal Organs

CXCL1 is a CXC chemokine, CXCR2 ligand and chemotactic factor for neutrophils. In this paper, we present a review of the role of the chemokine CXCL1 in physiology and in selected major non-cancer diseases of the oral cavity and abdominal organs (gingiva, salivary glands, stomach, liver, pancreas, intestines, and kidneys). We focus on the importance of CXCL1 on implantation and placentation as well as on human pluripotent stem cells. We also show the significance of CXCL1 in selected diseases of the abdominal organs, including the gastrointestinal tract and oral cavity (periodontal diseases, periodontitis, Sjögren syndrome, Helicobacter pylori infection, diabetes, liver cirrhosis, alcoholic liver disease (ALD), non-alcoholic fatty liver disease (NAFLD), HBV and HCV infection, liver ischemia and reperfusion injury, inflammatory bowel disease (Crohn’s disease and ulcerative colitis), obesity and overweight, kidney transplantation and ischemic-reperfusion injury, endometriosis and adenomyosis).

Integrated Bioinformatics Analysis and Verification of Gene Targets for Myocardial Ischemia-Reperfusion Injury

Background

Myocardial ischemia-reperfusion injury (MIRI) has become a thorny and unsolved clinical problem. The pathological mechanisms of MIRI are intricate and unclear, so it is of great significance to explore potential hub genes and search for some natural products that exhibit potential therapeutic efficacy on MIRI via targeting the hub genes.

Methods

First, the differential expression genes (DEGs) from GSE58486, GSE108940, and GSE115568 were screened and integrated via a robust rank aggregation algorithm. Then, the hub genes were identified and verified by the functional experiment of the MIRI mice. Finally, natural products with protective effects against MIRI were retrieved, and molecular docking simulations between hub genes and natural products were performed.

Results

230 integrated DEGs and 9 hub genes were identified. After verification, Emr1, Tyrobp, Itgb2, Fcgr2b, Cybb, and Fcer1g might be the most significant genes during MIRI. A total of 75 natural products were discovered. Most of them (especially araloside C, glycyrrhizic acid, ophiopogonin D, polyphyllin I, and punicalagin) showed good ability to bind the hub genes.

Conclusions

Emr1, Tyrobp, Itgb2, Fcgr2b, Cybb, and Fcer1g might be critical in the pathological process of MIRI, and the natural products (araloside C, glycyrrhizic acid, ophiopogonin D, polyphyllin I, and punicalagin) targeting these hub genes exhibited potential therapeutic efficacy on MIRI. Our findings provided new insights to explore the mechanism and treatments for MIRI and revealed new therapeutic targets for natural products with protective properties against MIRI.

Identifying Biomarkers from Transcriptomic Signatures in Renal Allograft Biopsies Using Deceased and Living Donors

The survival of transplant kidneys using deceased donors (DD) is inferior to living donors (LD). In this study, we conducted a whole-transcriptome expression analysis of 24 human kidney biopsies paired at 30 minutes and 3 months post-transplantation using DD and LD. The transcriptome profile was found significantly different between two time points regardless of donor types. There were 446 differentially expressed genes (DEGs) between DD and LD at 30 minutes and 146 DEGs at 3 months, with 25 genes common to both time points. These DEGs reflected donor injury and acute immune responses associated with inflammation and cell death as early as at 30 minutes, which could be a precious window of potential intervention. DEGs at 3 months mainly represented the changes of adaptive immunity, immunosuppressive treatment, remodeling or fibrosis via different networks and signaling pathways. The expression levels of 20 highly DEGs involved in kidney diseases and 10 genes dysregulated at 30 minutes were found correlated with renal function and histology at 12 months, suggesting they could be potential biomarkers. These genes were further validated by quantitative polymerase chain reaction (qPCR) in 24 samples analysed by microarray, as well as in a validation cohort of 33 time point unpaired allograft biopsies. This analysis revealed that SERPINA3, SLPI and CBF were up-regulated at 30 minutes in DD compared to LD, while FTCD and TASPN7 were up-regulated at both time points. At 3 months, SERPINA3 was up-regulated in LD, but down-regulated in DD, with increased VCAN and TIMP1, and decreased FOS, in both donors. Taken together, divergent transcriptomic signatures between DD and LD, and changed by the time post-transplantation, might contribute to different allograft survival of two type kidney donors. Some DEGs including FTCD and TASPN7 could be novel biomarkers not only for timely diagnosis, but also for early precise genetic intervention at donor preservation, implantation and post-transplantation, in particular to effectively improve the quality and survival of DD.

