Filter and export

Publications

960 Publications visible to you, out of a total of 960
Common variants at the 19p13.1 and ZNF365 loci are associated with ER subtypes of breast cancer and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

BACKGROUND Genome-wide association studies (GWAS) identified variants at 19p13.1 and ZNF365 (10q21.2) as risk factors for breast cancer among BRCA1 and BRCA2 mutation carriers, respectively. We explored …d associations with ovarian cancer and with breast cancer by tumor histopathology for these variants in mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). METHODS Genotyping data for 12,599 BRCA1 and 7,132 BRCA2 mutation carriers from 40 studies were combined. RESULTS We confirmed associations between rs8170 at 19p13.1 and breast cancer risk for BRCA1 mutation carriers [HR, 1.17; 95% confidence interval (CI), 1.07-1.27; P = 7.42 \times 10(-4)] and between rs16917302 at ZNF365 (HR, 0.84; 95% CI, 0.73-0.97; P = 0.017) but not rs311499 at 20q13.3 (HR, 1.11; 95% CI, 0.94-1.31; P = 0.22) and breast cancer risk for BRCA2 mutation carriers. Analyses based on tumor histopathology showed that 19p13 variants were predominantly associated with estrogen receptor (ER)-negative breast cancer for both BRCA1 and BRCA2 mutation carriers, whereas rs16917302 at ZNF365 was mainly associated with ER-positive breast cancer for both BRCA1 and BRCA2 mutation carriers. We also found for the first time that rs67397200 at 19p13.1 was associated with an increased risk of ovarian cancer for BRCA1 (HR, 1.16; 95% CI, 1.05-1.29; P = 3.8 \times 10(-4)) and BRCA2 mutation carriers (HR, 1.30; 95% CI, 1.10-1.52; P = 1.8 \times 10(-3)). CONCLUSIONS 19p13.1 and ZNF365 are susceptibility loci for ovarian cancer and ER subtypes of breast cancer among BRCA1 and BRCA2 mutation carriers. IMPACT These findings can lead to an improved understanding of tumor development and may prove useful for breast and ovarian cancer risk prediction for BRCA1 and BRCA2 mutation carriers.

