Rosenberger, Albert

[["dc.bibliographiccitation.artnumber","S55"],["dc.bibliographiccitation.journal","BMC Genetics"],["dc.bibliographiccitation.volume","6"],["dc.contributor.author","Rosenberger, Albert"],["dc.contributor.author","Janicke, N."],["dc.contributor.author","Kohler, K."],["dc.contributor.author","Korb, Katrin"],["dc.contributor.author","Kulle, Bettina"],["dc.contributor.author","Bickeboeller, Heike"],["dc.date.accessioned","2018-11-07T10:53:25Z"],["dc.date.available","2018-11-07T10:53:25Z"],["dc.date.issued","2005"],["dc.description.abstract","For the identification of susceptibility loci in complex diseases the choice of the target phenotype is very important. We compared results of genome-wide searches for linkage or for association related to three phenotypes for alcohol use disorder. These are a behavioral score BQ, based on a 12-item questionnaire about drinking behavior and the subject's report of drinking-related health problems, and ERP pattern and ERP magnitude, both derived from the eyes closed resting ERP measures to quantify brain activity. Overall, we were able to identify 11 candidate regions for linkage. Only two regions were found to be related to both BQ and one of the ERP phenotypes. The genome-wide search for association using single-nucleotide polymorphisms did not yield interesting leads."],["dc.identifier.doi","10.1186/1471-2156-6-S1-S55"],["dc.identifier.isi","000236103400055"],["dc.identifier.pmid","16451667"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?goescholar/1371"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/49360"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Biomed Central Ltd"],["dc.publisher.place","London"],["dc.relation.conference","14th Genetic Analysis Workshop"],["dc.relation.eventlocation","Noordwijkerhout, NETHERLANDS"],["dc.relation.issn","1471-2156"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Surrogate phenotype definition for alcohol use disorders: a genome-wide search for linkage and association"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","44634"],["dc.bibliographiccitation.journal","Scientific Reports"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Pan, Yongchu"],["dc.contributor.author","Liu, Hongliang"],["dc.contributor.author","Wang, Y."],["dc.contributor.author","Kang, Xiaozheng"],["dc.contributor.author","Liu, Zhensheng"],["dc.contributor.author","Owzar, Kouros"],["dc.contributor.author","Han, Younghun"],["dc.contributor.author","Su, L. I."],["dc.contributor.author","Wei, Yongyue"],["dc.contributor.author","Hung, Rayjean J."],["dc.contributor.author","Brhane, Yonathan"],["dc.contributor.author","McLaughlin, John R."],["dc.contributor.author","Brennan, P. C."],["dc.contributor.author","Bickeboeller, Heike"],["dc.contributor.author","Rosenberger, Albert"],["dc.contributor.author","Houlston, Richard S."],["dc.contributor.author","Caporaso, Neil E."],["dc.contributor.author","Landi, Maria Teresa"],["dc.contributor.author","Heinrich, Joachim"],["dc.contributor.author","Risch, Angela"],["dc.contributor.author","Wu, X."],["dc.contributor.author","Ye, Yuanqing"],["dc.contributor.author","Christiani, David C."],["dc.contributor.author","Amos, Christopher I."],["dc.contributor.author","Wei, Qingyi"],["dc.date.accessioned","2018-11-07T10:26:10Z"],["dc.date.available","2018-11-07T10:26:10Z"],["dc.date.issued","2017"],["dc.description.abstract","mRNA splicing is an important mechanism to regulate mRNA expression. Abnormal regulation of this process may lead to lung cancer. Here, we investigated the associations of 11,966 single-nucleotide polymorphisms (SNPs) in 206 mRNA splicing-related genes with lung cancer risk by using the summary data from six published genome-wide association studies (GWASs) of Transdisciplinary Research in Cancer of the Lung (TRICL) (12,160 cases and 16,838 controls) and another two lung cancer GWASs of Harvard University (984 cases and 970 controls) and deCODE (1,319 cases and 26,380 