A Systems Toxicology Approach for the Prediction of Kidney Toxicity and Its Mechanisms In Vitro

The failure to predict kidney toxicity of new chemical entities early in the development process before they reach humans remains a critical issue. Here, we used primary human kidney cells and applied a systems biology approach that combines multidimensional datasets and machine learning to identify biomarkers that not only predict nephrotoxic compounds but also provide hints toward their mechanism of toxicity. Gene expression and high-content imaging-derived phenotypical data from 46 diverse kidney toxicants were analyzed using Random Forest machine learning. Imaging features capturing changes in cell morphology and nucleus texture along with mRNA levels of HMOX1 and SQSTM1 were identified as the most powerful predictors of toxicity. These biomarkers were validated by their ability to accurately predict kidney toxicity of four out of six candidate therapeutics that exhibited toxicity only in late stage preclinical/clinical studies. Network analysis of similarities in toxic phenotypes was performed based on live-cell high-content image analysis at seven time points. Using compounds with known mechanism as reference, we could infer potential mechanisms of toxicity of candidate therapeutics. In summary, we report an approach to generate a multidimensional biomarker panel for mechanistic de-risking and prediction of kidney toxicity in in vitro for new therapeutic candidates and chemical entities.

Functional roles of Grainyhead-like transcription factors in renal development and disease

Proper renal function relies on the tightly regulated development of nephrons and collecting ducts. This process, known as tubulogenesis, involves dynamic cellular and molecular changes that instruct cells to form highly organized tubes of epithelial cells which compartmentalize the renal interstitium and tubular lumen via assembly of a selective barrier. The integrity and diversity of the various renal epithelia is achieved via formation of intercellular protein complexes along the apical-basal axis of the epithelial cells. In recent years, the evolutionarily conserved family of Grainyhead-like (GRHL) transcription factors which encompasses three mammalian family members (Grainyhead-like 1, 2, 3) has emerged as a group of critical regulators for organ development, epithelial differentiation, and barrier formation. Evidence from transgenic animal models supports the presence of Grainyhead-like-dependent transcriptional mechanisms that promote formation and maintenance of epithelial barriers in the kidney. In this review, we highlight different Grhl-dependent mechanisms that modulate epithelial differentiation in the kidney. Additionally, we discuss how disruptions in these mechanisms result in impaired renal function later in life.

Complement Therapeutics in Autoimmune Disease

Many autoimmune diseases are characterized by generation of autoantibodies that bind to host proteins or deposit within tissues as a component of immune complexes. The autoantibodies can activate the complement system, which can mediate tissue damage and trigger systemic inflammation. Complement inhibitory drugs may, therefore, be beneficial across a large number of different autoimmune diseases. Many new anti-complement drugs that target specific activation mechanisms or downstream activation fragments are in development. Based on the shared pathophysiology of autoimmune diseases, some of these complement inhibitory drugs may provide benefit across multiple different diseases. In some antibody-mediated autoimmune diseases, however, unique features of the autoantibodies, the target antigens, or the affected tissues may make it advantageous to block individual components or pathways of the complement system. This paper reviews the evidence that complement is involved in various autoimmune diseases, as well as the studies that have examined whether or not complement inhibitors are effective for treating these diseases.

Identification of potential mechanism and hub genes for neuropathic pain by expression-based genome-wide association study

Neuropathic pain (NP) is a common pathological pain state with limited effective treatments. This study was designed to identify potential mechanisms and candidate genes using gene expression-based genome-wide association study (eGWAS). All NP-related microarray experiments were obtained from Gene Expression Omnibus and ArrayExpress. Significantly dysregulated genes were identified between experimental and untreated groups, and the number of microarray experiments in which each gene was dysregulated was calculated. Significantly dysregulated genes were ranked according to P values of the chi-square test. Using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes database, we performed functional and pathway enrichment analysis. Protein-protein interaction (PPI) network and module analysis was performed using Cytoscape software. A total of 115 candidate genes were identified from 19 independent microarray experiments by eGWAS based on the Bonferroni threshold ( P < 2.97 × 10 ^-6 ). Immune and inflammatory responses, and complement and coagulation cascades, were respectively the most enriched biological process and pathways for candidate genes. The hub genes with highest connectivity in PPI network and two modules Ccl2 and Jun, and Ctss application of the eGWAS methodology can identify mechanisms and candidate genes associated with NP. Our results support the validity and prevalence of inflammatory and immune mechanisms across different NP models, and Ccl2, Jun, and Ctss may be the hub genes for NP.

