Publications

958 Publications visible to you, out of a total of 958

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BACKGROUND: Whole-genome studies of vine cultivars have brought novel knowledge about the diversity, geographical relatedness, historical origin and dissemination, phenotype associations and genetic markers. METHOD: We applied SOM (self-organizing maps) portrayal, a neural network-based machine learning method, to re-analyze the genome-wide Single Nucleotide Polymorphism (SNP) data of nearly eight hundred grapevine cultivars. The method generates genome-specific data landscapes. Their topology reflects the geographical distribution of cultivars, indicates paths of cultivar dissemination in history and genome-phenotype associations about grape utilization. RESULTS: The landscape of vine genomes resembles the geographic map of the Mediterranean world, reflecting two major dissemination paths from South Caucasus along a northern route via Balkan towards Western Europe and along a southern route via Palestine and Maghreb towards Iberian Peninsula. The Mediterranean and Black Sea, as well as the Pyrenees, constitute barriers for genetic exchange. On the coarsest level of stratification, cultivars divide into three major groups: Western Europe and Italian grapes, Iberian grapes and vine cultivars from Near East and Maghreb regions. Genetic landmarks were associated with agronomic traits, referring to their utilization as table and wine grapes. Pseudotime analysis describes the dissemination of grapevines in an East to West direction in different waves of cultivation. CONCLUSION: In analogy to the tasks of the wine waiter in gastronomy, the sommelier, our 'SOMmelier'-approach supports understanding the diversity of grapevine genomes in the context of their geographic and historical background, using SOM portrayal. It offers an option to supplement vine cultivar passports by genome fingerprint portraits.

Authors: M. Nikoghosyan, M. Schmidt, K. Margaryan, H. Loeffler-Wirth, A. Arakelyan, H. Binder

Date Published: 17th Jul 2020

Publication Type: Journal article

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The lack of publicly available text corpora is a major obstacle for progress in clinical natural language processing, for non-English speaking countries in particular. In this work, we present GGPONC (German Guideline Program in Oncology NLP Corpus), a freely distributable German language corpus based on clinical practice guidelines in the field of oncology. The corpus is one of the largest corpora of German medical text to date. It does not contain any patient-related data and can therefore be used without data protection restrictions. Moreover, it is the first corpus for the German language covering diverse conditions in a large medical subfield. In addition to the textual sources, we provide a large variety of metadata, such as literature references and evidence levels. By applying and evaluating existing medical information extraction pipelines for German text, we are able to draw comparisons for the use of medical language to other medical text corpora.

Authors: F. Borchert, C. Lohr, L. Modersohn, T. Langer, M. Follmann, J. P. Sachs, U. Hahn, M. P. Schapranow

Date Published: 13th Jul 2020

Publication Type: Misc

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Glioblastoma is a common, malignant brain tumor whose disease incidence increases with age. Glioblastoma stem-like cells (GSCs) are thought to contribute to cancer therapy resistance and to be responsible for tumor initiation, maintenance, and recurrence. This study utilizes both SNP array and gene expression profiling to better understand GSCs and their relation to malignant disease. Peripheral blood and primary glioblastoma tumor tissue were obtained from patients, the latter of which was used to generate GSCs as well as a CD133pos./CD15pos. subpopulation. The stem cell features of GSCs were confirmed via the immunofluorescent expression of Nestin, SOX2, and CD133. Both tumor tissue and the isolated primary cells shared unique abnormal genomic characteristics, including a gain of chromosome 7 as well as either a partial or complete loss of chromosome 10. Individual genomic differences were also observed, including the loss of chromosome 4 and segmental uniparental disomy of 9p24.3-->p21.3 in GSCs. Gene expression profiling revealed 418 genes upregulated in tumor tissue vs. CD133pos./CD15pos. cells and 44 genes upregulated in CD133pos./CD15pos. cells vs. tumor tissue. Pathway analyses demonstrated that upregulated genes in CD133pos./CD15pos. cells are relevant to cell cycle processes and cancerogenesis. In summary, we detected previously undescribed genomic and gene expression differences when comparing tumor tissue and isolated stem-like subpopulations.

