Paul Perco

In-silico human genomics with GeneCards

Since 1998, the bioinformatics, systems biology, genomics and medical communities have enjoyed a synergistic relationship with the GeneCards database of human genes (http://www.genecards.org). This human gene compendium was created to help to introduce order into the increasing chaos of information flow. As a consequence of viewing details and deep links related to specific genes, users have often requested enhanced capabilities, such that, over time, GeneCards has blossomed into a suite of tools (including GeneDecks, GeneALaCart, GeneLoc, GeneNote and GeneAnnot) for a variety of analyses of both single human genes and sets thereof. In this paper, we focus on inhouse and external research activities which have been enabled, enhanced, complemented and, in some cases, motivated by GeneCards. In turn, such interactions have often inspired and propelled improvements in GeneCards. We describe here the evolution and architecture of this project, including examples of synergistic applications in diverse areas such as synthetic lethality in cancer, the annotation of genetic variations in disease, omics integration in a systems biology approach to kidney disease, and bioinformatics tools.

Markers of cellular senescence in zero hour biopsies predict outcome in renal transplantation.

Although chronological donor age is the most potent predictor of long‐term outcome after renal transplantation, it does not incorporate individual differences of the aging‐process itself. We therefore hypothesized that an estimate of biological organ age as derived from markers of cellular senescence in zero hour biopsies would be of higher predictive value. Telomere length and mRNA expression levels of the cell cycle inhibitors CDKN2A (p16INK4a) and CDKN1A (p21WAF1) were assessed in pre‐implantation biopsies of 54 patients and the association of these and various other clinical parameters with serum creatinine after 1 year was determined. In a linear regression analysis, CDKN2A turned out to be the best single predictor followed by donor age and telomere length. A multiple linear regression analysis revealed that the combination of CDKN2A values and donor age yielded even higher predictive values for serum creatinine 1 year after transplantation. We conclude that the molecular aging marker CDKN2A in combination with chronological donor age predict renal allograft function after 1 year significantly better than chronological donor age alone.

Genome-wide gene-expression patterns of donor kidney biopsies distinguish primary allograft function.

Roughly 25% of cadaveric, but rarely living donor renal transplant recipients, develop postischemic acute renal failure, which is a main risk factor for reduced long-term allograft survival. An accurate prediction of recipients at risk for ARF is not possible on the basis of donor kidney morphology or donor/recipient demographics. We determined the genome-wide gene-expression pattern using cDNA microarrays in three groups of 36 donor kidney wedge biopsies: living donor kidneys with primary function, cadaveric donor kidneys with primary function and cadaveric donor kidneys with biopsy proven acute renal failure. The descriptive genes were characterized in gene ontology terms to determine their functional role. The validation of microarray experiments was performed by real-time PCR. We retrieved 132 genes after maxT adjustment for multiple testing that significantly separated living from cadaveric kidneys, and 48 genes that classified the donor kidneys according to their post-transplant course. The main functional roles of these genes are cell communication, apoptosis and inflammation. In particular, members of the complement cascade were activated in cadaveric, but not in living donor kidneys. Thus, suppression of inflammation in the cadaveric donor might be a cheap and promising intervention for postischemic acute renal failure.

Hypoxia response and VEGF-A expression in human proximal tubular epithelial cells in stable and progressive renal disease

Proteinuria, inflammation, chronic hypoxia, and rarefaction of peritubular capillaries contribute to the progression of renal disease by affecting proximal tubular epithelial cells (PTECs). To study the transcriptional response that separates patients with a stable course from those with a progressive course of disease, we isolated PTECs by laser capture microdissection from cryocut tissue sections of patients with proteinuric glomerulopathies (stable n=20, progressive n=11) with a median clinical follow-up of 26 months. Gene-expression profiling and a systems biology analysis identified activation of intracellular vascular endothelial growth factor (VEGF) signaling and hypoxia response pathways in progressive patients, which was associated with upregulation of hypoxia-inducible-factor (HIF)-1α and several HIF target genes, such as transferrin, transferrin-receptor, p21, and VEGF-receptor 1, but downregulation of VEGF-A. The inverse expression levels of HIF-1α and VEGF-A were significantly superior in predicting clinical outcome as compared with proteinuria, renal function, and degree of tubular atrophy and interstitial fibrosis at the time of biopsy. Interactome analysis showed the association of attenuated VEGF-A expression with the downregulation of genes that usually stimulate VEGF-A expression, such as epidermal growth factor (EGF), insulin-like growth factor-1 (IGF-1), and HIF-2α. In vitro experiments confirmed the positive regulatory effect of EGF and IGF-1 on VEGF-A transcription in human proximal tubular cells. Thus, in progressive but not in stable proteinuric kidney disease, human PTECs show an attenuated VEGF-A expression despite an activation of intracellular hypoxia response and VEGF signaling pathways, which might be due to a reduced expression of positive coregulators, such as EGF and IGF-1.