Genetic susceptibility to delayed graft function following kidney transplantation: a systematic review of the literature

Delayed graft function (DGF) is defined as the need for dialysis within 7 days following kidney transplantation (KTx). DGF is associated with increased costs, higher risk for acute rejection and decreased long-term graft function. Renal ischaemia/reperfusion (I/R) injury plays a major role in DGF occurrence. Single nucleotide polymorphisms (SNPs) in certain genes may aggravate kidney susceptibility to I/R injury, thereby worsening post-transplant outcomes. The present article proposes an extensive review of the literature about the putative impact of donor or recipient SNPs on DGF occurrence in kidney transplant recipients (KTRs). Among 30 relevant PubMed reports, 16 articles identified an association between 18 SNPs and DGF. These polymorphisms concern 14 different well-known genes and one not-yet-identified gene located on chromosome 18. They have been categorized into five groups according to the role of the corresponding proteins in I/R cascade: (i) oxidative stress, (ii) telomere shortening, (iii) chemokines, (iv) T-cell homeostasis and (v) metabolism of anti-inflammatory molecules. The remaining 14 studies failed to demonstrate any association between the studied SNPs and the occurrence of DGF. A better understanding of the genetic susceptibility to renal I/R injury may help prevent DGF and improve clinical outcomes in KTRs.

Transcriptomic analysis identifies a role of PI3K-Akt signalling in the responses of skeletal muscle to acute hypoxia in vivo

KEY POINTS

Changes in gene expression that occur within hours of exposure to hypoxia in in vivo skeletal muscles remain unexplored. Two hours of hypoxia caused significant down-regulation of extracellular matrix genes followed by a shift at 6 h to altered expression of genes associated with the nuclear lumen while respiratory and blood gases were stabilized. Enrichment analysis of mRNAs classified by stability rates suggests an attenuation of post-transcriptional regulation within hours of hypoxic exposure, where PI3K-Akt signalling was suggested to have a nodal role by pathway analysis. Experimental measurements and bioinformatic analyses suggested that the dephosphorylation of Akt after 2 h of hypoxic exposure might deactivate RNA-binding protein BRF1, hence resulting in the selective degradation of mRNAs.

ABSTRACT

The effects of acute hypoxia have been widely studied, but there are few studies of transcriptional responses to hours of hypoxia in vivo, especially in hypoxia-tolerant tissues like skeletal muscles. We used RNA-seq to analyse gene expression in plantaris muscles while monitoring respiration, arterial blood gases, and blood glucose in mice exposed to 8% O₂ for 2 or 6 h. Rapid decreases in blood gases and a slower reduction in blood glucose suggest stress, which was accompanied by widespread changes in gene expression. Early down-regulation of genes associated with the extracellular matrix was followed by a shift to genes associated with the nuclear lumen. Most of the early down-regulated genes had mRNA half-lives longer than 2 h, suggesting a role for post-transcriptional regulation. These transcriptional changes were enriched in signalling pathways in which the PI3K-Akt signalling pathway was identified as a hub. Our analyses indicated that gene targets of PI3K-Akt but not HIF were enriched in early transcriptional responses to hypoxia. Among the PI3K-Akt targets, 75% could be explained by a deactivation of adenylate-uridylate-rich element (ARE)-binding protein BRF1, a target of PI3K-Akt. Consistent decreases in the phosphorylation of Akt and BRF1 were experimentally confirmed following 2 h of hypoxia. These results suggest that the PI3K-Akt signalling pathway might play a role in responses induced by acute hypoxia in skeletal muscles, partially through the dephosphorylation of ARE-binding protein BRF1.

MC-PPEA as a new and more potent inhibitor of CLP-induced sepsis and pulmonary inflammation than FK866

Our previous study indicated that overexpression of nicotinamide phosphoribosyltransferase (NAMPT) aggravated acute lung injury, while knockdown of NAMPT expression attenuated ventilator-induced lung injury. Recently, we found that meta-carborane-butyl-3-(3-pyridinyl)-2E-propenamide (MC-PPEA, MC4), in which the benzoylpiperidine moiety of FK866 has been replaced by a carborane, displayed a 100-fold increase in NAMPT inhibition over FK866. Here, we determined the effects of MC4 and FK866 on cecal ligation and puncture (CLP) surgery-induced sepsis in C57BL/6J mice. MC4 showed stronger inhibitory effects than FK866 on CLP-induced mortality, serum tumor necrosis factor α (TNFα) levels, pulmonary myeloperoxidase activity, alveolar injury, and interleukin 6 and interleukin1β messenger RNA levels. In vitro cell permeability and electric cell-substrate impedance sensing assays demonstrated that MC4 inhibited TNFα- and thrombin-mediated pulmonary endothelial cell permeability better than FK866. MC4 also exerted more potent effects than FK866, at concentrations as low as 0.3 nM, to attenuate TNFα-mediated intracellular cytokine expression, nicotinamide adenine dinucleotide (NAD+) and its reduced form NADH levels, and nuclear factor kappa B p65 phosphorylation and nuclear translocation in A549 cells. Our results strongly suggest that the newly developed MC4 is a more potent suppressor of CLP-induced pulmonary inflammation and sepsis than FK866, with potential clinical application as a new treatment agent for sepsis and inflammation.

