Filter and export

Publications

468 Publications visible to you, out of a total of 468
Telomere Length Maintenance and Its Transcriptional Regulation in Lynch Syndrome and Sporadic Colorectal Carcinoma.
HNPCC-Sys - Genomic and transcriptomic heterogeneity of colorectal tumours arising in Lynch syndrome, oBIG - omics Bioinformatics for Health

Abstract (Expand)

Background: Activation of telomere maintenance mechanisms (TMMs) is a hallmark of most cancers, and is required to prevent genome instability and to establish cellular immortality through reconstitution … of capping of chromosome ends. TMM depends on the cancer type. Comparative studies linking tumor biology and TMM have potential impact for evaluating cancer onset and development. Methods: We have studied alterations of telomere length, their sequence composition and transcriptional regulation in mismatch repair deficient colorectal cancers arising in Lynch syndrome (LS-CRC) and microsatellite instable (MSI) sporadic CRC (MSI s-CRC), and for comparison, in microsatellite stable (MSS) s-CRC and in benign colon mucosa. Our study applied bioinformatics analysis of whole genome DNA and RNA sequencing data and a pathway model to study telomere length alterations and the potential effect of the "classical" telomerase (TEL-) and alternative (ALT-) TMM using transcriptomic signatures. Results: We have found progressive decrease of mean telomere length in all cancer subtypes compared with reference systems. Our results support the view that telomere attrition is an early event in tumorigenesis. TMM gets activated in all tumors studied due to concerted overexpression of a large fraction of genes with direct relation to telomere function, where only a very small fraction of them showed recurrent mutations. TEL-related transcriptional state was dominating in all CRC subtypes, showing, however, subtype-specific activation patterns; while contribution of the ALT-TMM was slightly more prominent in the hypermutated MSI s-CRC and LS-CRC. TEL-TMM is mainly activated by over-expression of DKC1 and/or TERT genes and their interaction partners, where DKC1 is more prominent in MSS than in MSI s-CRC and can serve as a transcriptomic marker of TMM activity. Conclusions: Our results suggest that transcriptional patterns are indicative for TMM pathway activation with subtle differences between TEL and ALT mechanisms in a CRC subtype-specific fashion. Sequencing data potentially provide a suited measure to study alterations of telomere length and of underlying transcriptional regulation. Further studies are needed to improve this method.

Authors: L. Nersisyan, L. Hopp, H. Loeffler-Wirth, J. Galle, M. Loeffler, A. Arakelyan, H. Binder

Date Published: 22nd Nov 2019

Publication Type: Not specified

Human Diseases: cancer

Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness.
LIFE Adult

Abstract (Expand)

PURPOSE: To investigate the role of sex on retinal nerve fiber layer (RNFL) thickness at 768 circumpapillary locations based on OCT findings. DESIGN: Population-based cross-sectional study. PARTICIPANTS: … We investigated 5646 eyes of 5646 healthy participants from the Leipzig Research Centre for Civilization Diseases (LIFE)-Adult Study of a predominantly white population. METHODS: All participants underwent standardized systemic assessments and ocular imaging. Circumpapillary RNFL (cRNFL) thickness was measured at 768 points equidistant from the optic nerve head using spectral-domain OCT (Spectralis; Heidelberg Engineering, Heidelberg, Germany). To control ocular magnification effects, the true scanning radius was estimated by scanning focus. Student t test was used to evaluate sex differences in cRNFL thickness globally and at each of the 768 locations. Multivariable linear regression and analysis of variance were used to evaluate individual contributions of various factors to cRNFL thickness variance. MAIN OUTCOME MEASURES: Difference in cRNFL thickness between males and females. RESULTS: Our population consisted of 54.8% females. The global cRNFL thickness was 1 mum thicker in females (P < 0.001). However, detailed analysis at each of the 768 locations revealed substantial location specificity of the sex effects, with RNFL thickness difference ranging from -9.98 to +8.00 mum. Females showed significantly thicker RNFLs in the temporal, superotemporal, nasal, inferonasal, and inferotemporal regions (43.6% of 768 locations), whereas males showed significantly thicker RNFLs in the superior region (13.2%). The results were similar after adjusting for age, body height, and scanning radius. The superotemporal and inferotemporal RNFL peaks shifted temporally in females by 2.4 degrees and 1.9 degrees , respectively. On regions with significant sex effects, sex explained more RNFL thickness variance than age, whereas the major peak locations and interpeak angle explained most of the RNFL thickness variance unexplained by sex. CONCLUSIONS: Substantial sex effects on cRNFL thickness were found at 56.8% of all 768 circumpapillary locations, with specific patterns for different sectors. Over large regions, sex was at least as important in explaining the cRNFL thickness variance as was age, which is well established to have a substantial impact on cRNFL thickness. Including sex in the cRNFL thickness norm could therefore improve glaucoma diagnosis and monitoring.