Authors: Fergus J. Couch, Mia M. Gaudet, Antonis C. Antoniou, Susan J. Ramus, Karoline B. Kuchenbaecker, Penny Soucy, Jonathan Beesley, Xiaoqing Chen, Xianshu Wang, Tomas Kirchhoff, Lesley McGuffog, Daniel Barrowdale, Andrew Lee, Sue Healey, Olga M. Sinilnikova, Irene L. Andrulis, Hilmi Ozcelik, Anna Marie Mulligan, Mads Thomassen, Anne-Marie Gerdes, Uffe Birk Jensen, Anne-Bine Skytte, Torben A. Kruse, Maria A. Caligo, Anna von Wachenfeldt, Gisela Barbany-Bustinza, Niklas Loman, Maria Soller, Hans Ehrencrona, Per Karlsson, Katherine L. Nathanson, Timothy R. Rebbeck, Susan M. Domchek, Ania Jakubowska, Jan Lubinski, Katarzyna Jaworska, Katarzyna Durda, Elzbieta Zlowocka, Tomasz Huzarski, Tomasz Byrski, Jacek Gronwald, Cezary Cybulski, Bohdan Górski, Ana Osorio, Mercedes Durán, María Isabel Tejada, Javier Benitez, Ute Hamann, Frans B. L. Hogervorst, Theo A. van Os, Flora E. van Leeuwen, Hanne E. J. Meijers-Heijboer, Juul Wijnen, Marinus J. Blok, Marleen Kets, Maartje J. Hooning, Rogier A. Oldenburg, Margreet G. E. M. Ausems, Susan Peock, Debra Frost, Steve D. Ellis, Radka Platte, Elena Fineberg, D. Gareth Evans, Chris Jacobs, Rosalind A. Eeles, Julian Adlard, Rosemarie Davidson, Diana M. Eccles, Trevor Cole, Jackie Cook, Joan Paterson, Carole Brewer, Fiona Douglas, Shirley V. Hodgson, Patrick J. Morrison, Lisa Walker, Mary E. Porteous, M. John Kennedy, Lucy E. Side, Betsy Bove, Andrew K. Godwin, Dominique Stoppa-Lyonnet, Marion Fassy-Colcombet, Laurent Castera, François Cornelis, Sylvie Mazoyer, Mélanie Léoné, Nadia Boutry-Kryza, Brigitte Bressac-de Paillerets, Olivier Caron, Pascal Pujol, Isabelle Coupier, Capucine Delnatte, Linda Akloul, Henry T. Lynch, Carrie L. Snyder, Saundra S. Buys, Mary B. Daly, Marybeth Terry, Wendy K. Chung, Esther M. John, Alexander Miron, Melissa C. Southey, John L. Hopper, David E. Goldgar, Christian F. Singer, Christine Rappaport, Muy-Kheng M. Tea, Anneliese Fink-Retter, Thomas v. O. Hansen, Finn C. Nielsen, A\dhalgeir Arason, Joseph Vijai, Sohela Shah, Kara Sarrel, Mark E. Robson, Marion Piedmonte, Kelly Phillips, Jack Basil, Wendy S. Rubinstein, John Boggess, Katie Wakeley, Amanda Ewart-Toland, Marco Montagna, Simona Agata, Evgeny N. Imyanitov, Claudine Isaacs, Ramunas Janavicius, Conxi Lazaro, Ignacio Blanco, Lidia Feliubadalo, Joan Brunet, Simon A. Gayther, Paul P. D. Pharoah, Kunle O. Odunsi, Beth Y. Karlan, Christine S. Walsh, Edith Olah, Soo Hwang Teo, Patricia A. Ganz, Mary S. Beattie, Elizabeth J. van Rensburg, Cecelia M. Dorfling, Orland Diez, Ava Kwong, Rita K. Schmutzler, Barbara Wappenschmidt, Christoph Engel, Alfons Meindl, Nina Ditsch, Norbert Arnold, Simone Heidemann, Dieter Niederacher, Sabine Preisler-Adams, Dorothea Gadzicki, Raymonda Varon-Mateeva, Helmut Deissler, Andrea Gehrig, Christian Sutter, Karin Kast, Britta Fiebig, Wolfram Heinritz, Trinidad Caldes, Miguel de La Hoya, Taru A. Muranen, Heli Nevanlinna, Marc D. Tischkowitz, Amanda B. Spurdle, Susan L. Neuhausen, Yuan Chun Ding, Noralane M. Lindor, Zachary Fredericksen, V. Shane Pankratz, Paolo Peterlongo, Siranoush Manoukian, Bernard Peissel, Daniela Zaffaroni, Monica Barile, Loris Bernard, Alessandra Viel, Giuseppe Giannini, Liliana Varesco, Paolo Radice, Mark H. Greene, Phuong L. Mai, Douglas F. Easton, Georgia Chenevix-Trench, Kenneth Offit, Jacques Simard

Date Published: 28th Mar 2012

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Classifying prostate cancer malignancy by quantitative histomorphometry.
ProstataCA

Abstract (Expand)

PURPOSE: Prostate cancer is routinely graded according to the Gleason grading scheme. This scheme is predominantly based on the textural appearance of aberrant glandular structures. Gleason grade is … difficult to standardize and often leads to discussion due to interrater and intrarater disagreement. Thus, we investigated whether digital image based automated quantitative histomorphometry could be used to achieve a more standardized, reproducible classification outcome. MATERIALS AND METHODS: In a proof of principle study we developed a method to evaluate digitized histological images of single prostate cancer regions in hematoxylin and eosin stained sections. Preprocessed color images were subjected to color deconvolution, followed by the binarization of obtained hematoxylin related image channels. Highlighted neoplastic epithelial gland related objects were morphometrically assessed by a classifier based on 2 calculated quantitative and objective geometric measures, that is inverse solidity and inverse compactness. The procedure was then applied to the prostate cancer probes of 125 patients. Each probe was independently classified for Gleason grade 3, 4 or 5 by an experienced pathologist blinded to image analysis outcome. RESULTS: Together inverse compactness and inverse solidity were adequate discriminatory features for a powerful classifier that distinguished Gleason grade 3 from grade 4/5 histology. The classifier was robust on sensitivity analysis. CONCLUSIONS: Results suggest that quantitative and interpretable measures can be obtained from image based analysis, permitting algorithmic differentiation of prostate Gleason grades. The method must be validated in a large independent series of specimens.