controls). We found that a total of 12 significant SNPs with false discovery rate (FDR) <= 0.05 were mapped to one novel gene PRPF6 and two previously reported genes (DHX16 and LSM2) that were also confirmed in this study. The six novel SNPs in PRPF6 were in high linkage disequilibrium and associated with PRPF6 mRNA expression in lymphoblastoid cells from 373 Europeans in the 1000 Genomes Project. Taken together, our studies shed new light on the role of mRNA splicing genes in the development of lung cancer."],["dc.identifier.doi","10.1038/srep44634"],["dc.identifier.isi","000397001600001"],["dc.identifier.pmid","28304396"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14434"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/42982"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Nature Publishing Group"],["dc.relation.issn","2045-2322"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Associations between genetic variants in mRNA splicing-related genes and risk of lung cancer: a pathway-based analysis from published GWASs"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.issue","60"],["dc.bibliographiccitation.journal","BMC Cancer"],["dc.bibliographiccitation.lastpage","12"],["dc.bibliographiccitation.volume","8"],["dc.contributor.author","Rosenberger, Albert"],["dc.contributor.author","Illig, Thomas"],["dc.contributor.author","Korb, Katrin"],["dc.contributor.author","Klopp, Norman"],["dc.contributor.author","Zietemann, Vera"],["dc.contributor.author","Wölke, Gabi"],["dc.contributor.author","Meese, Eckart"],["dc.contributor.author","Sybrecht, Gerhard"],["dc.contributor.author","Kronenberg, Florian"],["dc.contributor.author","Cebulla, Mathias"],["dc.contributor.author","Degen, Maria"],["dc.contributor.author","Drings, Peter"],["dc.contributor.author","Gröschel, Andreas"],["dc.contributor.author","Konietzko, Nikolaus"],["dc.contributor.author","Kreymborg, Karsten Grosse"],["dc.contributor.author","Häußinger, Karl"],["dc.contributor.author","Höffken, Gerd"],["dc.contributor.author","Jilge, Bettina"],["dc.contributor.author","Ko, You-Dschun"],["dc.contributor.author","Morr, Harald"],["dc.date.accessioned","2019-07-10T08:12:54Z"],["dc.date.available","2019-07-10T08:12:54Z"],["dc.date.issued","2008"],["dc.description.abstract","Background: Early onset lung cancer shows some familial aggregation, pointing to a genetic predisposition. This study was set up to investigate the role of candidate genes in the susceptibility to lung cancer patients younger than 51 years at diagnosis. Methods: 246 patients with a primary, histologically or cytologically confirmed neoplasm, recruited from 2000 to 2003 in major lung clinics across Germany, were matched to 223 unrelated healthy controls. 11 single nucleotide polymorphisms of genes with reported associations to lung cancer have been genotyped. Results: Genetic associations or gene-smoking interactions was found for GPX1(Pro200Leu) and EPHX1(His113Tyr). Carriers of the Leu-allele of GPX1(Pro200Leu) showed a significant risk reduction of OR = 0.6 (95% CI: 0.40.8, p = 0.002) in general and of OR = 0.3 (95% CI:0.10.8, p = 0.012) within heavy smokers. We could also find a risk decreasing genetic effect for His-carriers of EPHX1(His113Tyr) for moderate smokers (OR = 0.2, 95% CI:0.10.7, p = 0.012). Considered both variants together, a monotone decrease of the OR was found for smokers (OR of 0.20; 95% CI: 0.070.60) for each protective allele. Conclusion: Smoking is the most important risk factor for young lung cancer patients. However, this study provides some support for the T-Allel of GPX1(Pro200Leu) and the C-Allele of EPHX1(His113Tyr) to play a protective role in early onset lung cancer susceptibility."],["dc.identifier.fs","161137"],["dc.identifier.ppn","576826227"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/4326"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/61073"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.orgunit","Universitätsmedizin