Authors: M. Wallenborn, L. X. Xu, H. Kirsten, L. Rohani, D. Rudolf, P. Ahnert, C. Schmidt, R. M. Schulz, M. Richter, W. Krupp, W. Mueller, A. A. Johnson, J. Meixensberger, H. Holland

Date Published: 8th Jul 2020

Publication Type: Journal article

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Importance The limited data on cancer phenotypes in men with germline BRCA1 and BRCA2 pathogenic variants (PVs) have hampered the development of evidence-based recommendations for early cancer detectionn and risk reduction in this population. Objective To compare the cancer spectrum and frequencies between male BRCA1 and BRCA2 PV carriers. Design, Setting, and Participants Retrospective cohort study of 6902 men, including 3651 BRCA1 and 3251 BRCA2 PV carriers, older than 18 years recruited from cancer genetics clinics from 1966 to 2017 by 53 study groups in 33 countries worldwide collaborating through the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Clinical data and pathologic characteristics were collected. Main Outcomes and Measures BRCA1/2 status was the outcome in a logistic regression, and cancer diagnoses were the independent predictors. All odds ratios (ORs) were adjusted for age, country of origin, and calendar year of the first interview. Results Among the 6902 men in the study (median [range] age, 51.6 [18-100] years), 1634 cancers were diagnosed in 1376 men (19.9%), the majority (922 of 1,376 [67%]) being BRCA2 PV carriers. Being affected by any cancer was associated with a higher probability of being a BRCA2, rather than a BRCA1, PV carrier (OR, 3.23; 95% CI, 2.81-3.70; P \textless .001), as well as developing 2 (OR, 7.97; 95% CI, 5.47-11.60; P \textless .001) and 3 (OR, 19.60; 95% CI, 4.64-82.89; P \textless .001) primary tumors. A higher frequency of breast (OR, 5.47; 95% CI, 4.06-7.37; P \textless .001) and prostate (OR, 1.39; 95% CI, 1.09-1.78; P = .008) cancers was associated with a higher probability of being a BRCA2 PV carrier. Among cancers other than breast and prostate, pancreatic cancer was associated with a higher probability (OR, 3.00; 95% CI, 1.55-5.81; P = .001) and colorectal cancer with a lower probability (OR, 0.47; 95% CI, 0.29-0.78; P = .003) of being a BRCA2 PV carrier. Conclusions and Relevance Significant differences in the cancer spectrum were observed in male BRCA2, compared with BRCA1, PV carriers. These data may inform future recommendations for surveillance of BRCA1/2-associated cancers and guide future prospective studies for estimating cancer risks in men with BRCA1/2 PVs.

