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Voxel-based analyses of magnetization transfer imaging of the brain in hepatic encephalopathy

World Journal of Gastroenterology 2009年第41期15卷 5157-5164页

作者： Falk R Miese Hans-Jrg Wittsack Gerald Kircheis arne holstein Christian Mathys Ulrich Mdder Mathias Cohnen Institute of Radiology University Hospital Düsseldorf MNR Clinic Moorenstrasse 5 Düsseldorf 40225 Germany Department of Internal Medicine Division of Gastroenterology Hepatology and Infectious Diseases University Hospital Düsseldorf Moorenstrasse 5 Düsseldorf 40225 Germany

AIM: To evaluate the spatial distribution of cerebral abnormalities in cirrhotic subjects with and without hepatic encephalopathy (HE) found with magnetization transfer imaging (MTI).METHODS: Nineteen cirrhotic patients graded from neurologically normal to HE grade 2 and 18 healthy control subjects underwent magnetic resonance imaging. They gave institutional-review-board-approved written consent. Magnetization transfer ratio (MTR) maps were generated from MTI. We tested for significant differences compared to the control group using statistical non-parametric mapping (SnPM) for a voxelbased ***: The MTR of grey and white matter was lower in subjects with more severe HE. Changes were found in patients with cirrhosis without neurological defi cits in the basal ganglia and bilateral white matter. The loss in magnetization transfer increased in severity and spatial extent in patients with overt HE. Patients with HE grade 2 showed an MTR decrease in white and grey matter: the maximum loss of magnetization transfer effect was located in the basal ganglia [SnPM (pseudo-)t = 17.98, P = 0.0001].CONCLUSION: The distribution of MTR changes in HE points to an early involvement of basal ganglia and white matter in HE.

关键词： Brain Hepatic encephalopathy Magnetic resonance imaging Uver cirrhosis Magnetization transfer imaging

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Killer on the road?—cells from pancreatic preneoplastic lesions disseminate through pancreatic ducts on their way to cancer

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Hepatobiliary Surgery and Nutrition 2019年第4期8卷 392-394页

作者： Heiner Schafer arne Traulsen Susanne Sebens Institute for Experimental Cancer Research Kiel University&University Hospital Schleswig-Holstein Campus KielKielGermany Max Planck Institute for Evolutionary Biology PlonGermany

Pancreatic ductal adenocarcinoma (PDAC) is ranked the fourth most common cause of cancer related deaths in western countries with a 5-year survival rate of less than 8% (1). It is estimated to be even the second most common cause by 2030 as there are no successful treatment options (2). Due to the lack of early and specific symptoms as well as non-invasive biomarkers, the majority of patients is diagnosed at an advanced and already metastasized disease stage, where palliative treatment remains the only option (3). Thus, in order to improve the dismal prognosis of PDAC patients, a much better understanding of PDAC evolution is urgently needed allowing earlier detection of the disease and providing novel therapeutic modalities. It is well appreciated that the most common precursor lesion of PDAC is the pancreatic intraepithelial neoplasia (PanIN) (4). According to the progression model (5,6) and supported by genetic studies, PanINs develop from low-grade to high-grade lesions finally leading to an invasive carcinoma. This progression is characterized and driven by the acquisition of genetic (and epigenetic) alterations. In fact, mutations in the oncogene kras, being one of the earliest genetic alterations, are present in 99% of even early low-grade PanINs (PanIN1) (5,6). In resected PDAC tissues, PanINs are often found in and around the tumor mass (7). Genetic analysis revealed that PanINs and adjacent carcinoma tissues share many common mutations albeit some mutations are apparently acquired not until the carcinoma stage (8,9). These data indicate that PDAC may;origin from neighboring PanINs. However, the biology and genetic relationship between PanINs and PDAC and thereby PDAC evolution is still poorly understood.

