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37 Publications visible to you, out of a total of 37

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Abstract Background and Aims The presence of significant liver fibrosis associated with non‐alcoholic steatohepatitis (NASH) is regarded as the major prognostic factor in non‐alcoholic fatty liverhe major prognostic factor in non‐alcoholic fatty liver disease (NAFLD). Identification of patients at risk for NASH with significant fibrosis is therefore important. Although the established fibrosis score FIB‐4 is suitable to exclude advanced fibrosis, it does not allow the prediction of significant fibrosis in NAFLD patients. We therefore evaluated whether the hepatokine fibroblast growth factor 21 (FGF21), a regulator of glucose and lipid metabolism, might identify ‘at‐risk NASH’ in NAFLD. Methods FGF21 levels were assessed by enzyme‐linked immunosorbent assay in sera from an exploration ( n  = 137) and a validation ( n  = 88) cohort of biopsy‐proven NAFLD patients with different disease activity and fibrosis stages. In addition, we evaluated whether the use of FGF21 could improve risk stratification in NAFLD patients with low (<1.3) or intermediate (1.3–2.67) FIB‐4. Results FGF21 levels could significantly discriminate between NASH and non‐alcoholic fatty liver (NAFL) patients, even in the absence of diabetes. Moreover, patients with NASH and fibrosis ≥F2 showed significantly higher FGF21 levels compared to NAFLD patients without significant fibrosis. Significantly elevated FGF21 levels could even be detected in NAFLD patients with NASH and significant fibrosis despite low or intermediate FIB‐4. Conclusion Serological FGF21 detection might allow the identification of NAFLD patients at risk and improves patient stratification in combination with FIB‐4.

Authors: Martin Franck, Katharina John, Sherin Al Aoua, Monika Rau, Andreas Geier, Jörn M. Schattenberg, Heiner Wedemeyer, Klaus Schulze‐Osthoff, Heike Bantel

Date Published: 3rd Aug 2023

Publication Type: Journal

Abstract

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Authors: Dirk Drasdo, Jieling Zhao

Date Published: 1st Aug 2023

Publication Type: Journal

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Abstract The human liver has a remarkable capacity to regenerate and thus compensate over decades for fibrosis caused by toxic chemicals, drugs, alcohol, or malnutrition. To date, no protective mechanismsrition. To date, no protective mechanisms have been identified that help the liver tolerate these repeated injuries. In this study, we revealed dysregulation of lipid metabolism and mild inflammation as protective mechanisms by studying longitudinal multi-omic measurements of liver fibrosis induced by repeated CCl 4 injections in mice ( n  = 45). Based on comprehensive proteomics, transcriptomics, blood- and tissue-level profiling, we uncovered three phases of early disease development—initiation, progression, and tolerance. Using novel multi-omic network analysis, we identified multi-level mechanisms that are significantly dysregulated in the injury-tolerant response. Public data analysis shows that these profiles are altered in human liver diseases, including fibrosis and early cirrhosis stages. Our findings mark the beginning of the tolerance phase as the critical switching point in liver response to repetitive toxic doses. After fostering extracellular matrix accumulation as an acute response, we observe a deposition of tiny lipid droplets in hepatocytes only in the Tolerant phase. Our comprehensive study shows that lipid metabolism and mild inflammation may serve as biomarkers and are putative functional requirements to resist further disease progression.

Authors: Seddik Hammad, Christoph Ogris, Amnah Othman, Pia Erdoesi, Wolfgang Schmidt-Heck, Ina Biermayer, Barbara Helm, Yan Gao, Weronika Piorońska, Christian H. Holland, Lorenza A. D’Alessandro, Carolina de la Torre, Carsten Sticht, Sherin Al Aoua, Fabian J. Theis, Heike Bantel, Matthias P. Ebert, Ursula Klingmüller, Jan G. Hengstler, Steven Dooley, Nikola S. Mueller

Date Published: 1st Jul 2023

Publication Type: Journal

Abstract

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Authors: Mihael Vucur, Ahmed Ghallab, Anne T. Schneider, Arlind Adili, Mingbo Cheng, Mirco Castoldi, Michael T. Singer, Veronika Büttner, Leonie S. Keysberg, Lena Küsgens, Marlene Kohlhepp, Boris Görg, Suchira Gallage, Jose Efren Barragan Avila, Kristian Unger, Claus Kordes, Anne-Laure Leblond, Wiebke Albrecht, Sven H. Loosen, Carolin Lohr, Markus S. Jördens, Anne Babler, Sikander Hayat, David Schumacher, Maria T. Koenen, Olivier Govaere, Mark V. Boekschoten, Simone Jörs, Carlos Villacorta-Martin, Vincenzo Mazzaferro, Josep M. Llovet, Ralf Weiskirchen, Jakob N. Kather, Patrick Starlinger, Michael Trauner, Mark Luedde, Lara R. Heij, Ulf P. Neumann, Verena Keitel, Johannes G. Bode, Rebekka K. Schneider, Frank Tacke, Bodo Levkau, Twan Lammers, Georg Fluegen, Theodore Alexandrov, Amy L. Collins, Glyn Nelson, Fiona Oakley, Derek A. Mann, Christoph Roderburg, Thomas Longerich, Achim Weber, Augusto Villanueva, Andre L. Samson, James M. Murphy, Rafael Kramann, Fabian Geisler, Ivan G. Costa, Jan G. Hengstler, Mathias Heikenwalder, Tom Luedde