Göttingen"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.subject.ddc","616"],["dc.title","Do genetic factors protect for early onset lung cancer? A case control study before the age of 50 years"],["dc.title.alternative","Research article"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","44"],["dc.bibliographiccitation.journal","BMC Genetics"],["dc.bibliographiccitation.volume","8"],["dc.contributor.author","Rosenberger, Albert"],["dc.contributor.author","Sharma, Manu"],["dc.contributor.author","Mueller-Myhsok, Bertram"],["dc.contributor.author","Gasser, Thomas"],["dc.contributor.author","Bickeboeller, Heike"],["dc.date.accessioned","2018-11-07T11:00:44Z"],["dc.date.available","2018-11-07T11:00:44Z"],["dc.date.issued","2007"],["dc.description.abstract","Background: Genome wide linkage scans have often been successful in the identification of genetic regions containing susceptibility genes for a disease. Meta analysis is used to synthesize information and can even deliver evidence for findings missed by original studies. If researchers are not contributing their data, extracting valid information from publications is technically challenging, but worth the effort. We propose an approach to include data extracted from published figures of genome wide linkage scans. The validity of the extraction was examined on the basis of those 25 markers, for which sufficient information was reported. Monte Carlo simulations were used to take into account the uncertainty in marker position and in linkage test statistic. For the final meta analysis we compared the Genome Search Meta Analysis method (GSMA) and the Corrected p-value Meta analysis Method (CPMM). An application to Parkinson's disease is given. Because we had to use secondary data a meta analysis based on original summary values would be desirable. Results: Data uncertainty by replicated extraction of marker position is shown to be much smaller than 30 cM, a distance up to which a maximum LOD score may usually be found away from the true locus. The main findings are not impaired by data uncertainty. Conclusion: Applying the proposed method a novel linked region for Parkinson's disease was identified on chromosome 14 ( p= 0.036). Comparing the two meta analysis methods we found in this analysis more regions of interest being identified by GSMA, whereas CPMM provides stronger evidence for linkage. For further validation of the extraction method comparisons with raw data would be required."],["dc.identifier.doi","10.1186/1471-2156-8-44"],["dc.identifier.isi","000248703900001"],["dc.identifier.pmid","17605797"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?goescholar/1251"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/50989"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Biomed Central Ltd"],["dc.relation.issn","1471-2156"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Meta analysis of whole-genome linkage scans with data uncertainty: an application to Parkinson's disease"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","S95"],["dc.bibliographiccitation.issue","Suppl 7"],["dc.bibliographiccitation.journal","BMC Proceedings"],["dc.bibliographiccitation.volume","3"],["dc.contributor.author","Sohns, Melanie"],["dc.contributor.author","Rosenberger, Albert"],["dc.contributor.author","Bickeböller, Heike"],["dc.date.accessioned","2016-02-18T17:03:24Z"],["dc.date.accessioned","2021-10-27T13:20:24Z"],["dc.date.available","2016-02-18T17:03:24Z"],["dc.date.available","2021-10-27T13:20:24Z"],["dc.date.issued","2009"],["dc.date.updated","2016-02-18T17:03:24Z"],["dc.description.abstract","Abstract In genome-wide association studies (GWAS) genetic markers are often ranked to select genes for further pursuit. Especially for moderately associated and interrelated genes, information on genes and pathways may improve the selection. We applied and combined two main approaches for data integration to a GWAS for rheumatoid arthritis, gene set enrichment