Authors: D. Li, F. G. Rauscher, E. Y. Choi, M. Wang, N. Baniasadi, K. Wirkner, T. Kirsten, J. Thiery, C. Engel, M. Loeffler, T. Elze

Date Published: 17th Nov 2019

Publication Type: Journal article

Association of Genomic Domains in BRCA1 and BRCA2 with Prostate Cancer Risk and Aggressiveness
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

Pathogenic sequence variants (PSV) in BRCA1 or BRCA2 (BRCA1/2) are associated with increased risk and severity of prostate cancer (PCa). We evaluated whether PSVs in BRCA1/2 were associated with risk … of overall PCa or high grade (Gleason 8+) PCa using an international sample of 65 BRCA1 and 171 BRCA2 male PSV carriers with PCa, and 3,388 BRCA1 and 2,880 BRCA2 male PSV carriers without PCa. PSVs in the 3’ region of BRCA2 (c.7914+) were significantly associated with elevated risk of PCa compared with reference bin c.1001-c.7913 (HR=1.78, 95%CI: 1.25-2.52, p=0.001), as well as elevated risk of Gleason 8+ PCa (HR=3.11, 95%CI: 1.63-5.95, p=0.001). c.756-c.1000 was also associated with elevated PCa risk (HR=2.83, 95%CI: 1.71-4.68, p=0.00004) and elevated risk of Gleason 8+ PCa (HR=4.95, 95%CI: 2.12-11.54, p=0.0002). No genotype-phenotype associations were detected for PSVs in BRCA1. These results demonstrate that specific BRCA2 PSVs may be associated with elevated risk of developing aggressive PCa.