Date Published: 1st Jul 2023

Publication Type: Journal

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The interplay between chromatin, transcription factors and genes generates complex regulatory circuits that can be represented as gene regulatory networks (GRNs). The study of GRNs is useful to understand how cellular identity is established, maintained and disrupted in disease. GRNs can be inferred from experimental data - historically, bulk omics data - and/or from the literature. The advent of single-cell multi-omics technologies has led to the development of novel computational methods that leverage genomic, transcriptomic and chromatin accessibility information to infer GRNs at an unprecedented resolution. Here, we review the key principles of inferring GRNs that encompass transcription factor-gene interactions from transcriptomics and chromatin accessibility data. We focus on the comparison and classification of methods that use single-cell multimodal data. We highlight challenges in GRN inference, in particular with respect to benchmarking, and potential further developments using additional data modalities.

Authors: P. Badia-I-Mompel, L. Wessels, S. Muller-Dott, R. Trimbour, R. O. Ramirez Flores, R. Argelaguet, J. Saez-Rodriguez

Date Published: 26th Jun 2023

Publication Type: Journal

Abstract

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Authors: Yoon Seok Jung, Yong-Hoon Kim, Kamalakannan Radhakrishnan, Jung-Ran Noh, Jung Hyeon Choi, Hyo-Jin Kim, Jae-Ho Jeong, Steven Dooley, Chul-Ho Lee, Hueng-Sik Choi

Date Published: 1st May 2023

Publication Type: Journal

Abstract

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Authors: Stefan Hoehme, Seddik Hammad, Jan Boettger, Brigitte Begher-Tibbe, Petru Bucur, Eric Vibert, Rolf Gebhardt, Jan G. Hengstler, Dirk Drasdo

Date Published: 2023

Publication Type: Journal

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Background: Macrophages play an important role in maintaining liver homeostasis and regeneration. However, it is not clear to what extent the different macrophage populations of the liver differ in terms of their activation state and which other liver cell populations may play a role in regulating the same. Methods: Reverse transcription PCR, flow cytometry, transcriptome, proteome, secretome, single cell analysis, and immunohistochemical methods were used to study changes in gene expression as well as the activation state of macrophages in vitro and in vivo under homeostatic conditions and after partial hepatectomy. Results: We show that F4/80+/CD11bhi/CD14hi macrophages of the liver are recruited in a C-C motif chemokine receptor (CCR2)–dependent manner and exhibit an activation state that differs substantially from that of the other liver macrophage populations, which can be distinguished on the basis of CD11b and CD14 expressions. Thereby, primary hepatocytes are capable of creating an environment in vitro that elicits the same specific activation state in bone marrow–derived macrophages as observed in F4/80+/CD11bhi/CD14hi liver macrophages in vivo. Subsequent analyses, including studies in mice with a myeloid cell–specific deletion of the TGF-β type II receptor, suggest that the availability of activated TGF-β and its downregulation by a hepatocyte-conditioned milieu are critical. Reduction of TGF-βRII-mediated signal transduction in myeloid cells leads to upregulation of IL-6, IL-10, and SIGLEC1 expression, a hallmark of the activation state of F4/80+/CD11bhi/CD14hi macrophages, and enhances liver regeneration. Conclusions: The availability of activated TGF-β determines the activation state of specific macrophage populations in the liver, and the observed rapid transient activation of TGF-β may represent an important regulatory mechanism in the early phase of liver regeneration in this context.

Authors: Stephanie D. Wolf, Christian Ehlting, Sophia Müller-Dott, Gereon Poschmann, Patrick Petzsch, Tobias Lautwein, Sai Wang, Barbara Helm, Marcel Schilling, Julio Saez-Rodriguez, Mihael Vucur, Kai Stühler, Karl Köhrer, Frank Tacke, Steven Dooley, Ursula Klingmüller, Tom Luedde, Johannes G. Bode

Date Published: 2023

Publication Type: Journal

Abstract

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Authors: Sai Wang, Frederik Link, Rilu Feng, Stefan Munker, Yujia Li, Roman Liebe, Matthias P. Ebert, Steven Dooley, Huiguo Ding, Shanshan Wang, Honglei Weng

Date Published: 2023

Publication Type: Journal

Abstract

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Authors: Alaa Hammad, Seddik Hammad, Kerry Gould, Matthias P. Ebert, Steven Dooley, Anne Dropmann

