Filter and export

Publications

959 Publications visible to you, out of a total of 959
Circulating oxytocin is genetically determined and associated with obesity and impaired glucose tolerance
Genetical Statistics and Systems Biology

Abstract (Expand)

CONTEXT Despite the emerging evidence on the role of oxytocin (OXT) in metabolic diseases, there is a lack of well powered studies addressing the relationship of circulating OXT with obesity and diabetes. …. OBJECTIVES AND DESIGN Here, we measured OXT in a study cohort (n=721; 396 women, 325 men; mean age\pmSD - 47.7\pm15.2 years) with sub-phenotypes related to obesity including anthropometric traits such as body mass index (BMI; mean\pmSD - 47.7\pm15.2 kg/m2), waist-to-hip-ratio (WHR; 0.88\pm0.09), blood parameters (glucose - 5.32\pm0.50 mmol/l, insulin - 5.3\pm3.3 µU/ml, lipids) and oral glucose tolerance test (OGTT) to clarify the association with OXT. We also tested in a genome-wide association study (GWAS) whether the inter-individual variation in OXT serum levels might be explained by genetic variation. RESULTS The OXT concentration was increased in subjects with elevated BMI and positively correlated with WHR, waist circumference and triglyceride levels. The OXT concentration in subjects with BMI\textless25 kg/m2 was significantly lower (n=256; 78.6 pg/ml) than in subjects with a BMI between 25-30 kg/m2 (n=314; 98.5 pg/ml, p=6x10-6) and with BMI\textgreater30 kg/m2 (n=137; 106.4 pg/ml, p=8x10-6). OXT levels were also positively correlated with plasma glucose and insulin and were elevated in subjects with impaired glucose tolerance (p=4.6x10-3). Heritability of OXT was estimated to 12.8%. In a GWAS, two hits in linkage disequilibrium close (19kb) to the OXT reached genome-wide significant association (top-hit rs12625893, p=3.1x10-8, explained variance 3%). CONCLUSIONS Our data show that OXT is genetically affected by a variant in OXT and is associated with obesity and impaired glucose tolerance.

Authors: Mark Florian Joachim Weingarten, Markus Scholz, Tobias Wohland, Katrin Horn, Michael Stumvoll, Peter Kovacs, Anke Tönjes

Date Published: 1st Nov 2019

Publication Type: Journal article

Common variants in glyoxalase I do not increase chronic pancreatitis risk
Genetical Statistics and Systems Biology

Abstract (Expand)

INTRODUCTION Chronic pancreatitis (CP) may be caused by oxidative stress. An important source of reactive oxygen species (ROS) is the methylglyoxal-derived formation of advanced glycation endproducts …s (AGE). Methylglyoxal is detoxified by Glyoxalase I (GLO1). A reduction in GLO1 activity results in increased ROS. Single nucleotide polymorphisms (SNPs) of GLO1 have been linked to various inflammatory diseases. Here, we analyzed whether common GLO1 variants are associated with alcoholic (ACP) and non-alcoholic CP (NACP). METHODS Using melting curve analysis, we genotyped a screening cohort of 223 ACP, 218 NACP patients, and 328 controls for 11 tagging SNPs defined by the SNPinfo LD TAG SNP Selection tool and the functionally relevant variant rs4746. For selected variants the cohorts were extended to up to 1,441 patient samples. RESULTS In the ACP cohort, comparison of genotypes for rs1937780 between patients and controls displayed an ambiguous result in the screening cohort (p = 0.08). However, in the extended cohort of 1,441 patients no statistically significant association was found for the comparison of genotypes (p = 0.11), nor in logistic regression analysis (p = 0.214, OR 1.072, 95% CI 0.961-1.196). In the NACP screening cohort SNPs rs937662, rs1699012, and rs4746 displayed an ambiguous result when patients were compared to controls in the recessive or dominant model (p = 0.08, 0.08, and 0.07, respectively). Again, these associations were not confirmed in the extended cohorts (rs937662, dominant model: p = 0.07, logistic regression: p = 0.07, OR 1.207, 95% CI 0.985-1.480) or in the replication cohorts for rs4746 (Germany, p = 0.42, OR 1.080, 95% CI 0.673-1.124; France, p = 0.19, OR 0.90, 95% CI 0.76-1.06; China, p = 0.24, OR 1.18, 95% CI 0.90-1.54) and rs1699012 (Germany, Munich; p = 0.279, OR 0.903, 95% CI 0.750-1.087). CONCLUSIONS Common GLO1 variants do not increase chronic pancreatitis risk.