analysis (GSEA) and hierarchical Bayes prioritization (HBP). Many associated genes are located in the HLA region on 6p21. However, the ranking lists of genes and gene sets differ considerably depending on the chosen approach: HBP changes the ranking only slightly and primarily contains HLA genes in the top 100 gene lists. GSEA includes also many non-HLA genes."],["dc.identifier.doi","10.1186/1753-6561-3-S7-S95"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/12881"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/91963"],["dc.language.iso","en"],["dc.notes.intern","Migrated from goescholar"],["dc.relation.orgunit","Universitätsmedizin Göttingen"],["dc.rights","CC BY 2.0"],["dc.rights.holder","Sohns et al; licensee BioMed Central Ltd."],["dc.rights.uri","https://creativecommons.org/licenses/by/2.0"],["dc.title","Integration of a priori gene set information into genome-wide association studies"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1709"],["dc.bibliographiccitation.issue","12"],["dc.bibliographiccitation.journal","Cancer Causes & Control"],["dc.bibliographiccitation.lastpage","1720"],["dc.bibliographiccitation.volume","22"],["dc.contributor.author","McCormack, Valerie A."],["dc.contributor.author","Hung, Rayjean J."],["dc.contributor.author","Brenner, Darren R."],["dc.contributor.author","Bickeboeller, Heike"],["dc.contributor.author","Rosenberger, Albert"],["dc.contributor.author","Muscat, Joshua E."],["dc.contributor.author","Lazarus, Philip"],["dc.contributor.author","Tjonneland, Anne"],["dc.contributor.author","Friis, Soren"],["dc.contributor.author","Christiani, David C."],["dc.contributor.author","Chun, Eun-mi"],["dc.contributor.author","Le Marchand, Loic"],["dc.contributor.author","Rennert, Gad"],["dc.contributor.author","Rennert, Hedy S."],["dc.contributor.author","Andrew, Angeline S."],["dc.contributor.author","Orlow, Irene"],["dc.contributor.author","Park, Bernard J."],["dc.contributor.author","Boffetta, Paolo"],["dc.contributor.author","Duell, Eric J."],["dc.date.accessioned","2018-11-07T08:49:20Z"],["dc.date.available","2018-11-07T08:49:20Z"],["dc.date.issued","2011"],["dc.description.abstract","Purpose To investigate the hypothesis that non-steroidal anti-inflammatory drugs (NSAIDs) lower lung cancer risk. Methods We analysed pooled individual-level data from seven case-control and one cohort study in the International Lung Cancer Consortium (ILCCO). Relative risks for lung cancer associated with self-reported history of aspirin and other NSAID use were estimated within individual studies using logistic regression or proportional hazards models, adjusted for packyears of smoking, age, calendar period, ethnicity and education and were combined using random effects meta-analysis. Results A total of 4,309 lung cancer cases (mean age at diagnosis 65 years, 45% adenocarcinoma and 22% squamous-cell carcinoma) and 58,301 non-cases/controls were included. Amongst controls, 34% had used NSAIDs in the past (81% of them used aspirin). After adjustment for negative confounding by smoking, ever-NSAID use (affirmative answer to the study-specific question on NSAID use) was associated with a 26% reduction (95% confidence interval 8 to 41%) in lung cancer risk in men, but not in women (3% increase (-11% to 30%)). In men, the association was stronger in current and former smokers, and for squamous-cell carcinoma than for adenocarcinomas, but there was no trend with duration of use. No differences were found in the effects on lung cancer risk of aspirin and non-aspirin NSAIDs. Conclusions Evidence from ILCCO suggests that NSAID use in men confers a modest protection for lung cancer, especially amongst ever-smokers. Additional investigation is needed regarding the possible effects of age, duration, dose and type of NSAID and whether effect modification by smoking status or sex