Authors: Vivek L. Patel, Evan L. Busch, Tara M. Friebel, Angel Cronin, Goska Leslie, Lesley McGuffog, Julian Adlard, Simona Agata, Bjarni A. Agnarsson, Munaza Ahmed, Kristiina Aittomäki, Elisa Alducci, Irene L. Andrulis, Adalgeir Arason, Norbert Arnold, Grazia Artioli, Brita Arver, Bernd Auber, Jacopo Azzollini, Judith Balmaña, Rosa B. Barkardottir, Daniel R. Barnes, Alicia Barroso, Daniel Barrowdale, Muriel Belotti, Javier Benitez, Brigitte Bertelsen, Marinus J. Blok, Istvan Bodrogi, Valérie Bonadona, Bernardo Bonanni, Davide Bondavalli, Susanne E. Boonen, Julika Borde, Ake Borg, Angela R. Bradbury, Angela Brady, Carole Brewer, Joan Brunet, Bruno Buecher, Saundra S. Buys, Santiago Cabezas-Camarero, Trinidad Caldés, Almuth Caliebe, Maria A. Caligo, Mariarosaria Calvello, Ian G. Campbell, Ileana Carnevali, Estela Carrasco, Tsun L. Chan, Annie T. W. Chu, Wendy K. Chung, Kathleen B. M. Claes, Gemo Study Collaborators, Embrace Collaborators, Jackie Cook, Laura Cortesi, Fergus J. Couch, Mary B. Daly, Giuseppe Damante, Esther Darder, Rosemarie Davidson, Miguel de La Hoya, Lara Della Puppa, Joe Dennis, Orland Díez, Yuan Chun Ding, Nina Ditsch, Susan M. Domchek, Alan Donaldson, Bernd Dworniczak, Douglas F. Easton, Diana M. Eccles, Rosalind A. Eeles, Hans Ehrencrona, Bent Ejlertsen, Christoph Engel, D. Gareth Evans, Laurence Faivre, Ulrike Faust, Lídia Feliubadaló, Lenka Foretova, Florentia Fostira, George Fountzilas, Debra Frost, Vanesa García-Barberán, Pilar Garre, Marion Gauthier-Villars, Lajos Géczi, Andrea Gehrig, Anne-Marie Gerdes, Paul Gesta, Giuseppe Giannini, Gord Glendon, Andrew K. Godwin, David E. Goldgar, Mark H. Greene, Angelica M. Gutierrez-Barrera, Eric Hahnen, Ute Hamann, Jan Hauke, Natalie Herold, Frans B. L. Hogervorst, Ellen Honisch, John L. Hopper, Peter J. Hulick, Kconfab Investigators, Hebon Investigators, Louise Izatt, Agnes Jager, Paul James, Ramunas Janavicius, Uffe Birk Jensen, Thomas Dyrso Jensen, Oskar Th Johannsson, Esther M. John, Vijai Joseph, Eunyoung Kang, Karin Kast, Johanna I. Kiiski, Sung-Won Kim, Zisun Kim, Kwang-Pil Ko, Irene Konstantopoulou, Gero Kramer, Lotte Krogh, Torben A. Kruse, Ava Kwong, Mirjam Larsen, Christine Lasset, Charlotte Lautrup, Conxi Lázaro, Jihyoun Lee, Jong Won Lee, Min Hyuk Lee, Johannes Lemke, Fabienne Lesueur, Annelie Liljegren, Annika Lindblom, Patricia Llovet, Adria Lopez-Fernández, Irene Lopez-Perolio, Victor Lorca, Jennifer T. Loud, Edmond S. K. Ma, Phuong L. Mai, Siranoush Manoukian, Veronique Mari, Lynn Martin, Laura Matricardi, Noura Mebirouk, Veronica Medici, Hanne E. J. Meijers-Heijboer, Alfons Meindl, Arjen R. Mensenkamp, Clare Miller, Denise Molina Gomes, Marco Montagna, Thea M. Mooij, Lidia Moserle, Emmanuelle Mouret-Fourme, Anna Marie Mulligan, Katherine L. Nathanson, Marie Navratilova, Heli Nevanlinna, Dieter Niederacher, Finn C. Cilius Nielsen, Liene Nikitina-Zake, Kenneth Offit, Edith Olah, Olufunmilayo I. Olopade, Kai-Ren Ong, Ana Osorio, Claus-Eric Ott, Domenico Palli, Sue K. Park, Michael T. Parsons, Inge Sokilde Pedersen, Bernard Peissel, Ana Peixoto, Pedro Pérez-Segura, Paolo Peterlongo, Annabeth Høgh Petersen, Mary E. Porteous, Miguel Angel Pujana, Paolo Radice, Juliane Ramser, Johanna Rantala, Muhammad U. Rashid, Kerstin Rhiem, Piera Rizzolo, Mark E. Robson, Matti A. Rookus, Caroline Maria Rossing, Kathryn J. Ruddy, Catarina Santos, Claire Saule, Rosa Scarpitta, Rita K. Schmutzler, Hélène Schuster, Leigha Senter, Caroline M. Seynaeve, Payal D. Shah, Priyanka Sharma, Vivian Y. Shin, Valentina Silvestri, Jacques Simard, Christian F. Singer, Anne-Bine Skytte, Katie Snape, Angela R. Solano, Penny Soucy, Melissa C. Southey, Amanda B. Spurdle, Linda Steele, Doris Steinemann, Dominique Stoppa-Lyonnet, Agostina Stradella, Lone Sunde, Christian Sutter, Yen Y. Tan, Manuel R. Teixeira, Soo Hwang Teo, Mads Thomassen, Maria Grazia Tibiletti, Marc Tischkowitz, Silvia Tognazzo, Amanda E. Toland, Stefania Tommasi, Diana Torres, Angela Toss, Alison H. Trainer, Nadine Tung, Christi J. van Asperen, Frederieke H. van der Baan, Lizet E. van der Kolk, Rob B. van der Luijt, Liselotte P. van Hest, Liliana Varesco, Raymonda Varon-Mateeva, Alessandra Viel, Jeroen Vierstraete, Roberta Villa, Anna von Wachenfeldt, Philipp Wagner, Shan Wang-Gohrke, Barbara Wappenschmidt, Jeffrey N. Weitzel, Greet Wieme, Siddhartha Yadav, Drakoulis Yannoukakos, Sook-Yee Yoon, Cristina Zanzottera, Kristin K. Zorn, Anthony V. D’Amico, Matthew L. Freedman, Mark M. Pomerantz, Georgia Chenevix-Trench, Antonis C. Antoniou, Susan L. Neuhausen, Laura Ottini, Henriette Roed Nielsen, Timothy R. Rebbeck