Authors: M. Loeffler, L. Greulich, P. Scheibe, P. Kahl, Z. Shaikhibrahim, U. D. Braumann, J. P. Kuska, N. Wernert

Date Published: 20th Mar 2012

Publication Type: Not specified

Human Diseases: prostate cancer

Association of death receptor 4 variant (683A C) with ovarian cancer risk in BRCA1 mutation carriers
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

Dysregulation of apoptosis plays an important role in carcinogenesis. Therefore, apoptosis-associated genes like the death receptor 4 (DR4, TRAIL-R1) are interesting candidates for modifying the … penetrance of breast and ovarian cancer in carriers of BRCA1 and BRCA2 mutations. The DR-4 haplotype 626C-683C [626C \textgreater G, Thr209Arg (rs4871857) and 683A \textgreater C, Glu228Ala (rs17088993)] has recently been linked to an increased risk of breast cancer. To evaluate whether DR4 626C \textgreater G or DR4 683A \textgreater C modifies the risk of breast or ovarian cancer in carriers of BRCA1 and BRCA2 mutations, we undertook a national multicenter study including data of 840 carriers of breast cancer gene (BRCA) mutations. DNA samples were collected from 12 German research centers between 1996 and 2005 and were genotyped by the Taqman allelic discrimination assay. The association between genotypes and incidence of breast or ovarian cancer data was evaluated using a Cox proportional hazards regression model. We found evidence for a significant association of DR4 683A \textgreater C with a higher risk for ovarian cancer in carriers of BRCA1 mutations [n = 557, hazard ratio 1.78 (1.24-2.55), p = 0.009]. Our results thus indicate that the DR4 683A \textgreater C variant modifies the risk of ovarian cancer in carriers of BRCA1 mutations.

Authors: Michelle G. Dick, Beatrix Versmold, Christoph Engel, Alfons Meindl, Norbert Arnold, Raymonda Varon-Mateeva, Christian Sutter, Dieter Niederacher, Helmut Deissler, Sabine Preisler-Adams, Karin Kast, Dieter Schäfer, Dorothea Gadzicki, Wolfram Heinritz, Barbara Wappenschmidt, Rita K. Schmutzler

Date Published: 15th Mar 2012

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Suitability of infrared microspectroscopic imaging for histopathology of the uterine cervix.
ProstataCA

Abstract (Expand)

AIMS: Infrared microspectroscopy (IR-MSP) has been proposed for automated histological tissue differentiation of unstained specimens based on chemical analysis of cell and extracellular constituents. … This study aimed to determine the accuracy of IR-MSP-based histopathology of cervical carcinoma sections with complex tissue architecture under practically relevant testing conditions. METHODS AND RESULTS: In total, 46 regions of interest, covering an area of almost 50 mm(2) on sections derived from paraffin-embedded tissue of radical hysterectomy specimens, were analysed by IR-MSP (nominal resolution ~4.2 mum). More than 2.8 million pixel spectra that were processed using fuzzy c-means clustering followed by hierarchical cluster analysis permitted image segmentation regarding different biochemical properties. Linear image registration was applied to compare these segmentation results with manual labelling on haematoxylin and eosin-stained references (resolution ~0.7 mum). For recognition of nine tissue types, sensitivities were 42-91% and specificities were 79-100%, mostly being affected by peritumoral inflammatory responses. Algorithmic variation of the outline of dysplasia and carcinoma revealed a spatial preference of false values in tissue transition areas. CONCLUSIONS: This imaging technique has potential as a new method for tissue characterization; however, the recognition accuracy does not justify a pathologist-independent tissue analysis, and the application is only possible in combination with concomitant conventional histopathology.