Authors: Valentina Silvestri, Goska Leslie, Daniel R. Barnes, Bjarni A. Agnarsson, Kristiina Aittomäki, Elisa Alducci, Irene L. Andrulis, Rosa B. Barkardottir, Alicia Barroso, Daniel Barrowdale, Javier Benitez, Bernardo Bonanni, Ake Borg, Saundra S. Buys, Trinidad Caldés, Maria A. Caligo, Carlo Capalbo, Ian Campbell, Wendy K. Chung, Kathleen B. M. Claes, Sarah V. Colonna, Laura Cortesi, Fergus J. Couch, Miguel de La Hoya, Orland Diez, Yuan Chun Ding, Susan Domchek, Douglas F. Easton, Bent Ejlertsen, Christoph Engel, D. Gareth Evans, Lidia Feliubadalò, Lenka Foretova, Florentia Fostira, Lajos Géczi, Anne-Marie Gerdes, Gord Glendon, Andrew K. Godwin, David E. Goldgar, Eric Hahnen, Frans B. L. Hogervorst, John L. Hopper, Peter J. Hulick, Claudine Isaacs, Angel Izquierdo, Paul A. James, Ramunas Janavicius, Uffe Birk Jensen, Esther M. John, Vijai Joseph, Irene Konstantopoulou, Allison W. Kurian, Ava Kwong, Elisabetta Landucci, Fabienne Lesueur, Jennifer T. Loud, Eva Machackova, Phuong L. Mai, Keivan Majidzadeh-A, Siranoush Manoukian, Marco Montagna, Lidia Moserle, Anna Marie Mulligan, Katherine L. Nathanson, Heli Nevanlinna, Joanne Ngeow Yuen Ye, Liene Nikitina-Zake, Kenneth Offit, Edith Olah, Olufunmilayo I. Olopade, Ana Osorio, Laura Papi, Sue K. Park, Inge Sokilde Pedersen, Pedro Perez-Segura, Annabeth H. Petersen, Pedro Pinto, Berardino Porfirio, Miquel Angel Pujana, Paolo Radice, Johanna Rantala, Muhammad U. Rashid, Barak Rosenzweig, Maria Rossing, Marta Santamariña, Rita K. Schmutzler, Leigha Senter, Jacques Simard, Christian F. Singer, Angela R. Solano, Melissa C. Southey, Linda Steele, Zoe Steinsnyder, Dominique Stoppa-Lyonnet, Yen Yen Tan, Manuel R. Teixeira, Soo H. Teo, Mary Beth Terry, Mads Thomassen, Amanda E. Toland, Sara Torres-Esquius, Nadine Tung, Christi J. van Asperen, Ana Vega, Alessandra Viel, Jeroen Vierstraete, Barbara Wappenschmidt, Jeffrey N. Weitzel, Greet Wieme, Sook-Yee Yoon, Kristin K. Zorn, Lesley McGuffog, Michael T. Parsons, Ute Hamann, Mark H. Greene, Judy A. Kirk, Susan L. Neuhausen, Timothy R. Rebbeck, Marc Tischkowitz, Georgia Chenevix-Trench, Antonis C. Antoniou, Eitan Friedman, Laura Ottini

Date Published: 2nd Jul 2020

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Abstract (Expand)

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.