Date Published: 13th Nov 2019

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Der Leipzig Health Atlas
LHA - Leipzig Health Atlas

Abstract (Expand)

Die Notwendigkeit des Managements von Forschungsdaten ist von der Forschungscommunity erkannt – Sponsoren, Gesetzgeber, Verlage erwarten und fördern die Einhaltung der guten wissenschaftlichen Praxis, … was nicht nur die Archivierung umfasst, sondern auch die Verfügbarkeit von Forschungsdaten- und ergebnissen im Sinne der FAIR-Prinzipien. Der Leipzig Health Atlas (LHA) ist ein Projekt zur Präsentation und zum Austausch eines breiten Spektrums von Publikationen, (bio) medizinischen Daten (z.B. klinisch, epidemiologisch, molekular), Modellen und Tools z.B. zur Risikoberechnung in der Gesundheitsforschung. Die Verbundpartner decken hierbei einen breiten Bereich wissenschaftlicher Disziplinen ab, beginnend von medizinischer Systembiologie über klinische und epidemiologische Forschung bis zu ontologischer und dynamischer Modellierung. Derzeit sind 18 Forschungskonsortien beteiligt (u.a. zu den Domänen Lymphome, Gliome, Sepsis, Erblicher Darm- und Brustkrebs), die Daten aus klinischen Studien, Patientenkohorten, epidemiologischen Kohorten, teilweise mit umfangreichen molekularen und genetischen Profilen, sammeln. Die Modellierung umfasst algorithmische Phänotypklassifizierung, Risikovorhersage und Krankheitsdynamik. Wir konnten in einer ersten Entwicklungsphase zeigen, dass unsere webbasierte Plattform geeignet ist, um (1) Methoden zur Verfügung zu stellen, um individuelle Patientendaten aus Publikationen für eine Weiternutzung zugänglich zu machen, (2) algorithmische Werkzeuge zur Phänotypisierung und Risikoprofilerstellung zu präsentieren, (3) Werkzeuge zur Durchführung dynamischer Krankheits- und Therapiemodelle interaktiv verfügbar zu machen und (4) strukturierte Metadaten zu quantitativen und qualitativen Merkmalen bereit zu stellen. Die semantische Datenintegration liefert hierzu die Technologien (Ontologien und Datamining Werkzeuge) für die (semantische) Datenintegration und Wissensanreicherung. Darüber hinaus stellt sie Werkzeuge zur Verknüpfung eigener Daten, Analyseergebnisse, öffentlich zugänglicher Daten- und Metadaten-Repositorien sowie zur Verdichtung komplexer Daten zur Verfügung. Eine Arbeitsgruppe zur Applikationsentwicklung und –validierung entwickelt innovative paradigmatische Anwendungen für (1) die klinische Entscheidungsfindung für Krebsstudien, die genetische Beratung, für Risikovorhersagemodelle sowie Gewebe- und Krankheitsmodelle und (2) Anwendungen (sog. Apps), die sich auf die Charakterisierung neuer Phänotypen (z.B. ‚omics‘-Merkmale, Körpertypen, Referenzwerte) aus epidemiologischen Studien konzentrieren. Diese Anwendungen werden gemeinsam mit klinischen Experten, Genetikern, Systembiologen, Biometrikern und Bioinformatikern spezifiziert. Der LHA stellt Integrationstechnologie bereit und implementiert die Anwendungen für die User Communities unter Verwendung verschiedener Präsentationswerkzeuge bzw. Technologien (z.B. R-Shiny, i2b2, Kubernetes, SEEK). Dazu ist es erforderlich, die Daten und Metadaten vor dem Hochladen zu kuratieren, Erlaubnisse der Datenbesitzer einzuholen, die erforderlichen Datenschutzkriterien zu berücksichtigen und semantische Annotationen zu überprüfen. Zudem werden die zugelieferten Modellalgorithmen in einer qualitätsgesicherten Weise aufbereitet und, soweit anwendbar, online interaktiv zur Verfügung gestellt. Der LHA richtet sich insbesondere an die Zielgruppen Kliniker, Epidemiologen, Molekulargenetiker, Humangenetiker, Pathologen, Biostatistiker und Modellierer ist aber unter www.healthatlas.de öffentlich zugänglich – aus rechtlichen Gründen erfordert der Zugriff auf bestimmte Applikationen und Datensätze zusätzliche Autorisierung. Das Projekt wird über das BMBF Programm i:DSem (Integrative Datensemantik für die Systemmedizin, Förderkennzeichen 031L0026) gefördert.