Date Published: 2023

Publication Type: Journal

Abstract

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Authors: Seddik Hammad, Christoph Ogris, Amnah Othman, Pia Erdoesi, Wolfgang Schmidt-Heck, Ina Biermayer, Barbara Helm, Yan Gao, Weronika Piorońska, Lorenza D'Alessandro, Fabian J. Theis, Matthias P. Ebert, Ursula Klingmüller, Jan Hengstler, Nikola S. Mueller, Steven Dooley

Date Published: 2023

Publication Type: Journal

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MOTIVATION: Over the last decades, image processing and analysis have become one of the key technologies in systems biology and medicine. The quantification of anatomical structures and dynamic processes in living systems is essential for understanding the complex underlying mechanisms and allows, i.e. the construction of spatio-temporal models that illuminate the interplay between architecture and function. Recently, deep learning significantly improved the performance of traditional image analysis in cases where imaging techniques provide large amounts of data. However, if only a few images are available or qualified annotations are expensive to produce, the applicability of deep learning is still limited. RESULTS: We present a novel approach that combines machine learning-based interactive image segmentation using supervoxels with a clustering method for the automated identification of similarly colored images in large image sets which enables a guided reuse of interactively trained classifiers. Our approach solves the problem of deteriorated segmentation and quantification accuracy when reusing trained classifiers which is due to significant color variability prevalent and often unavoidable in biological and medical images. This increase in efficiency improves the suitability of interactive segmentation for larger image sets, enabling efficient quantification or the rapid generation of training data for deep learning with minimal effort. The presented methods are applicable for almost any image type and represent a useful tool for image analysis tasks in general. AVAILABILITY AND IMPLEMENTATION: The presented methods are implemented in our image processing software TiQuant which is freely available at tiquant.hoehme.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Authors: A. Friebel, T. Johann, D. Drasdo, S. Hoehme

Date Published: 30th Sep 2022

Publication Type: Journal

Abstract

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Authors: Yujia Li, Weiguo Fan, Frederik Link, Sai Wang, Steven Dooley

Date Published: 1st Feb 2022

Publication Type: Journal

Abstract (Expand)

Abstract Chronic alcohol consumption induces stress and damage in alcohol metabolising hepatocytes, which leads to inflammatory and fibrogenic responses. Besides these direct effects, alcohol disruptsffects, alcohol disrupts intestinal barrier functions and induces gut microbial dysbiosis, causing translocation of bacteria or microbial products through the gut mucosa to the liver and, which induce inflammation indirectly. Inflammation is one of the key drivers of alcohol-associated liver disease progression from steatosis to severe alcoholic hepatitis. The current standard of care for the treatment of severe alcoholic hepatitis is prednisolone, aiming to reduce inflammation. Prednisolone, however improves only short-term but not long-term survival rates in those patients, and even increases the risk for bacterial infections. Thus, recent studies focus on the exploration of more specific inflammatory targets for the treatment of severe alcoholic hepatitis. These comprise, among others interference with inflammatory cytokines, modulation of macrophage phenotypes or targeting of immune cell communication, as summarized in the present overview. Although several approaches give promising results in preclinical studies, data robustness and ability to transfer experimental results to human disease is still not sufficient for effective clinical translation.

Authors: Sophie Lotersztajn, Antonio Riva, Sai Wang, Steven Dooley, Shilpa Chokshi, Bin Gao

Date Published: 18th Jan 2022

Publication Type: Journal

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Abstract Alcohol-related liver disease (ALD) impacts millions of patients worldwide each year and the numbers are increasing. Disease stages range from steatosis via steatohepatitis and fibrosis toepatitis and fibrosis to cirrhosis, severe alcohol-associated hepatitis and liver cancer. ALD is usually diagnosed at an advanced stage of progression with no effective therapies. A major research goal is to improve diagnosis, prognosis and also treatments for early ALD. This however needs prioritization of this disease for financial investment in basic and clinical research to more deeply investigate mechanisms and identify biomarkers and therapeutic targets for early detection and intervention. Topics of interest are communication of the liver with other organs of the body, especially the gut microbiome, the individual genetic constitution, systemic and liver innate inflammation, including bacterial infections, as well as fate and number of hepatic stellate cells and the composition of the extracellular matrix in the liver. Additionally, mechanical forces and damaging stresses towards the sophisticated vessel system of the liver, including the especially equipped sinusoidal endothelium and the biliary tract, work together to mediate hepatocytic import and export of nutritional and toxic substances, adapting to chronic liver disease by morphological and functional changes. All the aforementioned parameters contribute to the outcome of alcohol use disorder and the risk to develop advanced disease stages including cirrhosis, severe alcoholic hepatitis and liver cancer. In the present collection, we summarize current knowledge on these alcohol-related liver disease parameters, excluding the aspect of inflammation, which is presented in the accompanying review article by Lotersztajn and colleagues.

Authors: Bernd Schnabl, Gavin E. Arteel, Felix Stickel, Jan Hengstler, Nachiket Vartak, Ahmed Ghallab, Steven Dooley, Yujia Li, Robert F. Schwabe

Date Published: 18th Jan 2022

Publication Type: Journal

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