Authors: Helian Feng, Alexander Gusev, Bogdan Pasaniuc, Lang Wu, Jirong Long, Zomoroda Abu-Full, Kristiina Aittomäki, Irene L. Andrulis, Hoda Anton-Culver, Antonis C. Antoniou, Adalgeir Arason, Volker Arndt, Kristan J. Aronson, Banu K. Arun, Ella Asseryanis, Paul L. Auer, Jacopo Azzollini, Judith Balmaña, Rosa B. Barkardottir, Daniel R. Barnes, Daniel Barrowdale, Matthias W. Beckmann, Sabine Behrens, Javier Benitez, Marina Bermisheva, Katarzyna Białkowska, Ana Blanco, Carl Blomqvist, Bram Boeckx, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Bernardo Bonanni, Ake Borg, Hiltrud Brauch, Hermann Brenner, Ignacio Briceno, Annegien Broeks, Thomas Brüning, Barbara Burwinkel, Qiuyin Cai, Trinidad Caldés, Maria A. Caligo, Ian Campbell, Sander Canisius, Daniele Campa, Brian D. Carter, Jonathan Carter, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Hans Christiansen, Wendy K. Chung, Kathleen B. M. Claes, Christine L. Clarke, Fergus J. Couch, Angela Cox, Simon S. Cross, Cezary Cybulski, Kamila Czene, Mary B. Daly, Miguel de La Hoya, Kim de Leeneer, Joe Dennis, Peter Devilee, Orland Diez, Susan M. Domchek, Thilo Dörk, Isabel Dos-Santos-Silva, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Bent Ejlertsen, Carolina Ellberg, Christoph Engel, Mikael Eriksson, Peter A. Fasching, Olivia Fletcher, Henrik Flyger, Florentia Fostira, Eitan Friedman, Lin Fritschi, Debra Frost, Marike Gabrielson, Patricia A. Ganz, Susan M. Gapstur, Judy Garber, Montserrat García-Closas, José A. García-Sáenz, Mia M. Gaudet, Graham G. Giles, Gord Glendon, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Anna González-Neira, Mark H. Greene, Jacek Gronwald, Pascal Guénel, Christopher A. Haiman, Per Hall, Ute Hamann, Christopher Hake, Wei He, Jane Heyworth, Frans B. L. Hogervorst, Antoinette Hollestelle, Maartje J. Hooning, Robert N. Hoover, John L. Hopper, Guanmengqian Huang, Peter J. Hulick, Keith Humphreys, Evgeny N. Imyanitov, Claudine Isaacs, Milena Jakimovska, Anna Jakubowska, Paul James, Ramunas Janavicius, Rachel C. Jankowitz, Esther M. John, Nichola Johnson, Vijai Joseph, Audrey Jung, Beth Y. Karlan, Elza Khusnutdinova, Johanna I. Kiiski, Irene Konstantopoulou, Vessela N. Kristensen, Yael Laitman, Diether Lambrechts, Conxi Lazaro, Dominique Leroux, Goska Leslie, Jenny Lester, Fabienne Lesueur, Noralane Lindor, Sara Lindström, Wing-Yee Lo, Jennifer T. Loud, Jan Lubiński, Enes Makalic, Arto Mannermaa, Mehdi Manoochehri, Siranoush Manoukian, Sara Margolin, John W. M. Martens, Maria E. Martinez, Laura Matricardi, Tabea Maurer, Dimitrios Mavroudis, Lesley McGuffog, Alfons Meindl, Usha Menon, Kyriaki Michailidou, Pooja M. Kapoor, Austin Miller, Marco Montagna, Fernando Moreno, Lidia Moserle, Anna M. Mulligan, Taru A. Muranen, Katherine L. Nathanson, Susan L. Neuhausen, Heli Nevanlinna, Ines Nevelsteen, Finn C. Nielsen, Liene Nikitina-Zake, Kenneth Offit, Edith Olah, Olufunmilayo I. Olopade, Håkan Olsson, Ana Osorio, Janos Papp, Tjoung-Won Park-Simon, Michael T. Parsons, Inge S. Pedersen, Ana Peixoto, Paolo Peterlongo, Julian Peto, Paul D. P. Pharoah, Kelly-Anne Phillips, Dijana Plaseska-Karanfilska, Bruce Poppe, Nisha Pradhan, Karolina Prajzendanc, Nadege Presneau, Kevin Punie, Katri Pylkäs, Paolo Radice, Johanna Rantala, Muhammad Usman Rashid, Gad Rennert, Harvey A. Risch, Mark Robson, Atocha Romero, Emmanouil Saloustros, Dale P. Sandler, Catarina Santos, Elinor J. Sawyer, Marjanka K. Schmidt, Daniel F. Schmidt, Rita K. Schmutzler, Minouk J. Schoemaker, Rodney J. Scott, Priyanka Sharma, Xiao-Ou Shu, Jacques Simard, Christian F. Singer, Anne-Bine Skytte, Penny Soucy, Melissa C. Southey, John J. Spinelli, Amanda B. Spurdle, Jennifer Stone, Anthony J. Swerdlow, William J. Tapper, Jack A. Taylor, Manuel R. Teixeira, Mary Beth Terry, Alex Teulé, Mads Thomassen, Kathrin Thöne, Darcy L. Thull, Marc Tischkowitz, Amanda E. Toland, Rob A. E. M. Tollenaar, Diana Torres, Thérèse Truong, Nadine Tung, Celine M. Vachon, Christi J. van Asperen, Ans M. W. van den Ouweland, Elizabeth J. van Rensburg, Ana Vega, Alessandra Viel, Paula Vieiro-Balo, Qin Wang, Barbara Wappenschmidt, Clarice R. Weinberg, Jeffrey N. Weitzel, Camilla Wendt, Robert Winqvist, Xiaohong R. Yang, Drakoulis Yannoukakos, Argyrios Ziogas, Roger L. Milne, Douglas F. Easton, Georgia Chenevix-Trench, Wei Zheng, Peter Kraft, Xia Jiang

Date Published: 1st Jul 2020

Publication Type: Journal article

Human Diseases: breast cancer

Abstract (Expand)

BACKGROUND AND PURPOSE Periventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study,, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings. METHODS Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC. RESULTS In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (NBEAL), 10q23.1 (TSPAN14/FAM231A), and 10q24.33 (SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 (NOS3) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype. CONCLUSIONS Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.