Authors: F. A. Meineke, Sebastian Stäubert, Matthias Löbe, C. Beger, René Hänsel, A. Uciteli, H. Binder, T. Kirsten, M. Scholz, H. Herre, C. Engel, Markus Löffler

Date Published: 19th Sep 2019

Publication Type: Misc

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated … in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known non-pathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification. This article is protected by copyright. All rights reserved.

Authors: Michael T. Parsons, Emma Tudini, Hongyan Li, Eric Hahnen, Barbara Wappenschmidt, Lidia Feliubadaló, Cora M. Aalfs, Simona Agata, Kristiina Aittomäki, Elisa Alducci, María Concepción Alonso-Cerezo, Norbert Arnold, Bernd Auber, Rachel Austin, Jacopo Azzollini, Judith Balmaña, Elena Barbieri, Claus R. Bartram, Ana Blanco, Britta Blümcke, Sandra Bonache, Bernardo Bonanni, Åke Borg, Beatrice Bortesi, Joan Brunet, Carla Bruzzone, Karolin Bucksch, Giulia Cagnoli, Trinidad Caldés, Almuth Caliebe, Maria A. Caligo, Mariarosaria Calvello, Gabriele L. Capone, Sandrine M. Caputo, Ileana Carnevali, Estela Carrasco, Virginie Caux-Moncoutier, Pietro Cavalli, Giulia Cini, Edward M. Clarke, Paola Concolino, Elisa J. Cops, Laura Cortesi, Fergus J. Couch, Esther Darder, Miguel de La Hoya, Michael Dean, Irmgard Debatin, Jesús Del Valle, Capucine Delnatte, Nicolas Derive, Orland Diez, Nina Ditsch, Susan M. Domchek, Véronique Dutrannoy, Diana M. Eccles, Hans Ehrencrona, Ute Enders, D. Gareth Evans, Ulrike Faust, Ute Felbor, Irene Feroce, Miriam Fine, Henrique C. R. Galvao, Gaetana Gambino, Andrea Gehrig, Francesca Gensini, Anne-Marie Gerdes, Aldo Germani, Jutta Giesecke, Viviana Gismondi, Carolina Gómez, Encarna B. Gómez Garcia, Sara González, Elia Grau, Sabine Grill, Eva Gross, Aliana Guerrieri-Gonzaga, Marine Guillaud-Bataille, Sara Gutiérrez-Enríquez, Thomas Haaf, Karl Hackmann, Thomas v. O. Hansen, Marion Harris, Jan Hauke, Tilman Heinrich, Heide Hellebrand, Karen N. Herold, Ellen Honisch, Judit Horvath, Claude Houdayer, Verena Hübbel, Silvia Iglesias, Angel Izquierdo, Paul A. James, Linda A. M. Janssen, Udo Jeschke, Silke Kaulfuß, Katharina Keupp, Marion Kiechle, Alexandra Kölbl, Sophie Krieger, Torben A. Kruse, Anders Kvist, Fiona Lalloo, Mirjam Larsen, Vanessa L. Lattimore, Charlotte Lautrup, Susanne Ledig, Elena Leinert, Alexandra L. Lewis, Joanna Lim, Markus Loeffler, Adrià López-Fernández, Emanuela Lucci-Cordisco, Nicolai Maass, Siranoush Manoukian, Monica Marabelli, Laura Matricardi, Alfons Meindl, Rodrigo D. Michelli, Setareh Moghadasi, Alejandro Moles-Fernández, Marco Montagna, Gemma Montalban, Alvaro N. Monteiro, Eva Montes, Luigi Mori, Lidia Moserle, Clemens R. Müller, Christoph Mundhenke, Nadia Naldi, Katherine L. Nathanson, Matilde Navarro, Heli Nevanlinna, Cassandra B. Nichols, Dieter Niederacher, Henriette R. Nielsen, Kai-Ren Ong, Nicholas Pachter, Edenir I. Palmero, Laura Papi, Inge Sokilde Pedersen, Bernard Peissel, Pedro Pérez-Segura, Katharina Pfeifer, Marta Pineda, Esther Pohl-Rescigno, Nicola K. Poplawski, Berardino Porfirio, Anne S. Quante, Juliane Ramser, Rui M. Reis, Françoise Revillion, Kerstin Rhiem, Barbara Riboli, Julia Ritter, Daniela Rivera, Paula Rofes, Andreas Rump, Monica Salinas, Ana María Sánchez de Abajo, Gunnar Schmidt, Ulrike Schoenwiese, Jochen Seggewiß, Ares Solanes, Doris Steinemann, Mathias Stiller, Dominique Stoppa-Lyonnet, Kelly J. Sullivan, Rachel Susman, Christian Sutter, Sean V. Tavtigian, Soo H. Teo, Alex Teulé, Mads Thomassen, Maria Grazia Tibiletti, Silvia Tognazzo, Amanda E. Toland, Eva Tornero, Therese Törngren, Sara Torres-Esquius, Angela Toss, Alison H. Trainer, Christi J. van Asperen, Marion T. van Mackelenbergh, Liliana Varesco, Gardenia Vargas-Parra, Raymonda Varon, Ana Vega, Ángela Velasco, Anne-Sophie Vesper, Alessandra Viel, Maaike P. G. Vreeswijk, Sebastian A. Wagner, Anke Waha, Logan C. Walker, Rhiannon J. Walters, Shan Wang-Gohrke, Bernhard H. F. Weber, Wilko Weichert, Kerstin Wieland, Lisa Wiesmüller, Isabell Witzel, Achim Wöckel, Emma R. Woodward, Silke Zachariae, Valentina Zampiga, Christine Zeder-Göß, Conxi Lázaro, Arcangela de Nicolo, Paolo Radice, Christoph Engel, Rita K. Schmutzler, David E. Goldgar, Amanda B. Spurdle