Authors: Tom Kaune, Marcus Hollenbach, Bettina Keil, Jian-Min Chen, Emmanuelle Masson, Carla Becker, Marko Damm, Claudia Ruffert, Robert Grützmann, Albrecht Hoffmeister, Rene H. M. Te Morsche, Giulia Martina Cavestro, Raffaella Alessia Zuppardo, Adrian Saftoiu, Ewa Malecka-Panas, Stanislaw Głuszek, Peter Bugert, Markus M. Lerch, Frank Ulrich Weiss, Wen-Bin Zou, Zhuan Liao, Peter Hegyi, Joost Ph Drenth, Jan Riedel, Claude Férec, Markus Scholz, Holger Kirsten, Andrea Tóth, Maren Ewers, Heiko Witt, Heidi Griesmann, Patrick Michl, Jonas Rosendahl

Date Published: 29th Oct 2019

Publication Type: Journal article

Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels
Genetical Statistics and Systems Biology

Abstract (Expand)

Elevated serum urate levels cause gout and correlate with cardiometabolic diseases via poorly understood mechanisms. We performed a trans-ancestry genome-wide association study of serum urate in 457,690 … individuals, identifying 183 loci (147 previously unknown) that improve the prediction of gout in an independent cohort of 334,880 individuals. Serum urate showed significant genetic correlations with many cardiometabolic traits, with genetic causality analyses supporting a substantial role for pleiotropy. Enrichment analysis, fine-mapping of urate-associated loci and colocalization with gene expression in 47 tissues implicated the kidney and liver as the main target organs and prioritized potentially causal genes and variants, including the transcriptional master regulators in the liver and kidney, HNF1A and HNF4A. Experimental validation showed that HNF4A transactivated the promoter of ABCG2, encoding a major urate transporter, in kidney cells, and that HNF4A p.Thr139Ile is a functional variant. Transcriptional coregulation within and across organs may be a general mechanism underlying the observed pleiotropy between urate and cardiometabolic traits.

