Publications

960 Publications visible to you, out of a total of 960

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INTRODUCTION: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. "Smart Medical Information Technology for Healthcare (SMITH)" is one of four consortia funded by the German Medical Informatics Initiative (MI-I) to create an alliance of universities, university hospitals, research institutions and IT companies. SMITH's goals are to establish Data Integration Centers (DICs) at each SMITH partner hospital and to implement use cases which demonstrate the usefulness of the approach. OBJECTIVES: To give insight into architectural design issues underlying SMITH data integration and to introduce the use cases to be implemented. GOVERNANCE AND POLICIES: SMITH implements a federated approach as well for its governance structure as for its information system architecture. SMITH has designed a generic concept for its data integration centers. They share identical services and functionalities to take best advantage of the interoperability architectures and of the data use and access process planned. The DICs provide access to the local hospitals' Electronic Medical Records (EMR). This is based on data trustee and privacy management services. DIC staff will curate and amend EMR data in the Health Data Storage. METHODOLOGY AND ARCHITECTURAL FRAMEWORK: To share medical and research data, SMITH's information system is based on communication and storage standards. We use the Reference Model of the Open Archival Information System and will consistently implement profiles of Integrating the Health Care Enterprise (IHE) and Health Level Seven (HL7) standards. Standard terminologies will be applied. The SMITH Market Place will be used for devising agreements on data access and distribution. 3LGM(2) for enterprise architecture modeling supports a consistent development process.The DIC reference architecture determines the services, applications and the standardsbased communication links needed for efficiently supporting the ingesting, data nourishing, trustee, privacy management and data transfer tasks of the SMITH DICs. The reference architecture is adopted at the local sites. Data sharing services and the market place enable interoperability. USE CASES: The methodological use case "Phenotype Pipeline" (PheP) constructs algorithms for annotations and analyses of patient-related phenotypes according to classification rules or statistical models based on structured data. Unstructured textual data will be subject to natural language processing to permit integration into the phenotyping algorithms. The clinical use case "Algorithmic Surveillance of ICU Patients" (ASIC) focusses on patients in Intensive Care Units (ICU) with the acute respiratory distress syndrome (ARDS). A model-based decision-support system will give advice for mechanical ventilation. The clinical use case HELP develops a "hospital-wide electronic medical record-based computerized decision support system to improve outcomes of patients with blood-stream infections" (HELP). ASIC and HELP use the PheP. The clinical benefit of the use cases ASIC and HELP will be demonstrated in a change of care clinical trial based on a step wedge design. DISCUSSION: SMITH's strength is the modular, reusable IT architecture based on interoperability standards, the integration of the hospitals' information management departments and the public-private partnership. The project aims at sustainability beyond the first 4-year funding period.

Authors: A. Winter, S. Staubert, D. Ammon, S. Aiche, O. Beyan, V. Bischoff, P. Daumke, S. Decker, G. Funkat, J. E. Gewehr, A. de Greiff, S. Haferkamp, U. Hahn, A. Henkel, T. Kirsten, T. Kloss, J. Lippert, M. Lobe, V. Lowitsch, O. Maassen, J. Maschmann, S. Meister, R. Mikolajczyk, M. Nuchter, M. W. Pletz, E. Rahm, M. Riedel, K. Saleh, A. Schuppert, S. Smers, A. Stollenwerk, S. Uhlig, T. Wendt, S. Zenker, W. Fleig, G. Marx, A. Scherag, M. Loffler