Authors: J. Einenkel, U. D. Braumann, W. Steller, H. Binder, L. C. Horn

Date Published: 1st Mar 2012

Publication Type: Not specified

Human Diseases: cervical cancer

Patient age at diagnosis is associated with the molecular characteristics of diffuse large B-cell lymphoma.
MMML - Molecular mechanisms in malignant lymphoma

Abstract (Expand)

Diffuse large B-cell lymphoma is the most frequent type of B-cell lymphoma in adult patients but also occurs in children. Patients are currently assigned to therapy regimens based on arbitrarily chosen … age limits only (eg, 18 or 60 years) and not biologically justified limits. A total of 364 diffuse large B-cell lymphomas and related mature aggressive B-cell lymphomas other than Burkitt lymphoma from all age groups were analyzed by comprehensive molecular profiling. The probability of several biologic features previously reported to be associated with poor prognosis in diffuse large B-cell lymphoma, such as ABC subtype, BCL2 expression, or cytogenetic complexity, increases with age at diagnosis. Similarly, various genetic features, such as IRF4 translocations, gains in 1q21, 18q21, 7p22, and 7q21, as well as changes in 3q27, including gains and translocations affecting the BCL6 locus, are significantly associated with patient age, but no cut-offs between age groups could be defined. If age was incorporated in multivariate analyses, genetic complexity lost its prognostic significance, whereas the prognostic impact of ABC subtype and age were additive. Our data indicate that aging is a major determinant of lymphoma biology. They challenge current concepts regarding both prognostic biomarkers and treatment stratification based on strict age cut-offs.

Authors: W. Klapper, M. Kreuz, C. W. Kohler, B. Burkhardt, M. Szczepanowski, I. Salaverria, M. Hummel, M. Loeffler, S. Pellissery, W. Woessmann, C. Schwanen, L. Trumper, S. Wessendorf, R. Spang, D. Hasenclever, R. Siebert

Date Published: 23rd Feb 2012

Publication Type: Not specified

Human Diseases: diffuse large B-cell lymphoma

Common variants at 12p11, 12q24, 9p21, 9q31.2 and in ZNF365 are associated with breast cancer risk for BRCA1 and/or BRCA2 mutation carriers
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

INTRODUCTION Several common alleles have been shown to be associated with breast and/or ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. Recent genome-wide association studies of breast cancer …r have identified eight additional breast cancer susceptibility loci: rs1011970 (9p21, CDKN2A/B), rs10995190 (ZNF365), rs704010 (ZMIZ1), rs2380205 (10p15), rs614367 (11q13), rs1292011 (12q24), rs10771399 (12p11 near PTHLH) and rs865686 (9q31.2). METHODS To evaluate whether these single nucleotide polymorphisms (SNPs) are associated with breast cancer risk for BRCA1 and BRCA2 carriers, we genotyped these SNPs in 12,599 BRCA1 and 7,132 BRCA2 mutation carriers and analysed the associations with breast cancer risk within a retrospective likelihood framework. RESULTS Only SNP rs10771399 near PTHLH was associated with breast cancer risk for BRCA1 mutation carriers (per-allele hazard ratio (HR) = 0.87, 95% CI: 0.81 to 0.94, P-trend = 3 \times 10-4). The association was restricted to mutations proven or predicted to lead to absence of protein expression (HR = 0.82, 95% CI: 0.74 to 0.90, P-trend = 3.1 \times 10-5, P-difference = 0.03). Four SNPs were associated with the risk of breast cancer for BRCA2 mutation carriers: rs10995190, P-trend = 0.015; rs1011970, P-trend = 0.048; rs865686, 2df-P = 0.007; rs1292011 2df-P = 0.03. rs10771399 (PTHLH) was predominantly associated with estrogen receptor (ER)-negative breast cancer for BRCA1 mutation carriers (HR = 0.81, 95% CI: 0.74 to 0.90, P-trend = 4 \times 10-5) and there was marginal evidence of association with ER-negative breast cancer for BRCA2 mutation carriers (HR = 0.78, 95% CI: 0.62 to 1.00, P-trend = 0.049). CONCLUSIONS The present findings, in combination with previously identified modifiers of risk, will ultimately lead to more accurate risk prediction and an improved understanding of the disease etiology in BRCA1 and BRCA2 mutation carriers.