Authors: Adrienne Tin, Jonathan Marten, Victoria L. Halperin Kuhns, Yong Li, Matthias Wuttke, Holger Kirsten, Karsten B. Sieber, Chengxiang Qiu, Mathias Gorski, Zhi Yu, Ayush Giri, Gardar Sveinbjornsson, Man Li, Audrey Y. Chu, Anselm Hoppmann, Luke J. O’Connor, Bram Prins, Teresa Nutile, Damia Noce, Masato Akiyama, Massimiliano Cocca, Sahar Ghasemi, Peter J. van der Most, Katrin Horn, Yizhe Xu, Christian Fuchsberger, Sanaz Sedaghat, Saima Afaq, Najaf Amin, Johan Ärnlöv, Stephan J. L. Bakker, Nisha Bansal, Daniela Baptista, Sven Bergmann, Mary L. Biggs, Ginevra Biino, Eric Boerwinkle, Erwin P. Bottinger, Thibaud S. Boutin, Marco Brumat, Ralph Burkhardt, Eric Campana, Archie Campbell, Harry Campbell, Robert J. Carroll, Eulalia Catamo, John C. Chambers, Marina Ciullo, Maria Pina Concas, Josef Coresh, Tanguy Corre, Daniele Cusi, Sala Cinzia Felicita, Martin H. de Borst, Alessandro de Grandi, Renée de Mutsert, Aiko P. J. de Vries, Graciela Delgado, Ayşe Demirkan, Olivier Devuyst, Katalin Dittrich, Kai-Uwe Eckardt, Georg Ehret, Karlhans Endlich, Michele K. Evans, Ron T. Gansevoort, Paolo Gasparini, Vilmantas Giedraitis, Christian Gieger, Giorgia Girotto, Martin Gögele, Scott D. Gordon, Daniel F. Gudbjartsson, Vilmundur Gudnason, Toomas Haller, Pavel Hamet, Tamara B. Harris, Caroline Hayward, Andrew A. Hicks, Edith Hofer, Hilma Holm, Wei Huang, Nina Hutri-Kähönen, Shih-Jen Hwang, M. Arfan Ikram, Raychel M. Lewis, Erik Ingelsson, Johanna Jakobsdottir, Ingileif Jonsdottir, Helgi Jonsson, Peter K. Joshi, Navya Shilpa Josyula, Bettina Jung, Mika Kähönen, Yoichiro Kamatani, Masahiro Kanai, Shona M. Kerr, Wieland Kiess, Marcus E. Kleber, Wolfgang Koenig, Jaspal S. Kooner, Antje Körner, Peter Kovacs, Bernhard K. Krämer, Florian Kronenberg, Michiaki Kubo, Brigitte Kühnel, Martina La Bianca, Leslie A. Lange, Benjamin Lehne, Terho Lehtimäki, Jun Liu, Markus Loeffler, Ruth J. F. Loos, Leo-Pekka Lyytikäinen, Reedik Magi, Anubha Mahajan, Nicholas G. Martin, Winfried März, Deborah Mascalzoni, Koichi Matsuda, Christa Meisinger, Thomas Meitinger, Andres Metspalu, Yuri Milaneschi, Christopher J. O’Donnell, Otis D. Wilson, J. Michael Gaziano, Pashupati P. Mishra, Karen L. Mohlke, Nina Mononen, Grant W. Montgomery, Dennis O. Mook-Kanamori, Martina Müller-Nurasyid, Girish N. Nadkarni, Mike A. Nalls, Matthias Nauck, Kjell Nikus, Boting Ning, Ilja M. Nolte, Raymond Noordam, Jeffrey R. O’Connell, Isleifur Olafsson, Sandosh Padmanabhan, Brenda W. J. H. Penninx, Thomas Perls, Annette Peters, Mario Pirastu, Nicola Pirastu, Giorgio Pistis, Ozren Polasek, Belen Ponte, David J. Porteous, Tanja Poulain, Michael H. Preuss, Ton J. Rabelink, Laura M. Raffield, Olli T. Raitakari, Rainer Rettig, Myriam Rheinberger, Kenneth M. Rice, Federica Rizzi, Antonietta Robino, Igor Rudan, Alena Krajcoviechova, Renata Cifkova, Rico Rueedi, Daniela Ruggiero, Kathleen A. Ryan, Yasaman Saba, Erika Salvi, Helena Schmidt, Reinhold Schmidt, Christian M. Shaffer, Albert V. Smith, Blair H. Smith, Cassandra N. Spracklen, Konstantin Strauch, Michael Stumvoll, Patrick Sulem, Salman M. Tajuddin, Andrej Teren, Joachim Thiery, Chris H. L. Thio, Unnur Thorsteinsdottir, Daniela Toniolo, Anke Tönjes, Johanne Tremblay, André G. Uitterlinden, Simona Vaccargiu, Pim van der Harst, Cornelia M. van Duijn, Niek Verweij, Uwe Völker, Peter Vollenweider, Gerard Waeber, Melanie Waldenberger, John B. Whitfield, Sarah H. Wild, James F. Wilson, Qiong Yang, Weihua Zhang, Alan B. Zonderman, Murielle Bochud, James G. Wilson, Sarah A. Pendergrass, Kevin Ho, Afshin Parsa, Peter P. Pramstaller, Bruce M. Psaty, Carsten A. Böger, Harold Snieder, Adam S. Butterworth, Yukinori Okada, Todd L. Edwards, Kari Stefansson, Katalin Susztak, Markus Scholz, Iris M. Heid, Adriana M. Hung, Alexander Teumer, Cristian Pattaro, Owen M. Woodward, Veronique Vitart, Anna Köttgen