Date Published: 18th Jul 2018

Publication Type: Journal article

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RATIONALE During pneumonia, pathogen-host interaction evokes inflammation and lung barrier dysfunction. Tie2-activation by Angiopoietin-1 reduces, while Tie2-blockade by Angiopoietin-2 increasess inflammation and permeability during sepsis. The role of Angiopoietin-1/-2 in pneumonia remains unidentified. OBJECTIVES To investigate the prognostic and pathogenetic impact of Angiopoietins in regulating pulmonary vascular barrier function and inflammation in bacterial pneumonia. METHODS Serum Angiopoietin levels were quantified in pneumonia patients of two independent cohorts (n=148, n=395). Human post mortem lung tissue, pneumolysin- or Angiopoietin-2-stimulated endothelial cells, isolated perfused and ventilated mouse lungs, and mice with pneumococcal pneumonia were investigated. MEASUREMENTS AND MAIN RESULTS In pneumonia patients, decreased serum Angiopoietin-1 and increased Angiopoietin-2 levels were observed as compared to healthy subjects. Higher Angiopoietin-2 serum levels were found in community-acquired pneumonia patients who died within 28 days after diagnosis compared to survivors. ROC analysis revealed improved prognostic accuracy of CURB-65 for 28-day survival, intensive care treatment and length of hospital stay if combined with Angiopoietin-2 serum levels. In vitro, pneumolysin enhanced endothelial Angiopoietin-2 release, Angiopoietin-2 increased endothelial permeability, and Angiopoietin-1 reduced pneumolysin-evoked endothelial permeability. Ventilated and perfused lungs of mice with Angiopoietin-2-knockdown showed reduced permeability upon pneumolysin stimulation. Increased pulmonary Angiopoietin-2 and reduced Angiopoietin-1 mRNA expression were observed in S. pneumoniae infected mice. Finally, Angiopoietin-1 therapy reduced inflammation and permeability in murine pneumonia. CONCLUSIONS These data suggest a central role of Angiopoietin-1/-2 in pneumonia-evoked inflammation and permeability. Increased Angiopoietin-2 serum levels predicted mortality and length of hospital stay, and Angiopoietin-1 may provide a therapeutic target for severe pneumonia.

Authors: Birgitt Gutbier, Anne-Kathrin Neuhauß, Katrin Reppe, Carolin Ehrler, Ansgar Santel, Jörg Kaufmann, Markus Scholz, Norbert Weissmann, Lars Morawietz, Timothy J. Mitchell, Stefano Aliberti, Stefan Hippenstiel, Norbert Suttorp, Martin Witzenrath

Date Published: 15th Jul 2018

Publication Type: Journal article

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Recent studies revealed trajectories of mutational events in early melanomagenesis, but the accompanying changes in gene expression are far less understood. Therefore, we performed a comprehensive RNA-seq analysis of laser-microdissected melanocytic nevi (n = 23) and primary melanoma samples (n = 57) and characterized the molecular mechanisms of early melanoma development. Using self-organizing maps, unsupervised clustering, and analysis of pseudotime (PT) dynamics to identify evolutionary trajectories, we describe here two transcriptomic types of melanocytic nevi (N1 and N2) and primary melanomas (M1 and M2). N1/M1 lesions are characterized by pigmentation-type and MITF gene signatures, and a high prevalence of NRAS mutations in M1 melanomas. N2/M2 lesions are characterized by inflammatory-type and AXL gene signatures with an equal distribution of wild-type and mutated BRAF and low prevalence of NRAS mutations in M2 melanomas. Interestingly, N1 nevi and M1 melanomas and N2 nevi and M2 melanomas, respectively, cluster together, but there is no clustering in a stage-dependent manner. Transcriptional signatures of M1 melanomas harbor signatures of BRAF/MEK inhibitor resistance and M2 melanomas harbor signatures of anti-PD-1 antibody treatment resistance. Pseudotime dynamics of nevus and melanoma samples are suggestive for a switch-like immune-escape mechanism in melanoma development with downregulation of immune genes paralleled by an increasing expression of a cell cycle signature in late-stage melanomas. Taken together, the transcriptome analysis identifies gene signatures and mechanisms underlying development of melanoma in early and late stages with relevance for diagnostics and therapy.

Authors: M. Kunz, H. Loffler-Wirth, M. Dannemann, E. Willscher, G. Doose, J. Kelso, T. Kottek, B. Nickel, L. Hopp, J. Landsberg, S. Hoffmann, T. Tuting, P. Zigrino, C. Mauch, J. Utikal, M. Ziemer, H. J. Schulze, M. Holzel, A. Roesch, S. Kneitz, S. Meierjohann, A. Bosserhoff, H. Binder, M. Schartl

Date Published: 12th Jul 2018

Publication Type: Not specified

Human Diseases: melanoma

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The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P \textless 5.82 \times 10-6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