exists."],["dc.identifier.doi","10.1007/s10552-011-9847-z"],["dc.identifier.isi","000297799200010"],["dc.identifier.pmid","21987079"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/21438"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.relation.issn","1573-7225"],["dc.relation.issn","0957-5243"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Aspirin and NSAID use and lung cancer risk: a pooled analysis in the International Lung Cancer Consortium (ILCCO)"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","2021"],["dc.bibliographiccitation.issue","11"],["dc.bibliographiccitation.journal","Cancer Immunology Immunotherapy"],["dc.bibliographiccitation.lastpage","2031"],["dc.bibliographiccitation.volume","61"],["dc.contributor.author","Buhl, Timo"],["dc.contributor.author","Legler, Tobias Joerg"],["dc.contributor.author","Rosenberger, Albert"],["dc.contributor.author","Schardt, Anke"],["dc.contributor.author","Schoen, Michael Peter"],["dc.contributor.author","Haenssle, Holger Andreas"],["dc.date.accessioned","2018-11-07T09:03:57Z"],["dc.date.available","2018-11-07T09:03:57Z"],["dc.date.issued","2012"],["dc.description.abstract","Availability of large quantities of functionally effective dendritic cells (DC) represents one of the major challenges for immunotherapeutic trials against infectious or malignant diseases. Low numbers or insufficient T-cell activation of DC may result in premature termination of treatment and unsatisfying immune responses in clinical trials. Based on the notion that cryopreservation of monocytes is superior to cryopreservation of immature or mature DC in terms of resulting DC quantity and immuno-stimulatory capacity, we aimed to establish an optimized protocol for the cryopreservation of highly concentrated peripheral blood mononuclear cells (PBMC) for DC-based immunotherapy. Cryopreserved cell preparations were analyzed regarding quantitative recovery, viability, phenotype, and functional properties. In contrast to standard isopropyl alcohol (IPA) freezing, PBMC cryopreservation in an automated controlled-rate freezer (CRF) with subsequent thawing and differentiation resulted in significantly higher cell yields of immature and mature DC. Immature DC yields and total protein content after using CRF were comparable with results obtained with freshly prepared PBMC and exceeded results of standard IPA freezing by approximately 50 %. While differentiation markers, allogeneic T-cell stimulation, viability, and cytokine profiles were similar to DC from standard freezing procedures, DC generated from CRF-cryopreserved PBMC induced a significantly higher antigen-specific IFN-gamma release from autologous effector T cells. In summary, automated controlled-rate freezing of highly concentrated PBMC represents an improved method for increasing DC yields and autologous T-cell stimulation."],["dc.description.sponsorship","University Medical Center Gottingen for young researchers"],["dc.identifier.doi","10.1007/s00262-012-1262-0"],["dc.identifier.isi","000310888400012"],["dc.identifier.pmid","22527251"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/8798"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/25006"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.relation.issn","0340-7004"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Controlled-rate freezer cryopreservation of highly concentrated peripheral blood mononuclear cells results in higher cell yields and superior autologous T-cell stimulation for dendritic cell-based immunotherapy"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","S85"],["dc.bibliographiccitation.journal","BMC Genetics"],["dc.bibliographiccitation.volume","4"],["dc.contributor.author","Kulle, Bettina"],["dc.contributor.author","Kohler, K."],["dc.contributor.author","Rosenberger, Albert"],["dc.contributor.author","Loesgen, S."],["dc.contributor.author","Bickeboeller, Heike"],["dc.date.accessioned","2018-11-07T10:33:58Z"],["dc.date.available","2018-11-07T10:33:58Z"],["dc.date.issued","2003"],["dc.description.abstract","Basically no methods are available for the analysis