关键词： alterations Killer thereby

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Comparison of Cox Model Methods in A Low-dimensional Setting with Few Events

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Genomics, Proteomics & Bioinformatics 2016年第4期14卷 235-243页

作者： Francisco M. Ojeda Christian Miiller Daniela Bornigen David-Alexandre Tregouet arne Schillert Matthias Heinig Tanja Zeller Renate B. Schnabel Department of General and Interventional Cardiology University Heart Center Hamburg-Eppendorf 20246 Hamburg Germany German Center for Cardiovascular Research (DZHK) Hamburg |Kiel| Luebeck Germany Sorbonne Universites University Pierre et Marie Curie Paris 06 Institut National pour la Sante et la Recherche Medicale (INSERM) Unite Mixte de Recherche en Sante (UMR_S) 1166 F-75013 Paris France Institute for Cardiometaholism and Nutrition (ICAN) F-75013 Paris France Institut fur Medizinische Biometrie und Statistik Universitat zu Lubeck Universitatsklinikum Schleswig-Holstein Campus Lubeck 23562 Lubeck Germany Institute of Computational Biology German Research Center for Environmental Health Helmholtz Zentrum Munchen 85764 Neuherberg Germany

Prognostic models based on survival data frequently make use of the Cox proportional hazards model. Developing reliable Cox models with few events relative to the number of predictors can be challenging, even in low-dimensional datasets, with a much larger number of observations than variables. In such a setting we examined the performance of methods used to estimate a Cox model, including （i） full model using all available predictors and estimated by standard techniques, （ii） backward elimination （BE）, （iii） ridge regression, （iv） least absolute shrinkage and selection operator （lasso）, and （v） elastic net. Based on a prospective cohort of patients with manifest coronary artery disease （CAD）, we performed a simulation study to compare the predictive accuracy, calibration, and discrimination of these approaches, Candidate predictors for incident cardiovascular events we used included clinical variables, biomarkers, and a selection of genetic variants associated with CAD. The penalized methods, i.e., ridge, lasso, and elastic net, showed a comparable performance, in terms of predictive accuracy, calibration, and discrimination, and outperformed BE and the full model. Excessive shrinkage was observed in some cases for the penalized methods, mostly on the simulation scenarios having the lowest ratio of a number of events to the number of variables. We conclude that in similar settings, these three penalized methods can be used interchangeably. The full model and backward elimination are not recommended in rare event scenarios.

关键词： Proportional hazards regression Penalized regression Events per variable Coronary artery disease

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Key genes of the interleukin 6 signaling pathway are not associated with coronary artery disease in a large European population

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Open Journal of Genetics 2013年第1期3卷 67-78页

作者： Mark Luedde arne S.Schaefer Natalie Scheller Corinna Doege Hans-Joerg Hippe Michael Nothnagel Nils Haake Norbert Frey Stefan Schreiber Nour Eddine El-Mokhtari Department of Internal Medicine III:Cardiology and Angiology University of KielKielGermany Institute for Clinical Molecular Biology University of KielKielGermany Department of Pediatric Neurology University of KielKielGermany Institute of Medical Informatics and Statistics University of KielKielGermany Department of Cardiovascular Surgery University of KielKielGermany Department of Medicine Christian-Albrechts-Universitat KielKielGermany Imland Klinikum Rendsburg Christian-Albrechts-Universitat KielKielGermany

Background: Recent studies indicate a strong functional relevance of the canonical inflammatory interleukin 6 signaling pathway in coronary artery disease (CAD). A genetic association of this signaling pathway with CAD has not been shown yet. We aimed to assess novel single nucleotide polymorphisms (SNPs) from genes of the Interleukin 6 signaling pathway. Results: To identify novel SNPs that are relevant for CAD, we employed a large-scale population-based case-control association study of 2199 cases and 1715 controls and assessed 73 SNPs from 12 genes out of the IL-6 signaling pathway. Results were adjusted to the CAD-related risk factors diabetes, hypertension, Body Mass Index, smoking and sex by logistic regression analysis. In a primary explorative study, we identified 5 SNPs that were significantly associated with CAD (MAPK1_rs6928, MAPK1_rs9340, MAPK1_ rs11913721, MAPK14_rs7757672, JAK1_rs310236). After adjustment to CAD-risk factors, MAPK1_ rs6928 showed the strongest association with CAD (P 0.0217, Odds Ratio 1.36, Confidence Interval 1.05 - 1.77). To reproduce this result, we performed a replication study employing independent patient and control panels. In this study we could not approve the association of rs6928 with CAD. Conclusion: In conclusion, we did not detect significant associations of SNPs from the IL-6 signaling pathway with CAD. Our investigation demonstrates the importance of independent replication studies to verify results from candidate-gene association studies in the quest to discover the underlying pathomechanism of CAD.

关键词： Coronary Artery Disease Genetics Single Nucleotide Polymorphism Interleukin 6

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