Authors: Lang Wu, Wei Shi, Jirong Long, Xingyi Guo, Kyriaki Michailidou, Jonathan Beesley, Manjeet K. Bolla, Xiao-Ou Shu, Yingchang Lu, Qiuyin Cai, Fares Al-Ejeh, Esdy Rozali, Qin Wang, Joe Dennis, Bingshan Li, Chenjie Zeng, Helian Feng, Alexander Gusev, Richard T. Barfield, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Kristan J. Aronson, Paul L. Auer, Myrto Barrdahl, Caroline Baynes, Matthias W. Beckmann, Javier Benitez, Marina Bermisheva, Carl Blomqvist, Natalia V. Bogdanova, Stig E. Bojesen, Hiltrud Brauch, Hermann Brenner, Louise Brinton, Per Broberg, Sara Y. Brucker, Barbara Burwinkel, Trinidad Caldés, Federico Canzian, Brian D. Carter, J. Esteban Castelao, Jenny Chang-Claude, Xiaoqing Chen, Ting-Yuan David Cheng, Hans Christiansen, Christine L. Clarke, Margriet Collée, Sten Cornelissen, Fergus J. Couch, David Cox, Angela Cox, Simon S. Cross, Julie M. Cunningham, Kamila Czene, Mary B. Daly, Peter Devilee, Kimberly F. Doheny, Thilo Dörk, Isabel Dos-Santos-Silva, Martine Dumont, Miriam Dwek, Diana M. Eccles, Ursula Eilber, A. Heather Eliassen, Christoph Engel, Mikael Eriksson, Laura Fachal, Peter A. Fasching, Jonine Figueroa, Dieter Flesch-Janys, Olivia Fletcher, Henrik Flyger, Lin Fritschi, Marike Gabrielson, Manuela Gago-Dominguez, Susan M. Gapstur, Montserrat García-Closas, Mia M. Gaudet, Maya Ghoussaini, Graham G. Giles, Mark S. Goldberg, David E. Goldgar, Anna González-Neira, Pascal Guénel, Eric Hahnen, Christopher A. Haiman, Niclas Håkansson, Per Hall, Emily Hallberg, Ute Hamann, Patricia Harrington, Alexander Hein, Belynda Hicks, Peter Hillemanns, Antoinette Hollestelle, Robert N. Hoover, John L. Hopper, Guanmengqian Huang, Keith Humphreys, David J. Hunter, Anna Jakubowska, Wolfgang Janni, Esther M. John, Nichola Johnson, Kristine Jones, Michael E. Jones, Audrey Jung, Rudolf Kaaks, Michael J. Kerin, Elza Khusnutdinova, Veli-Matti Kosma, Vessela N. Kristensen, Diether Lambrechts, Loic Le Marchand, Jingmei Li, Sara Lindström, Jolanta Lissowska, Wing-Yee Lo, Sibylle Loibl, Jan Lubinski, Craig Luccarini, Michael P. Lux, Robert J. MacInnis, Tom Maishman, Ivana Maleva Kostovska, Arto Mannermaa, JoAnn E. Manson, Sara Margolin, Dimitrios Mavroudis, Hanne Meijers-Heijboer, Alfons Meindl, Usha Menon, Jeffery Meyer, Anna Marie Mulligan, Susan L. Neuhausen, Heli Nevanlinna, Patrick Neven, Sune F. Nielsen, Børge G. Nordestgaard, Olufunmilayo I. Olopade, Janet E. Olson, Håkan Olsson, Paolo Peterlongo, Julian Peto, Dijana Plaseska-Karanfilska, Ross Prentice, Nadege Presneau, Katri Pylkäs, Brigitte Rack, Paolo Radice, Nazneen Rahman, Gad Rennert, Hedy S. Rennert, Valerie Rhenius, Atocha Romero, Jane Romm, Anja Rudolph, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Marjanka K. Schmidt, Rita K. Schmutzler, Andreas Schneeweiss, Rodney J. Scott, Christopher G. Scott, Sheila Seal, Mitul Shah, Martha J. Shrubsole, Ann Smeets, Melissa C. Southey, John J. Spinelli, Jennifer Stone, Harald Surowy, Anthony J. Swerdlow, Rulla M. Tamimi, William Tapper, Jack A. Taylor, Mary Beth Terry, Daniel C. Tessier, Abigail Thomas, Kathrin Thöne, Rob A. E. M. Tollenaar, Diana Torres, Thérèse Truong, Michael Untch, Celine Vachon, David van den Berg, Daniel Vincent, Quinten Waisfisz, Clarice R. Weinberg, Camilla Wendt, Alice S. Whittemore, Hans Wildiers, Walter C. Willett, Robert Winqvist, Alicja Wolk, Lucy Xia, Xiaohong R. Yang, Argyrios Ziogas, Elad Ziv, Alison M. Dunning, Paul D. P. Pharoah, Jacques Simard, Roger L. Milne, Stacey L. Edwards, Peter Kraft, Douglas F. Easton, Georgia Chenevix-Trench, Wei Zheng

