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4 Publications visible to you, out of a total of 4
From heterogeneous healthcare data to disease-specific biomarker networks: A hierarchical Bayesian network approach.

Abstract (Expand)

In this work, we introduce an entirely data-driven and automated approach to reveal disease-associated biomarker and risk factor networks from heterogeneous and high-dimensional healthcare data. Our … workflow is based on Bayesian networks, which are a popular tool for analyzing the interplay of biomarkers. Usually, data require extensive manual preprocessing and dimension reduction to allow for effective learning of Bayesian networks. For heterogeneous data, this preprocessing is hard to automatize and typically requires domain-specific prior knowledge. We here combine Bayesian network learning with hierarchical variable clustering in order to detect groups of similar features and learn interactions between them entirely automated. We present an optimization algorithm for the adaptive refinement of such group Bayesian networks to account for a specific target variable, like a disease. The combination of Bayesian networks, clustering, and refinement yields low-dimensional but disease-specific interaction networks. These networks provide easily interpretable, yet accurate models of biomarker interdependencies. We test our method extensively on simulated data, as well as on data from the Study of Health in Pomerania (SHIP-TREND), and demonstrate its effectiveness using non-alcoholic fatty liver disease and hypertension as examples. We show that the group network models outperform available biomarker scores, while at the same time, they provide an easily interpretable interaction network.

Authors: A. K. Becker, M. Dorr, S. B. Felix, F. Frost, H. J. Grabe, M. M. Lerch, M. Nauck, U. Volker, H. Volzke, L. Kaderali

Date Published: 13th Feb 2021

Publication Type: Journal

Expression Analysis of Fibronectin Type III Domain-Containing (FNDC) Genes in Inflammatory Bowel Disease and Colorectal Cancer.

Abstract (Expand)

Background: Fibronectin type III domain-containing (FNDC) proteins fulfill manifold functions in tissue development and regulation of cellular metabolism. FNDC4 was described as anti-inflammatory factor, … upregulated in inflammatory bowel disease (IBD). FNDC signaling includes direct cell-cell interaction as well as release of bioactive peptides, like shown for FNDC4 or FNDC5. The G-protein-coupled receptor 116 (GPR116) was found as a putative FNDC4 receptor. We here aim to comprehensively analyze the mRNA expression of FNDC1, FNDC3A, FNDC3B, FNDC4, FNDC5, and GPR116 in nonaffected and affected mucosal samples of patients with IBD or colorectal cancer (CRC). Methods: Mucosa samples were obtained from 30 patients undergoing diagnostic colonoscopy or from surgical resection of IBD or CRC. Gene expression was determined by quantitative real-time PCR. In addition, FNDC expression data from publicly available Gene Expression Omnibus (GEO) data sets (GDS4296, GDS4515, and GDS5232) were analyzed. Results: Basal mucosal expression revealed higher expression of FNDC3A and FNDC5 in the ileum compared to colonic segments. FNDC1 and FNDC4 were significantly upregulated in IBD. None of the investigated FNDCs was differentially expressed in CRC, just FNDC3A trended to be upregulated. The GEO data set analysis revealed significantly downregulated FNDC4 and upregulated GPR116 in microsatellite unstable (MSI) CRCs. The expression of FNDCs and GPR116 was independent of age and sex. Conclusions: FNDC1 and FNDC4 may play a relevant role in the pathobiology of IBD, but none of the investigated FNDCs is regulated in CRC. GPR116 may be upregulated in advanced or MSI CRC. Further studies should validate the altered FNDC expression results on protein levels and examine the corresponding functional consequences.

