Kroemer, Heyo Klaus

[["dc.bibliographiccitation.firstpage","1069"],["dc.bibliographiccitation.issue","16"],["dc.bibliographiccitation.journal","European Heart Journal"],["dc.bibliographiccitation.lastpage","1077"],["dc.bibliographiccitation.volume","35"],["dc.contributor.author","Meder, Benjamin"],["dc.contributor.author","Rühle, Frank"],["dc.contributor.author","Weis, Tanja"],["dc.contributor.author","Homuth, Georg"],["dc.contributor.author","Keller, Andreas"],["dc.contributor.author","Franke, Jennifer"],["dc.contributor.author","Peil, Barbara"],["dc.contributor.author","Bermejo, Justo Lorenzo"],["dc.contributor.author","Frese, Karen"],["dc.contributor.author","Huge, Andreas"],["dc.contributor.author","Witten, Anika"],["dc.contributor.author","Vogel, Britta"],["dc.contributor.author","Haas, Jan"],["dc.contributor.author","Völker, Uwe"],["dc.contributor.author","Ernst, Florian"],["dc.contributor.author","Teumer, Alexander"],["dc.contributor.author","Ehlermann, Philipp"],["dc.contributor.author","Zugck, Christian"],["dc.contributor.author","Friedrichs, Frauke"],["dc.contributor.author","Kroemer, Heyo"],["dc.contributor.author","Dörr, Marcus"],["dc.contributor.author","Hoffmann, Wolfgang"],["dc.contributor.author","Maisch, Bernhard"],["dc.contributor.author","Pankuweit, Sabine"],["dc.contributor.author","Ruppert, Volker"],["dc.contributor.author","Scheffold, Thomas"],["dc.contributor.author","Kühl, Uwe"],["dc.contributor.author","Schultheiss, Hans-Peter"],["dc.contributor.author","Kreutz, Reinhold"],["dc.contributor.author","Ertl, Georg"],["dc.contributor.author","Angermann, Christiane"],["dc.contributor.author","Charron, Philippe"],["dc.contributor.author","Villard, Eric"],["dc.contributor.author","Gary, Françoise"],["dc.contributor.author","Isnard, Richard"],["dc.contributor.author","Komajda, Michel"],["dc.contributor.author","Lutz, Matthias"],["dc.contributor.author","Meitinger, Thomas"],["dc.contributor.author","Sinner, Moritz F."],["dc.contributor.author","Wichmann, H.-Erich"],["dc.contributor.author","Krawczak, Michael"],["dc.contributor.author","Ivandic, Boris"],["dc.contributor.author","Weichenhan, Dieter"],["dc.contributor.author","Gelbrich, Goetz"],["dc.contributor.author","El-Mokhtari, Nour-Eddine"],["dc.contributor.author","Schreiber, Stefan"],["dc.contributor.author","Felix, Stephan B."],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Pfeufer, Arne"],["dc.contributor.author","Hübner, Norbert"],["dc.contributor.author","Kääb, Stefan"],["dc.contributor.author","Arbustini, Eloisa"],["dc.contributor.author","Rottbauer, Wolfgang"],["dc.contributor.author","Frey, Norbert"],["dc.contributor.author","Stoll, Monika"],["dc.contributor.author","Katus, Hugo A."],["dc.date.accessioned","2017-09-07T11:46:19Z"],["dc.date.available","2017-09-07T11:46:19Z"],["dc.date.issued","2014"],["dc.description.abstract","Aims Dilated cardiomyopathy (DCM) is one of the leading causes for cardiac transplantations and accounts for up to one-third of all heart failure cases. Since extrinsic and monogenic causes explain only a fraction of all cases, common genetic variants are suspected to contribute to the pathogenesis of DCM, its age of onset, and clinical progression. By a large-scale case-control genome-wide association study we aimed here to identify novel genetic risk loci for DCM. Methods and reuslts Applying a three-staged study design, we analysed more than 4100 DCM cases and 7600 controls. We identified and successfully replicated multiple single nucleotide polymorphism on chromosome 6p21. In the combined analysis, the most significant association signal was obtained for rs9262636 (P = 4.90 x 10(-9)) located in HCG22, which could again be replicated in an independent cohort. Taking advantage of expression quantitative trait loci (eQTL) as molecular phenotypes, we identified rs9262636 as an eQTL for several closely located genes encoding class I and class II major histocompatibility complex heavy chain receptors. Conclusion The present study reveals a novel genetic susceptibility locus that clearly underlines the role of genetically driven, inflammatory processes in the pathogenesis of idiopathic DCM."],["dc.identifier.doi","10.1093/eurheartj/eht251"],["dc.identifier.gro","3142146"],["dc.identifier.isi","000335813500015"],["dc.identifier.pmid","23853074"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5044"],["dc.language.iso","en"],["dc.notes.intern","WoS Import 2017-03-10 / Funder: Bndesministerium fur Bildung und