Date Published: 1st Oct 2019

Publication Type: Journal article

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

Effectiveness of different central venous catheter fixation suture techniques: An in vitro crossover study
Genetical Statistics and Systems Biology

Abstract (Expand)

PURPOSE Proper fixation of central venous catheters (CVCs) is an integral part of safety to avoid dislodgement and malfunction. However, the effectiveness of different CVC securement sutures is unknown. …. METHODS Analysis of maximum dislodgement forces for CVCs from three different manufacturers using four different suture techniques in an in vitro tensile loading experiment: 1. \textquotedblclamp only\textquotedbl, 2. \textquotedblclamp and compression suture\textquotedbl, 3. \textquotedblfinger trap\textquotedbl and 4. \textquotedblcomplete\textquotedbl, i.e., \textquotedblclamp + compression suture + finger trap\textquotedbl. Twenty-five tests were performed for each of the three CVC models and four securement suture techniques (n = 300 test runs). RESULTS The primary cause of catheter dislodgement was sliding through the clamp in techniques 1 and 2. In contrast, rupture of the suture was the predominant cause for dislodgement in techniques 2 and 3. Median (IQR 25-75%) dislodgement forces were 26.0 (16.6) N in technique 1, 26.5 (18.8) N in technique 2, 76.7 (18.7) N in technique 3, and 84.8 (11.8) N in technique 4. Post-hoc analysis demonstrated significant differences (P < .001) between all pairwise combinations of techniques except technique 1 vs. 2 (P = .98). CONCLUSIONS \textquotedblFinger trap\textquotedbl fixation at the segmentation site considerably increases forces required for dislodgement compared to clamp-based approaches.

Authors: Manuel Florian Struck, Lars Friedrich, Stefan Schleifenbaum, Holger Kirsten, Wolfram Schummer, Bernd E. Winkler

Date Published: 12th Sep 2019

Publication Type: Journal article

Rückverfolgbarkeit für künstliche Intelligenz: Umsetzung einer Traceability-Strategie bei der modellgetriebenen Entwicklung klinischer Entscheidungsunterstützungssysteme
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Einleitung: Systeme auf Basis von Algorithmen mit \glqqkünstlicher Intelligenz\grqq werden im Gesundheitswesen zunehmend praktisch eingesetzt. Durch die Medizininformatik-Initiative sollen zukünftig … Daten aus Krankenversorgung und Forschung besser zugänglich werden. In diesem Rahmen[zum vollständigen Text gelangen Sie über die oben angegebene URL]

Authors: Lo Phan-Vogtmann an , Henner M. Kruse, Alexander Helhorn, Andrew J. Heidel, Eric Thomas, Kutaiba Saleh, André Scherag, Danny Ammon

Date Published: 8th Sep 2019

Publication Type: InProceedings

Modeling a Graph Data Model for FHIR Resources
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Introduction: (Fast Healthcare Interoperability Resources) is a modern standard for communication and representation of clinical data, where each dataset is defined by a single resource, linked to other … resources [ref:1]. But FHIR\circledR does explicitely not define how to persist these resources[for full text, please go to the a.m. URL]

Authors: Henner M. Kruse, Alexander Helhorn, Lo Phan-Vogtmann an , Eric Thomas, Andrew J. Heidel, Kutaiba Saleh, André Scherag, Danny Ammon

Date Published: 6th Sep 2019

Publication Type: InProceedings

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