of quantitative traits in longitudinal genetic epidemiological studies. We introduce a nonparametric factorial design for longitudinal data on independent sib pairs, modelling the phenotypic quadratic differences as the dependent variable. Factors are the number of alleles shared identically by descent (IBD) and the age categories at which the dependent variable is measured, allowing for dependence due to age. To identify a linked marker a rank statistic tests the influence of IBD group on phenotypic quadratic differences. No assumptions are made on normality or variances of the dependent variable. We apply our method to 71 sib pairs from the Framingham Heart Study data provided at the Genetic Analysis Workshop 13. For all 15 available markers on chromosome 17 we analyzed the influence on systolic blood pressure. In addition, different selection strategies to sample from the whole data are discussed."],["dc.identifier.doi","10.1186/1471-2156-4-S1-S85"],["dc.identifier.isi","000188320900085"],["dc.identifier.pmid","14975153"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?goescholar/1248"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/44749"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Biomed Central Ltd"],["dc.publisher.place","London"],["dc.relation.conference","13th Genetic Analysis Workshop"],["dc.relation.eventlocation","NEW ORLEANS, LOUISIANA"],["dc.relation.issn","1471-2156"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Nonparametric longitudinal allele-sharing model"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","14"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","European Journal of Medical Research"],["dc.bibliographiccitation.volume","27"],["dc.contributor.author","Rosenberger, Albert"],["dc.contributor.author","Muttray, Nils"],["dc.contributor.author","Hung, Rayjean J."],["dc.contributor.author","Christiani, David C."],["dc.contributor.author","Caporaso, Neil E."],["dc.contributor.author","Liu, Geoffrey"],["dc.contributor.author","Bojesen, Stig E."],["dc.contributor.author","Le Marchand, Loic"],["dc.contributor.author","Albanes, Demetrios"],["dc.contributor.author","Aldrich, Melinda C."],["dc.contributor.author","Tardon, Adonina"],["dc.contributor.author","Fernández-Tardón, Guillermo"],["dc.contributor.author","Rennert, Gad"],["dc.contributor.author","Field, John K."],["dc.contributor.author","Davies, Michael P. A."],["dc.contributor.author","Liloglou, Triantafillos"],["dc.contributor.author","Kiemeney, Lambertus A."],["dc.contributor.author","Lazarus, Philip"],["dc.contributor.author","Wendel, Bernadette"],["dc.contributor.author","Haugen, Aage"],["dc.contributor.author","Zienolddiny, Shanbeh"],["dc.contributor.author","Lam, Stephen"],["dc.contributor.author","Schabath, Matthew B."],["dc.contributor.author","Andrew, Angeline S."],["dc.contributor.author","Duell, Eric J."],["dc.contributor.author","Arnold, Susanne M."],["dc.contributor.author","Goodman, Gary E."],["dc.contributor.author","Chen, Chu"],["dc.contributor.author","Doherty, Jennifer A."],["dc.contributor.author","Taylor, Fiona"],["dc.contributor.author","Cox, Angela"],["dc.contributor.author","Woll, Penella J."],["dc.contributor.author","Risch, Angela"],["dc.contributor.author","Muley, Thomas R."],["dc.contributor.author","Johansson, Mikael"],["dc.contributor.author","Brennan, Paul"],["dc.contributor.author","Landi, Maria T."],["dc.contributor.author","Shete, Sanjay S."],["dc.contributor.author","Amos, Christopher I."],["dc.contributor.author","Bickeböller, Heike"],["dc.contributor.authorgroup","The INTEGRAL-ILCCO Consortium"],["dc.date.accessioned","2022-04-01T10:03:08Z"],["dc.date.accessioned","2022-08-18T12:40:47Z"],["dc.date.available","2022-04-01T10:03:08Z"],["dc.date.available","2022-08-18T12:40:47Z"],["dc.date.issued","2022-01-31"],["dc.date.updated","2022-07-29T12:18:28Z"],["dc.description.abstract","Background\r\nAberrant Wnt signalling, regulating cell development and stemness, influences the development of many cancer types. The Aryl hydrocarbon receptor (AhR) mediates tumorigenesis of environmental pollutants. Complex interaction patterns of genes assigned to AhR/Wnt-signalling were recently associated with lung cancer susceptibility.