Forschung' (BMBF)"],["dc.notes.status","final"],["dc.notes.submitter","PUB_WoS_Import"],["dc.relation.eissn","1522-9645"],["dc.relation.issn","0195-668X"],["dc.title","A genome-wide association study identifies 6p21 as novel risk locus for dilated cardiomyopathy"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","308"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Nature Reviews Cardiology"],["dc.bibliographiccitation.lastpage","316"],["dc.bibliographiccitation.volume","10"],["dc.contributor.author","Voelzke, Henry"],["dc.contributor.author","Schmidt, Carsten O."],["dc.contributor.author","Baumeister, Sebastian E."],["dc.contributor.author","Ittermann, Till"],["dc.contributor.author","Fung, Glenn"],["dc.contributor.author","Krafczyk-Korth, Janina"],["dc.contributor.author","Hoffmann, Wolfgang"],["dc.contributor.author","Schwab, Matthias"],["dc.contributor.author","Schwabedissen, Henriette E. Meyer zu"],["dc.contributor.author","Doerr, Marcus"],["dc.contributor.author","Felix, Stephan B."],["dc.contributor.author","Lieb, Wolfgang"],["dc.contributor.author","Kroemer, Heyo K."],["dc.date.accessioned","2018-11-07T09:24:22Z"],["dc.date.available","2018-11-07T09:24:22Z"],["dc.date.issued","2013"],["dc.description.abstract","The primary goals of personalized medicine are to optimize diagnostic and treatment strategies by tailoring them to the specific characteristics of an individual patient. In this Review, we summarize basic concepts and methods of personalizing cardiovascular medicine. In-depth characterization of study participants and patients in general practice using standardized methods is a pivotal component of study design in personalized medicine. Standardization and quality assurance of clinical data are similarly important, but in daily practice imprecise definitions of clinical variables can reduce power and introduce bias, which limits the validity of the data obtained as well as their potential clinical applicability. Changes in statistical methods with personalized medicine include a shift from dichotomous outcomes towards continuously measured variables, predictive modelling, and individualized medical decisions, subgroup analyses, and data-mining strategies. A variety of approaches to personalized medicine exist in cardiovascular research and clinical practice that might have the potential to individualize diagnostic and therapeutic procedures. For some of the emerging methods, such as data mining, the most-efficient way to use these tools is not yet fully understood. In addition, the predictive models-although promising-are far from mature, and are likely to be greatly improved by using available large-scale data sets."],["dc.identifier.doi","10.1038/nrcardio.2013.35"],["dc.identifier.isi","000319441300007"],["dc.identifier.pmid","23528962"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/29806"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Nature Publishing Group"],["dc.relation.issn","1759-5010"],["dc.relation.issn","1759-5002"],["dc.title","Personalized cardiovascular medicine: concepts and methodological considerations"],["dc.type","review"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1405"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Metabolomics"],["dc.bibliographiccitation.lastpage","1415"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Friedrich, Nele"],["dc.contributor.author","Budde, Kathrin"],["dc.contributor.author","Suhre, Karsten"],["dc.contributor.author","Voelker, Uwe"],["dc.contributor.author","John, Ulrich"],["dc.contributor.author","Felix, Stephan B."],["dc.contributor.author","Kroemer, Heyo K."],["dc.contributor.author","Grabe, Hans Joergen"],["dc.contributor.author","Voelzke, Henry"],["dc.contributor.author","Nauck, Matthias"],["dc.contributor.author","Wallaschofski, Henri"],["dc.date.accessioned","2018-11-07T09:51:23Z"],["dc.date.available","2018-11-07T09:51:23Z"],["dc.date.issued","2015"],["dc.description.abstract","Recently research provides evidence that blood metabolite profiles predicted type 2 diabetes. We aimed to assess the relation of urine metabolites measured via nuclear magnetic resonance spectroscopy with incident type 2 diabetes in a sample of 1353 men and 1356 women. Within 5 years, 87 men and 50 women developed diabetes. Five and 16 urine metabolites were associated with incident diabetes in men and women, respectively. Only three of these metabolites (glucose, lactate and glycine) were found in both sexes. In women, e.g. acetate, carnitine, N,N-dimethylglycine, trigonelline, 3-hydroxyisovalerate, alanine, formate, glycolate, trimethylamine N-oxide and tau-methylhistidine