Date Published: 1st Sep 2019

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Design and concept of the SMITH phenotyping pipeline
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Phenotyping means the determination of clinical relevant phenotypes, e.g. by classification or calculation based on EHR data. Within the German Medical Informatics Initiative, the SMITH consortium is … working on the implementation of a phenotyping pipeline. to extract, structure and normalize information from the EHR data of the hospital information systems of the participating sites; to automatically apply complex algorithms and models and to enrich the data within the research data warehouses of the distributed data integration centers with the computed results. Here we present the overall picture and essential building blocks and workflows of this concept.

Authors: Frank A Meineke, Sebastian Stäubert, Matthias Löbe, Alexandr Uciteli, Markus Löffler

Date Published: 1st Sep 2019

Publication Type: Journal article

Towards Structured Data Quality Assessment in the German Medical Informatics Initiative: Initial Approach in the MII Demonstrator Study.
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

The Demonstrator study aims to analyse comorbidities and rare diseases among patients from German university hospitals within the German Medical Informatics Initiative. This work aimed to design and … determine the feasibility of a model to assess the quality of the claims data used in the study. Several data quality issues were identified affecting small amounts of cases in one of the participating sites. As a next step an extension to all participating sites is planned.

Authors: G. Kamdje-Wabo, T. Gradinger, M. Lobe, R. Lodahl, S. A. Seuchter, U. Sax, T. Ganslandt

Date Published: 21st Aug 2019

Publication Type: Journal article

Navigate

Health Atlas - Local Data Hub/Leipzig

The Health Atlas - Local Data Hub/Leipzig is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research fields.

Registered Repository

re3data.org Badge
Powered by
 (v.1.13.0-master)
Health Atlas | Funding and Programmes | Credits | Terms & Conditions | Privacy Policy | Imprint
Copyright © 2008 - 2021 The University of Manchester and HITS gGmbH
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig

By continuing to use this site you agree to the use of cookies