The surface properties of nanocrystalline diamond and nanoparticulate diamond powder and their suitability as cell growth support surfaces

Nanocrystalline diamond (NCD) films and nanoparticulate diamond powder (DP) are the two main representatives of diamond at the nanoscale. This study was designed to investigate the suitability of these biomaterials as cell growth supports and to determine surface characteristic properties best suited to cell attachment and proliferation. Surface topography, chemical termination and wetting properties of NCD- and DP-coated borosilicate glass substrates were correlated to attachment, proliferation and differentially regulated gene expression of human renal epithelial cells (HK-2 cell line) cultured on these surfaces. Hydrogen-terminated NCD (NCD-H) surfaces were shown to inhibit cell attachment, which indicates that the lack of functional polar groups prevents adherent cells from settling on a surface, whether nanostructured or not. In contrast to NCD-H, oxygen-terminated NCD (NCD-O) as well as DP surfaces demonstrated improved cell attachment, as compared to borosilicate glass, which is a commonly used material for cell growth supports. NCD-O not only revealed an increased cell attachment, but also a markedly increased proliferation rate. Finally, none of the investigated surface modifications appeared to cause adverse cellular reactions or markedly alter cellular phenotype.

Characterization of protein-interaction networks in tumors

BackgroundAnalyzing differential-gene-expression data in the context of protein-interaction networks (PINs) yields information on the functional cellular status. PINs can be formally represented as graphs, and approximating PINs as undirected graphs allows the network properties to be characterized using well-established graph measures.This paper outlines features of PINs derived from 29 studies on differential gene expression in cancer. For each study the number of differentially regulated genes was determined and used as a basis for PIN construction utilizing the Online Predicted Human Interaction Database.ResultsGraph measures calculated for the largest subgraph of a PIN for a given differential-gene-expression data set comprised properties reflecting the size, distribution, biological relevance, density, modularity, and cycles. The values of a distinct set of graph measures, namely Closeness Centrality, Graph Diameter, Index of Aggregation, Assortative Mixing Coefficient, Connectivity, Sum of the Wiener Number, modified Vertex Distance Number, and Eigenvalues differed clearly between PINs derived on the basis of differential gene expression data sets characterizing malignant tissue and PINs derived on the basis of randomly selected protein lists.ConclusionCancer PINs representing differentially regulated genes are larger than those of randomly selected protein lists, indicating functional dependencies among protein lists that can be identified on the basis of transcriptomics experiments. However, the prevalence of hub proteins was not increased in the presence of cancer. Interpretation of such graphs in the context of robustness may yield novel therapies based on synthetic lethality that are more effective than focusing on single-action drugs for cancer treatment.

Protein biomarkers associated with acute renal failure and chronic kidney disease

Acute renal failure (ARF) as well as chronic kidney disease (CKD) are currently categorized according to serum creatinine concentrations. Serum creatinine, however, has shortcomings because of its low predictive values. The need for novel markers for the early diagnosis and prognosis of renal diseases is imminent, particularly for markers reflecting intrinsic organ injury in stages when glomerular filtration is not impaired. This review summarizes protein markers discussed in the context of ARF as well as CKD, and provides an overview on currently available discovery results following ‘omics’ techniques. The identified set of candidate marker proteins is discussed in their cellular and functional context. The systematic review of proteomics and genomics studies revealed 56 genes to be associated with acute or chronic kidney disease. Context analysis, i.e. correlation of biological processes and molecular functions of reported kidney markers, revealed that 15 genes on the candidate list were assigned to the most significant ontology groups: immunity and defence. Other significantly enriched groups were cell communication (14 genes), signal transduction (22 genes) and apoptosis (seven genes). Among 24 candidate protein markers, nine proteins were also identified by gene expression studies. Next generation candidate marker proteins with improved diagnostic and prognostic values for kidney diseases will be derived from whole genome scans and protemics approaches. Prospective validation still remains elusive for all proposed candidates.