were positively related with diabetes. Receiver operating characteristic (ROC) analysis revealed that compared with a standard model, a model additionally adjusted for urine glucose, trigonelline and trimethylamine N-oxide levels showed a better discrimination between incident diabetes cases and non-cases in women (AUC = 0.874 and 0.903, p = 0.019). In men, valine and 4-hydroxyphenylacetate were found as markers of diabetes. However, ROC analysis did not reveal any improvement in discrimination based on urine metabolites. In conclusion, we confirmed the potential of metabolomics to assess the risk of type 2 diabetes and detected pronounced sex differences. Moreover, we demonstrated the practicability of spot urine samples as potential non-invasive diabetes screening approach."],["dc.identifier.doi","10.1007/s11306-015-0795-6"],["dc.identifier.isi","000360715300034"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35903"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.relation.issn","1573-3890"],["dc.relation.issn","1573-3882"],["dc.title","Sex differences in urine metabolites related with risk of diabetes using NMR spectroscopy: results of the study of health in pomerania"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","144"],["dc.bibliographiccitation.journal","Journal of Translational Medicine"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Grabe, Hans Joergen"],["dc.contributor.author","Assel, Heinrich"],["dc.contributor.author","Bahls, Thomas"],["dc.contributor.author","Doerr, Marcus"],["dc.contributor.author","Endlich, Karlhans"],["dc.contributor.author","Endlich, Nicole"],["dc.contributor.author","Erdmann, Pia"],["dc.contributor.author","Ewert, Ralf"],["dc.contributor.author","Felix, Stephan B."],["dc.contributor.author","Fiene, Beate"],["dc.contributor.author","Fischer, Tobias"],["dc.contributor.author","Flessa, Steffen"],["dc.contributor.author","Friedrich, Nele"],["dc.contributor.author","Gadebusch-Bondio, Mariacarla"],["dc.contributor.author","Salazar, Manuela Gesell"],["dc.contributor.author","Hammer, Elke"],["dc.contributor.author","Haring, Robin"],["dc.contributor.author","Havemann, Christoph"],["dc.contributor.author","Hecker, Michael"],["dc.contributor.author","Hoffmann, Wolfgang"],["dc.contributor.author","Holtfreter, Birte"],["dc.contributor.author","Kacprowski, Tim"],["dc.contributor.author","Klein, Kathleen"],["dc.contributor.author","Kocher, Thomas"],["dc.contributor.author","Kock, Holger"],["dc.contributor.author","Krafczyk, Janina"],["dc.contributor.author","Kuhn, Jana"],["dc.contributor.author","Langanke, Martin"],["dc.contributor.author","Lendeckel, Uwe"],["dc.contributor.author","Lerch, Markus M."],["dc.contributor.author","Lieb, Wolfgang"],["dc.contributor.author","Lorbeer, Roberto"],["dc.contributor.author","Mayerle, Julia"],["dc.contributor.author","Meissner, Konrad"],["dc.contributor.author","Schwabedissen, Henriette E. Meyer zu"],["dc.contributor.author","Nauck, Matthias"],["dc.contributor.author","Ott, Konrad"],["dc.contributor.author","Rathmann, Wolfgang"],["dc.contributor.author","Rettig, Rainer"],["dc.contributor.author","Richardt, Claudia"],["dc.contributor.author","Salje, Karen"],["dc.contributor.author","Schminke, Ulf"],["dc.contributor.author","Schulz, Andrea"],["dc.contributor.author","Schwab, Matthias"],["dc.contributor.author","Siegmund, Werner"],["dc.contributor.author","Stracke, Sylvia"],["dc.contributor.author","Suhre, Karsten"],["dc.contributor.author","Ueffing, Marius"],["dc.contributor.author","Ungerer, Saskia"],["dc.contributor.author","Voelker, Uwe"],["dc.contributor.author","Voelzke, Henry"],["dc.contributor.author","Wallaschofski, Henri"],["dc.contributor.author","Werner, Vivian"],["dc.contributor.author","Zygmunt, Marek T."],["dc.contributor.author","Kroemer, Heyo K."],["dc.date.accessioned","2018-11-07T09:39:59Z"],["dc.date.available","2018-11-07T09:39:59Z"],["dc.date.issued","2014"],["dc.description.abstract","Background: Individualized Medicine aims at providing optimal treatment for an individual patient at a given time based on his specific genetic and molecular characteristics. This requires excellent clinical stratification of patients as well as the availability of genomic data and biomarkers as prerequisites for the development of novel diagnostic tools and therapeutic strategies. The University Medicine Greifswald, Germany, has launched the \"Greifswald Approach to Individualized Medicine\" (GANI_MED) project to address major challenges of Individualized Medicine. Herein, we describe the