Date Published: 1st Jul 2018

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

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BACKGROUND/OBJECTIVES Acute pancreatitis (AP) is one of the most common gastrointestinal disorders often requiring hospitalization. Frequent aetiologies are gallstones and alcohol abuse. In contrastt to chronic pancreatitis (CP) few robust genetic associations have been described. Here we analysed whether common variants in the CLDN2-MORC4 and the PRSS1-PRSS2 locus that increase recurrent AP and CP risk associate with AP. METHODS We screened 1462 AP patients and 3999 controls with melting curve analysis for SNPs rs10273639 (PRSS1-PRSS2), rs7057398 (RIPPLY), and rs12688220 (MORC4). Calculations were performed for the overall group, aetiology, and gender sub-groups. To examine genotype-phenotype relationships we performed several meta-analyses. RESULTS Meta-analyses of all AP patients depicted significant (p-value \textless 0.05) associations for rs10273639 (odds ratio (OR) 0.88, 95% confidence interval (CI) 0.81-0.97, p-value 0.01), rs7057398 (OR 1.27, 95% CI 1.07-1.5, p-value 0.005), and rs12688220 (OR 1.32, 95% CI 1.12-1.56, p-value 0.001). For the different aetiology groups a significant association was shown for rs10273639 (OR 0.76, 95% CI 0.63-0.92, p-value 0.005), rs7057398 (OR 1.43, 95% CI 1.07-1.92, p-value 0.02), and rs12688220 (OR 1.44, 95% CI 1.07-1.93, p-value 0.02) in the alcoholic sub-group only. CONCLUSIONS The association of CP risk variants with different AP aetiologies, which is strongest in the alcoholic AP group, might implicate common pathomechanisms most likely between alcoholic AP and CP.

Authors: Frank Ulrich Weiss, Nico Hesselbarth, Andrea Párniczky, Dora Mosztbacher, Felix Lämmerhirt, Claudia Ruffert, Peter Kovacs, Sebastian Beer, Katharina Seltsam, Heidi Griesmann, Richard Böhme, Tom Kaune, Marcus Hollenbach, Hans-Ulrich Schulz, Peter Simon, Julia Mayerle, Markus M. Lerch, Giulia Martina Cavestro, Raffaella Alessia Zuppardo, Milena Di Leo, Pier Alberto Testoni, Ewa Malecka-Panas, Anita Gasirowska, Stanislaw Głuszek, Peter Bugert, Andrea Szentesi, Joachim Mössner, Heiko Witt, Patrick Michl, Peter Hégyi, Markus Scholz, Jonas Rosendahl

Date Published: 1st Jul 2018

Publication Type: Journal article

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AIM: We present here a novel method that enables unraveling the interplay between gene expression and DNA methylation in complex diseases such as cancer. MATERIALS & METHODS: The method is based on self-organizing maps and allows for analysis of data landscapes from 'governed by methylation' to 'governed by expression'. RESULTS: We identified regulatory modules of coexpressed and comethylated genes in high-grade gliomas: two modes are governed by genes hypermethylated and underexpressed in IDH-mutated cases, while two other modes reflect immune and stromal signatures in the classical and mesenchymal subtypes. A fifth mode with proneural characteristics comprises genes of repressed and poised chromatin states active in healthy brain. Two additional modes enrich genes either in active or repressed chromatin states. CONCLUSION: The method disentangles the interplay between gene expression and methylation. It has the potential to integrate also mutation and copy number data and to apply to large sample cohorts.

Authors: L. Hopp, H. Loffler-Wirth, J. Galle, H. Binder

Date Published: 12th Jun 2018

Publication Type: Not specified

Human Diseases: glioblastoma multiforme

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Metadata Repositories (MDR) are databases for data elements that can be utilized in research as well as in medical care. These data elements are not the actual patient data (facts), but a complete definition of the variables or characteristics used, including coding, unit of measurement, data type and other aspects. The aim of the project described here was to evaluate possible application scenarios for MDRs by a larger group of experts. The focus was not on specific software, but on the community's basic expectation of such a database of data elements. To achieve this goal, a questionnaire was designed that contained questions on general aspects of setting up a registry for data elements in biomedical research as well as more specific points with regard to necessary functionalities, desired contents, tools for community work and the quality of data elements. One of the main results was that the users attach more importance to the quality of the content than to the efficiency in implementing their documentation concepts. At the same time, they consider the effort involved in using existing software systems to be too much compared with the benefits and have concerns about the use of their designs by third parties.

Author: Matthias Löbe

Date Published: 9th May 2018

Publication Type: Misc

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