Authors: T. Wuensch, J. Wizenty, J. Quint, W. Spitz, M. Bosma, O. Becker, A. Adler, W. Veltzke-Schlieker, M. Stockmann, S. Weiss, M. Biebl, J. Pratschke, F. Aigner

Date Published: 17th May 2019

Publication Type: Not specified

Epigenomic map of human liver reveals principles of zonated morphogenic and metabolic control

Abstract (Expand)

A deeper epigenomic understanding of spatial organization of cells in human tissues is an important challenge. Here we report the first combined positional analysis of transcriptomes and methylomes … across three micro-dissected zones (pericentral, intermediate and periportal) of human liver. We identify pronounced anti-correlated transcriptional and methylation gradients including a core of 271 genes controlling zonated metabolic and morphogen networks and observe a prominent porto-central gradient of DNA methylation at binding sites of 46 transcription factors. The gradient includes an epigenetic and transcriptional Wnt signature supporting the concept of a pericentral hepatocyte regeneration pathway under steady-state conditions. While donors with non-alcoholic fatty liver disease show consistent gene expression differences corresponding to the severity of the disease across all zones, the relative zonated gene expression and DNA methylation patterns remain unchanged. Overall our data provide a wealth of new positional insights into zonal networks controlled by epigenetic and transcriptional gradients in human liver.

Authors: Mario Brosch, Kathrin Kattler, Alexander Herrmann, Witigo von Schönfels, Karl Nordström, Daniel Seehofer, Georg Damm, Thomas Becker, Sebastian Zeissig, Sophie Nehring, Fabian Reichel, Vincent Moser, Raghavan Veera Thangapandi, Felix Stickel, Gustavo Baretton, Christoph Röcken, Michael Muders, Madlen Matz-Soja, Michael Krawczak, Gilles Gasparoni, Hella Hartmann, Andreas Dahl, Clemens Schafmayer, Jörn Walter, Jochen Hampe

Date Published: 1st Dec 2018

Publication Type: Not specified

Evolutionary Distance Predicts Recurrence After Liver Transplantation in Multifocal Hepatocellular Carcinoma.

Abstract (Expand)

BACKGROUND: Liver transplantation (LTx) is a potentially curative treatment option for hepatocellular carcinoma (HCC) in cirrhosis. However, patients, where HCC is already a systemic disease, LTx may … be individually harmful and has a negative impact on donor organ usage. Thus, there is a need for improved selection criteria beyond nodule morphology to select patients with a favorable outcome for LTx in multifocal HCC. Evolutionary distance measured from genome-wide single-nucleotide polymorphism data between tumor nodules and the cirrhotic liver may be a prognostic marker of survival after LTx for multifocal HCC. METHODS: In a retrospective multicenter study, clinical data and formalin-fixed paraffin-embedded specimens of the liver and 2 tumor nodules were obtained from explants of 30 patients in the discovery and 180 patients in the replication cohort. DNA was extracted from formalin-fixed paraffin-embedded specimens followed by genome wide single-nucleotide polymorphism genotyping. RESULTS: Genotype quality criteria allowed for analysis of 8 patients in the discovery and 17 patients in the replication set. DNA concentrations of a total of 25 patients fulfilled the quality criteria and were included in the analysis. Both, in the discovery (P = 0.04) and in the replication data sets (P = 0.01), evolutionary distance was associated with the risk of recurrence of HCC after transplantation (combined P = 0.0002). In a univariate analysis, evolutionary distance (P = 7.4 x 10) and microvascular invasion (P = 1.31 x 10) were significantly associated with survival in a Cox regression analysis. CONCLUSIONS: Evolutionary distance allows for the determination of a high-risk group of recurrence if preoperative liver biopsy is considered.

Authors: N. Heits, M. Brosch, A. Herrmann, R. Behrens, C. Rocken, H. Schrem, A. Kaltenborn, J. Klempnauer, H. H. Kreipe, B. Reichert, C. Lenschow, C. Wilms, T. Vogel, H. Wolters, E. Wardelmann, D. Seehofer, S. Buch, S. Zeissig, S. Pannach, N. Raschzok, M. Dietel, W. von Schoenfels, S. Hinz, A. Teufel, M. Evert, A. Franke, T. Becker, F. Braun, J. Hampe, C. Schafmayer

Date Published: 12th Jul 2018

Publication Type: Not specified

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