Amelioration of cisplatin-induced acute kidney injury by recombinant neutrophil gelatinase-associated lipocalin

We investigated the protective effect and mechanism of neutrophil gelatinase-associated lipocalin (NGAL) in a murine model of cisplatin-induced nephrotoxicity. Male Swiss-Webster mice were assigned to four groups (n = 10 in each group). Control mice received vehicle only. Mice in the experimental group were given a single intraperitoneal injection of cisplatin (20 mg/kg) to induce nephrotoxicity, and were divided into three groups. The first group received 100 μL of saline only via tail vein at the time of cisplatin administration. The second group was given biologically active recombinant NGAL via tail vein (250 μg/100 μL solution). The third group was injected with a 250 μg/100μL solution of inactivated NGAL. After 4 days, we measured serum creatinine and urinary N-acetyl-β-d-glucosaminidase (NAG), and performed histologic studies. Biologically active NGAL significantly blunted the rise in serum creatinine (NGAL plus cisplatin 1.33 ± 0.31 versus cisplatin alone 2.43 ± 0.31 mg/dL, p < .001) as well as the increase in urine NAG (NGAL plus cisplatin 60.7 ± 14.2 versus cisplatin alone 120.5 ± 22.5 units/gm creatinine, p < .005). In addition, NGAL conferred a marked reduction in tubule cell necrosis and apoptosis (NGAL plus cisplatin 6.9 ± 1.2 versus cisplatin alone 15.1 ± 3.4 TUNEL positive nuclei per 100 cells, p < .001). These beneficial effects were completely abolished when heat-inactivated NGAL was administered instead of the biologically active form. Since induction of NGAL in kidney tubules is a known physiologic response to cisplatin, the pharmacologic use of NGAL to prevent cisplatin nephrotoxicity is likely to be safe and effective.

Identification of new biomarkers for Acute Respiratory Distress Syndrome by expression-based genome-wide association study

Background

Accumulated to-date gene microarray data on Acute Respiratory Distress Syndrome (ARDS) in the Gene Expression Omnibus (GEO) represent a rich source for identifying new unsuspected targets and mechanisms of ARDS. The recently developed expression-based genome-wide association study (eGWAS) for analysis of GEO data was successfully used for analysis of gene expression of comparatively noncomplex adipose tissue, 75 % of which is represented by adipocytes. Although lung tissue is more heterogenic and does not possess a prevalent cell type for driving gene expression patterns, we hypothesized that eGWAS of ARDS samples will generate biologically meaningful results.

Methods

The eGWAS was conducted according to (Proc Natl Acad Sci U S A 109:7049-7054, 2012) and genes were ranked according to p values of chi-square test.

Results

The search of GEO retrieved 487 ARDS related entries. These entries were filtered for multiple qualitative and quantitative conditions and 219 samples were selected: mouse n_sham/ARDS = 67/92, rat n = 13/13, human cells n = 11/11, canine n = 6/6 with the following ARDS model distributions: mechanical ventilation (MV)/cyclic stretch n = 11; endotoxin (LPS) treatment n = 8; MV + LPS n = 3; distant organ injury induced ARDS n = 3; chemically induced ARDS n = 2; Staphylococcus aureus induced ARDS n = 2; and one experiment each for radiation and shock induced ARDS. The eGWAS of this dataset identified 42 significant (Bonferroni threshold P < 1.55 × 10⁻⁶) genes. 66.6 % of these genes, were associated previously with lung injury and include the well known ARDS genes such as IL1R2 (P = 4.42 × 10⁻¹⁹), IL1β (P = 3.38 × 10⁻¹⁷), PAI1 (P = 9.59 × 10⁻¹⁴), IL6 (P = 3.57 × 10⁻¹²), SOCS3 (P = 1.05 × 10⁻¹⁰), and THBS1 (P = 2.01 × 10⁻⁹). The remaining genes were new ARDS candidates. Expression of the most prominently upregulated genes, CLEC4E (P = 4.46 × 10⁻¹⁴) and CD300LF (P = 2.31 × 10⁻¹⁶), was confirmed by real time PCR. The former was also validated by in silico pathway analysis and the latter by Western blot analysis.