Analysis and prediction of protective continuous B-cell epitopes on pathogen proteins

BackgroundThe application of peptide based diagnostics and therapeutics mimicking part of protein antigen is experiencing renewed interest. So far selection and design rationale for such peptides is usually driven by T-cell epitope prediction, available experimental and modelled 3D structure, B-cell epitope predictions such as hydrophilicity plots or experience. If no structure is available the rational selection of peptides for the production of functionally altering or neutralizing antibodies is practically impossible. Specifically if many alternative antigens are available the reduction of required synthesized peptides until one successful candidate is found is of central technical interest. We have investigated the integration of B-cell epitope prediction with the variability of antigen and the conservation of patterns for post-translational modification (PTM) prediction to improve over state of the art in the field. In particular the application of machine-learning methods shows promising results.ResultsWe find that protein regions leading to the production of functionally altering antibodies are often characterized by a distinct increase in the cumulative sum of three presented parameters. Furthermore the concept to maximize antigenicity, minimize variability and minimize the likelihood of post-translational modification for the identification of relevant sites leads to biologically interesting observations. Primarily, for about 50% of antigen the approach works well with individual area under the ROC curve (AROC) values of at least 0.65. On the other hand a significant portion reveals equivalently low AROC values of < = 0.35 indicating an overall non-Gaussian distribution. While about a third of 57 antigens are seemingly intangible by our approach our results suggest the existence of at least two distinct classes of bioinformatically detectable epitopes which should be predicted separately. As a side effect of our study we present a hand curated dataset for the validation of protectivity classification. Based on this dataset machine-learning methods further improve predictive power to a class separation in an equilibrated dataset of up to 83%.ConclusionWe present a computational method to automatically select and rank peptides for the stimulation of potentially protective or otherwise functionally altering antibodies. It can be shown that integration of variability, post-translational modification pattern conservation and B-cell antigenicity improve rational selection over random guessing. Probably more important, we find that for about 50% of antigen the approach works substantially better than for the overall dataset of 57 proteins. Essentially as a side effect our method optimizes for presumably best applicable peptides as they tend to be likely unmodified and as invariable as possible which is answering needs in diagnosis and treatment of pathogen infection. In addition we show the potential for further improvement by the application of machine-learning methods, in particular Random Forests.

Alterations in Gene Expression in Cadaveric vs. Live Donor Kidneys Suggest Impaired Tubular Counterbalance of Oxidative Stress at Implantation

Recipients of live donor transplant kidneys (LIV) exhibit a significantly longer allograft half‐life compared with cadaveric donor organs (CADs). The reasons are incompletely understood. Therefore this study sought to elucidate the genome‐wide gene expression profiles in microdissected transplant kidney biopsies obtained from five cadaveric and five matched live donors before transplantation. cDNA microarrays were used to determine the transcripts in isolated glomeruli (G) and the tubulointerstitial (TI) compartment. Data were subjected to hierarchical clustering, maxT adjustment and a jackknife procedure to ensure robustness of reported findings; validation was performed by independent analysis of split biopsies and TaqMan‐PCR.

Steroid Pretreatment of Organ Donors to Prevent Postischemic Renal Allograft Failure A Randomized, Controlled Trial

BACKGROUND Posttransplantation acute renal failure (ARF) occurs in roughly 25% of recipients of organs from deceased donors. Inflammation in the donor organ is associated with risk for ARF. OBJECTIVE To determine whether administering corticosteroids to deceased organ donors reduces the incidence and duration of ARF in organ recipients more than placebo. DESIGN Parallel, blocked randomized trial, performed between February 2006 and November 2008, with computer-generated randomization and centralized allocation. Investigators were masked to group assignment. (Controlled-trials.com registration number: ISRCTN78828338) SETTING: 3 renal transplantation centers in Austria and Hungary. PATIENTS 306 deceased heart-beating donors and 455 renal transplant recipients. INTERVENTIONS Organ donors were administered an intravenous infusion of either 1000 mg of methylprednisolone (136 donors) or placebo (0.9% saline) (133 donors) at least 3 hours before organ harvesting. MEASUREMENTS Incidence of ARF, defined as more than 1 dialysis session in the first week after transplantation, was the primary end point. Secondary and other end points included duration of ARF and trajectories of serum creatinine level. The suppression of immune response and inflammation by the intervention was assessed in the donor organ on a genome-wide basis. RESULTS 52 of 238 recipients (22%) of kidneys from steroid-treated donors and 54 of 217 recipients (25%) of kidneys from placebo-treated donors had ARF (difference, 3 percentage points [95% CI, -11 to 5 percentage points]). One graft was lost on day 1 in each group, and 1 recipient in the placebo group died of cardiac arrest on day 2. The median duration of ARF was 5 days (interquartile range, 2 days) in the steroid group and 4 days (interquartile range, 2 days) in the placebo group (P = 0.31). The groups had similar trajectories of serum creatinine level in the first week (P = 0.72). Genomic analysis showed suppressed inflammation and immune response in kidney biopsies from deceased donors who received corticosteroids. LIMITATION Donors and recipients were mainly white, and all were from 3 transplantation centers in central Europe, which may limit generalizability. CONCLUSION Systemic suppression of inflammation in deceased donors by corticosteroids did not reduce the incidence or duration of posttransplantation ARF in allograft recipients. PRIMARY FUNDING SOURCE Austrian Science Fund and Austrian Academy of Science.