Authors: Nicola J. Armstrong, Karen A. Mather, Muralidharan Sargurupremraj, Maria J. Knol, Rainer Malik, Claudia L. Satizabal, Lisa R. Yanek, Wei Wen, Vilmundur G. Gudnason, Nicole D. Dueker, Lloyd T. Elliott, Edith Hofer, Joshua Bis, Neda Jahanshad, Shuo Li, Mark A. Logue, Michelle Luciano, Markus Scholz, Albert V. Smith, Stella Trompet, Dina Vojinovic, Rui Xia, Fidel Alfaro-Almagro, David Ames, Najaf Amin, Philippe Amouyel, Alexa S. Beiser, Henry Brodaty, Ian J. Deary, Christine Fennema-Notestine, Piyush G. Gampawar, Rebecca Gottesman, Ludovica Griffanti, Clifford R. Jack, Mark Jenkinson, Jiyang Jiang, Brian G. Kral, John B. Kwok, Leonie Lampe, David C M Liewald, Pauline Maillard, Jonathan Marchini, Mark E. Bastin, Bernard Mazoyer, Lukas Pirpamer, José Rafael Romero, Gennady V. Roshchupkin, Peter R. Schofield, Matthias L. Schroeter, David J. Stott, Anbupalam Thalamuthu, Julian Trollor, Christophe Tzourio, Jeroen van der Grond, Meike W. Vernooij, Veronica A. Witte, Margaret J. Wright, Qiong Yang, Zoe Morris, Siggi Siggurdsson, Bruce Psaty, Arno Villringer, Helena Schmidt, Asta K. Haberg, Cornelia M. van Duijn, J. Wouter Jukema, Martin Dichgans, Ralph L. Sacco, Clinton B. Wright, William S. Kremen, Lewis C. Becker, Paul M. Thompson, Thomas H. Mosley, Joanna M. Wardlaw, M. Arfan Ikram, Hieab H. H. Adams, Sudha Seshadri, Perminder S. Sachdev, Stephen M. Smith, Lenore Launer, William Longstreth, Charles DeCarli, Reinhold Schmidt, Myriam Fornage, Stephanie Debette, Paul A. Nyquist

Date Published: 1st Jul 2020

Publication Type: Journal article

Abstract (Expand)

BACKGROUND: Sharing sensitive data across organizational boundaries is often significantly limited by legal and ethical restrictions. Regulations such as the EU General Data Protection Rules (GDPR) impose strict requirements concerning the protection of personal and privacy sensitive data. Therefore new approaches, such as the Personal Health Train initiative, are emerging to utilize data right in their original repositories, circumventing the need to transfer data. RESULTS: Circumventing limitations of previous systems, this paper proposes a configurable and automated schema extraction and publishing approach, which enables ad-hoc SPARQL query formulation against RDF triple stores without requiring direct access to the private data. The approach is compatible with existing Semantic Web-based technologies and allows for the subsequent execution of such queries in a safe setting under the data provider’s control. Evaluation with four distinct datasets shows that a configurable amount of concise and task-relevant schema, closely describing the structure of the underlying data, was derived, enabling the schema introspection-assisted authoring of SPARQL queries. CONCLUSIONS: Automatically extracting and publishing data schema can enable the introspection-assisted creation of data selection and integration queries. In conjunction with the presented system architecture, this approach can enable reuse of data from private repositories and in settings where agreeing upon a shared schema and encoding a priori is infeasible. As such, it could provide an important step towards reuse of data from previously inaccessible sources and thus towards the proliferation of data-driven methods in the biomedical domain.

Authors: Lars Christoph Gleim, Md Rezaul Karim, Lukas Zimmermann, Oliver Kohlbacher, Holger Stenzhorn, Stefan Decker, Oya Beyan

Date Published: 1st Jul 2020

Publication Type: Journal article

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