implementation of the scientific and clinical infrastructure that allows future translation of findings relevant to Individualized Medicine into clinical practice. Methods/design: Clinical patient cohorts (N > 5,000) with an emphasis on metabolic and cardiovascular diseases are being established following a standardized protocol for the assessment of medical history, laboratory biomarkers, and the collection of various biosamples for bio-banking purposes. A multi-omics based biomarker assessment including genome-wide genotyping, transcriptome, metabolome, and proteome analyses complements the multi-level approach of GANI_MED. Comparisons with the general background population as characterized by our Study of Health in Pomerania (SHIP) are performed. A central data management structure has been implemented to capture and integrate all relevant clinical data for research purposes. Ethical research projects on informed consent procedures, reporting of incidental findings, and economic evaluations were launched in parallel."],["dc.identifier.doi","10.1186/1479-5876-12-144"],["dc.identifier.isi","000338469800002"],["dc.identifier.pmid","24886498"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10153"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/33415"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","1479-5876"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Cohort profile: Greifswald approach to individualized medicine (GANI_MED)"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","2142"],["dc.bibliographiccitation.issue","11"],["dc.bibliographiccitation.journal","Journal of Hypertension"],["dc.bibliographiccitation.lastpage","2150"],["dc.bibliographiccitation.volume","31"],["dc.contributor.author","Voelzke, Henry"],["dc.contributor.author","Fung, Glenn"],["dc.contributor.author","Ittermann, Till"],["dc.contributor.author","Yu, Shipeng"],["dc.contributor.author","Baumeister, Sebastian E."],["dc.contributor.author","Doerr, Marcus"],["dc.contributor.author","Lieb, Wolfgang"],["dc.contributor.author","Voelker, Uwe"],["dc.contributor.author","Linneberg, Allan"],["dc.contributor.author","Jorgensen, Torben"],["dc.contributor.author","Felix, Stephan B."],["dc.contributor.author","Rettig, Rainer"],["dc.contributor.author","Rao, B. Bhaskara"],["dc.contributor.author","Kroemer, Heyo K."],["dc.date.accessioned","2018-11-07T09:18:05Z"],["dc.date.available","2018-11-07T09:18:05Z"],["dc.date.issued","2013"],["dc.description.abstract","Objective:Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures.Methods:The primary study population consisted of 1605 normotensive individuals aged 20-79 years with 5-year follow-up from the population-based study, that is the Study of Health in Pomerania (SHIP). The initial set was randomly split into a training and a testing set. We used a probabilistic graphical model applying a Bayesian network to create a predictive model for incident hypertension and compared the predictive performance with the established Framingham risk score for hypertension. Finally, the model was validated in 2887 participants from INTER99, a Danish community-based intervention study.Results:In the training set of SHIP data, the Bayesian network used a small subset of relevant baseline features including age, mean arterial pressure, rs16998073, serum glucose and urinary albumin concentrations. Furthermore, we detected relevant interactions between age and serum glucose as well as between rs16998073 and urinary albumin concentrations [area under the receiver operating characteristic (AUC 0.76)]. The model was confirmed in the SHIP validation set (AUC 0.78) and externally replicated in INTER99 (AUC 0.77). Compared to the established Framingham risk score for hypertension, the predictive performance of the new model was similar in the SHIP validation set and moderately better in INTER99.Conclusion:Data mining procedures identified a predictive model for incident hypertension, which included innovative and easy-to-measure variables. The findings promise great applicability in screening settings and clinical practice."],["dc.identifier.doi","10.1097/HJH.0b013e328364a16d"],["dc.identifier.isi","000326601100010"],["dc.identifier.pmid","24077244"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/28329"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Lippincott Williams & Wilkins"],["dc.relation.issn","1473-5598"],["dc.relation.issn","0263-6352"],["dc.title","A new, accurate predictivemodel for incident hypertension"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]