\r\n\r\nAim\r\nTo assess the association and predictive ability of AhR/Wnt-genes with lung cancer in cases and controls of European descent.\r\n\r\nMethods\r\nOdds ratios (OR) were estimated for genomic variants assigned to the Wnt agonist and the antagonistic genes DKK2, DKK3, DKK4, FRZB, SFRP4 and Axin2. Logistic regression models with variable selection were trained, validated and tested to predict lung cancer, at which other previously identified SNPs that have been robustly associated with lung cancer risk could also enter the model. Furthermore, decision trees were created to investigate variant × variant interaction. All analyses were performed for overall lung cancer and for subgroups.\r\n\r\nResults\r\nNo genome-wide significant association of AhR/Wnt-genes with overall lung cancer was observed, but within the subgroups of ever smokers (e.g., maker rs2722278 SFRP4; OR  = 1.20; 95% CI 1.13–1.27; p  = 5.6 × 10–10) and never smokers (e.g., maker rs1133683 Axin2; OR  = 1.27; 95% CI 1.19–1.35; p  = 1.0 × 10–12). Although predictability is poor, AhR/Wnt-variants are unexpectedly overrepresented in optimized prediction scores for overall lung cancer and for small cell lung cancer. Remarkably, the score for never-smokers contained solely two AhR/Wnt-variants. The optimal decision tree for never smokers consists of 7 AhR/Wnt-variants and only two lung cancer variants.\r\n\r\nConclusions\r\nThe role of variants belonging to Wnt/AhR-pathways in lung cancer susceptibility may be underrated in main-effects association analysis. Complex interaction patterns in individuals of European descent have moderate predictive capacity for lung cancer or subgroups thereof, especially in never smokers."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2022"],["dc.identifier.citation","European Journal of Medical Research. 2022 Jan 31;27(1):14"],["dc.identifier.doi","10.1186/s40001-022-00638-7"],["dc.identifier.pii","638"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/106090"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/112985"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-530"],["dc.publisher","BioMed Central"],["dc.relation.eissn","2047-783X"],["dc.rights","CC BY 4.0"],["dc.rights.holder","The Author(s)"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject","Susceptibility"],["dc.subject","Association"],["dc.subject","Gene–gene integration"],["dc.subject","Prediction"],["dc.subject","Polygenic risk score"],["dc.subject","Decision trees"],["dc.subject","Never smoker"],["dc.subject","Small cell lung cancer"],["dc.title","Gene–gene interaction of AhRwith and within the Wntcascade affects susceptibility to lung cancer"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","4980"],["dc.bibliographiccitation.issue","22"],["dc.bibliographiccitation.journal","Human Molecular Genetics"],["dc.bibliographiccitation.lastpage","4995"],["dc.bibliographiccitation.volume","21"],["dc.contributor.author","Timofeeva, Maria N."],["dc.contributor.author","Hung, Rayjean J."],["dc.contributor.author","Rafnar, Thorunn"],["dc.contributor.author","Christiani, David C."],["dc.contributor.author","Field, John K."],["dc.contributor.author","Bickeboeller, Heike"],["dc.contributor.author","Risch, Angela"],["dc.contributor.author","McKay, James D."],["dc.contributor.author","Wang, Y."],["dc.contributor.author","Dai, Juncheng"],["dc.contributor.author","Gaborieau, Valerie"],["dc.contributor.author","McLaughlin, John R."],["dc.contributor.author","Brenner, Darren"],["dc.contributor.author","Narod, Steven A."],["dc.contributor.author","Caporaso, Neil