Conclusions

Our first in the field application of eGWAS in ARDS and utilization of more than 120 publicly available microarray samples of ARDS not only justified applicability of eGWAS to complex lung tissue, but also discovered 14 new candidate genes which associated with ARDS. Detailed studies of these new candidates might lead to identification of unsuspected evolutionarily conserved mechanisms triggered by ARDS.

Electronic supplementary material

The online version of this article (doi:10.1186/s12890-015-0088-x) contains supplementary material, which is available to authorized users.

Genomic and Proteomic Characterization of Acute Kidney Injury

The incidence and severity of acute kidney injury (AKI) is rising globally, and the associated morbidity and mortality remain high despite promising advances in experimental therapeutics. The reasons include (a) an incomplete understanding of the complex pathophysiology, (b) an inability to reliably identify risk factors for AKI and (c) a lack of biomarkers for the early prediction of AKI and its outcomes. Functional genomics, bioinformatics and proteomics have begun to uncover candidates that are emerging as biomarkers and therapeutic targets. This review will update the reader on current technologies in genomics (including targeted sequencing, genome wide association studies and transcriptome profiling) and proteomics (including gel electrophoresis and mass spectrometry methods) and their application on human AKI.

Current transcriptomics in pig immunity research

Swine performance in the face of disease challenge is becoming progressively more important. To improve the pig’s robustness and resilience against pathogens through selection, a better understanding of the genetic and epigenetic factors in the immune response is required. This review highlights results from the most recent transcriptome research, and the meta-analyses performed, in the context of pig immunity. A technological overview is given including wholegenome microarrays, immune-specific arrays, small-scale high-throughput expression methods, high-density tiling arrays, and next generation sequencing (NGS). Although whole genome microarray techniques will remain complementary to NGS for some time in domestic species, research will transition to sequencing-based methods due to cost-effectiveness and the extra information that such methods provide. Furthermore, upcoming high-throughput epigenomic studies, which will add greatly to our knowledge concerning the impact of epigenetic modifications on pig immune response, are listed in this review. With emphasis on the insights obtained from transcriptomic analyses for porcine immunity, we also discuss the experimental design in pig immunity research and the value of the newly published porcine genome assembly in using the pig as a model for human immune response. We conclude by discussing the importance of establishing community standards to maximize the possibility of integrative computational analyses, such as was clearly beneficial for the human ENCODE project.

Combined meta-analysis of systemic effects of allogeneic stem cell transplantation and systemic sclerosis

BACKGROUND

Chronic graft-versus-host disease (cGVHD) is a major factor of morbidity and mortality for allogeneic stem cell transplantation (aSCT). The skin and internal organ involvement is the most common systemic complication of cGVHD and closely resembles systemic sclerosis (SSc). Circulating lymphocytes characterize the autoimmune nature of both conditions. Therefore we hypothesized that the common clinical manifestation (systemic organ and skin injury) and the common underlying players (lymphocytes) justify the combined meta-analysis of these diseases.

RESULTS

The aSCT and SSc datasets were uploaded from Gene Expression Omnibus (GEO), a public functional genomics data repository. The available microarray studies of peripheral blood mononuclear cells (PBMCs) and isolated lymphocytes were limited to well established microarray platforms (Affymetrix, Agilent, Canvac, and Illumina) and experimental settings with ≥10 patients per group. The resulting pools of data were merged by unique gene identifier and analyzed by the expression genome-wide association studies (eGWAS) coupled with the subtraction of the cGVHD+ and cGVHD- molecular signatures. The eGWAS was applied to 47 and 50 lymphocyte profiles from aSCT and SSc patients, respectively. The identified 35 candidates were represented by 8 known cGVHD genes (including CXCR4, LTBR and PML) and 28 new candidate genes (including SEPX1 and DNJGB1). The further mutual subtraction of cGVHD+ and cGVHD- candidates and pathway analysis identified a list of 25 genes. Seven of these genes belong to the fibroblast development and function pathway, consisting of the well known cGVHD genes CCND1, JUN, and FOS, and the new molecular targets MMP2, FOSB, TNFAIP8, and DUSP1. These genes become primary candidates for a potential link of systemic effects of cGVHD and SSc.

CONCLUSIONS

We designed a new approach for meta-analysis by combining data from different diseases using common clinical manifestation as a linker. This allowed us to power up the insufficient standalone meta-analysis of aSCT microarray studies, by adding SSc samples to the data pool. This new method has successfully identified novel molecular targets for systemic effects of both aSCT and SSc. We believe that this approach is generalizable and can be applied to an array of diseases with common clinical manifestations.