E."],["dc.contributor.author","Albanes, Demetrius"],["dc.contributor.author","Thun, Michael"],["dc.contributor.author","Eisen, Timothy"],["dc.contributor.author","Wichmann, Heinz-Erich"],["dc.contributor.author","Rosenberger, Albert"],["dc.contributor.author","Han, Younghun"],["dc.contributor.author","Chen, Wei"],["dc.contributor.author","Zhu, D."],["dc.contributor.author","Spitz, Margaret R."],["dc.contributor.author","Wu, X."],["dc.contributor.author","Pande, Mala"],["dc.contributor.author","Zhao, Yang"],["dc.contributor.author","Zaridze, David"],["dc.contributor.author","Szeszenia-Dabrowska, Neonilia"],["dc.contributor.author","Lissowska, Jolanta"],["dc.contributor.author","Rudnai, Peter"],["dc.contributor.author","Fabianova, Eleonora"],["dc.contributor.author","Mates, Dana"],["dc.contributor.author","Bencko, Vladimir"],["dc.contributor.author","Foretova, Lenka"],["dc.contributor.author","Janout, Vladimir"],["dc.contributor.author","Krokan, Hans E."],["dc.contributor.author","Gabrielsen, Maiken Elvestad"],["dc.contributor.author","Skorpen, Frank"],["dc.contributor.author","Vatten, Lars"],["dc.contributor.author","Njolstad, Inger"],["dc.contributor.author","Chen, Chu"],["dc.contributor.author","Goodman, Gary"],["dc.contributor.author","Lathrop, Mark"],["dc.contributor.author","Benhamou, Simone"],["dc.contributor.author","Vooder, Tonu"],["dc.contributor.author","Vaelk, Kristjan"],["dc.contributor.author","Nelis, Mari"],["dc.contributor.author","Metspalu, Andres"],["dc.contributor.author","Raji, Olaide Y."],["dc.contributor.author","Chen, Ying"],["dc.contributor.author","Gosney, John"],["dc.contributor.author","Liloglou, Triantafillos"],["dc.contributor.author","Muley, Thomas"],["dc.contributor.author","Dienemann, Hendrik"],["dc.contributor.author","Thorleifsson, Gudmar"],["dc.contributor.author","Shen, Hongbing"],["dc.contributor.author","Stefansson, Kari"],["dc.contributor.author","Brennan, P. C."],["dc.contributor.author","Amos, Christopher I."],["dc.contributor.author","Houlston, Richard S."],["dc.contributor.author","Landi, Maria Teresa"],["dc.date.accessioned","2018-11-07T09:03:28Z"],["dc.date.available","2018-11-07T09:03:28Z"],["dc.date.issued","2012"],["dc.description.abstract","Recent genome-wide association studies (GWASs) have identified common genetic variants at 5p15.33, 6p216p22 and 15q25.1 associated with lung cancer risk. Several other genetic regions including variants of CHEK2 (22q12), TP53BP1 (15q15) and RAD52 (12p13) have been demonstrated to influence lung cancer risk in candidate- or pathway-based analyses. To identify novel risk variants for lung cancer, we performed a meta-analysis of 16 GWASs, totaling 14 900 cases and 29 485 controls of European descent. Our data provided increased support for previously identified risk loci at 5p15 (P 7.2 10(16)), 6p21 (P 2.3 10(14)) and 15q25 (P 2.2 10(63)). Furthermore, we demonstrated histology-specific effects for 5p15, 6p21 and 12p13 loci but not for the 15q25 region. Subgroup analysis also identified a novel disease locus for squamous cell carcinoma at 9p21 (CDKN2A/p16(INK4A)/p14(ARF)/CDKN2B/p15(INK4B)/ANRIL; rs1333040, P 3.0 10(7)) which was replicated in a series of 5415 Han Chinese (P 0.03; combined analysis, P 2.3 10(8)). This large analysis provides additional evidence for the role of inherited genetic susceptibility to lung cancer and insight into biological differences in the development of the different histological types of lung cancer."],["dc.identifier.doi","10.1093/hmg/dds334"],["dc.identifier.isi","000310369000016"],["dc.identifier.pmid","22899653"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10648"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/24907"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Oxford Univ Press"],["dc.relation.issn","1460-2083"],["dc.relation.issn","0964-6906"],["dc.rights","CC BY-NC 2.5"],["dc.rights.uri","https://creativecommons.org/licenses/by-nc/2.5"],["dc.title","Influence of common genetic variation on lung cancer risk: meta-analysis of 14 900 cases and 29 485 controls"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]