Authors: Antonis C. Antoniou, Karoline B. Kuchenbaecker, Penny Soucy, Jonathan Beesley, Xiaoqing Chen, Lesley McGuffog, Andrew Lee, Daniel Barrowdale, Sue Healey, Olga M. Sinilnikova, Maria A. Caligo, Niklas Loman, Katja Harbst, Annika Lindblom, Brita Arver, Richard Rosenquist, Per Karlsson, Kate Nathanson, Susan Domchek, Tim Rebbeck, Anna Jakubowska, Jan Lubinski, Katarzyna Jaworska, Katarzyna Durda, Elżbieta Złowowcka-Perłowska, Ana Osorio, Mercedes Durán, Raquel Andrés, Javier Benítez, Ute Hamann, Frans B. Hogervorst, Theo A. van Os, Senno Verhoef, Hanne E. J. Meijers-Heijboer, Juul Wijnen, Encarna B. Gómez Garcia, Marjolijn J. Ligtenberg, Mieke Kriege, J. Margriet Collée, Margreet G. E. M. Ausems, Jan C. Oosterwijk, Susan Peock, Debra Frost, Steve D. Ellis, Radka Platte, Elena Fineberg, D. Gareth Evans, Fiona Lalloo, Chris Jacobs, Ros Eeles, Julian Adlard, Rosemarie Davidson, Trevor Cole, Jackie Cook, Joan Paterson, Fiona Douglas, Carole Brewer, Shirley Hodgson, Patrick J. Morrison, Lisa Walker, Mark T. Rogers, Alan Donaldson, Huw Dorkins, Andrew K. Godwin, Betsy Bove, Dominique Stoppa-Lyonnet, Claude Houdayer, Bruno Buecher, Antoine de Pauw, Sylvie Mazoyer, Alain Calender, Mélanie Léoné, Brigitte Bressac-de Paillerets, Olivier Caron, Hagay Sobol, Marc Frenay, Fabienne Prieur, Sandra U. Ferrer, Isabelle Mortemousque, Saundra Buys, Mary Daly, Alexander Miron, Mary U. Terry, John L. Hopper, Esther M. John, Melissa Southey, David Goldgar, Christian F. Singer, Anneliese Fink-Retter, Muy-Kheng Tea, Daphne U. Kaulich, Thomas V. Hansen, Finn C. Nielsen, Rosa B. Barkardottir, Mia Gaudet, Tomas Kirchhoff, Vijai Joseph, Ana Dutra-Clarke, Kenneth Offit, Marion Piedmonte, Judy Kirk, David Cohn, Jean Hurteau, John Byron, James Fiorica, Amanda E. Toland, Marco Montagna, Cristina Oliani, Evgeny Imyanitov, Claudine Isaacs, Laima Tihomirova, Ignacio Blanco, Conxi Lazaro, Alex Teulé, J. Del Valle, Simon A. Gayther, Kunle Odunsi, Jenny Gross, Beth Y. Karlan, Edith Olah, Soo-Hwang Teo, Patricia A. Ganz, Mary S. Beattie, Cecelia M. Dorfling, Elizabeth U. van Rensburg, Orland Diez, Ava Kwong, Rita K. Schmutzler, Barbara Wappenschmidt, Christoph Engel, Alfons Meindl, Nina Ditsch, Norbert Arnold, Simone Heidemann, Dieter Niederacher, Sabine Preisler-Adams, Dorothea Gadzicki, Raymonda Varon-Mateeva, Helmut Deissler, Andrea Gehrig, Christian Sutter, Karin Kast, Britta Fiebig, Dieter Schäfer, Trinidad Caldes, Miguel de La Hoya, Heli Nevanlinna, Taru A. Muranen, Bernard Lespérance, Amanda B. Spurdle, Susan L. Neuhausen, Yuan C. Ding, Xianshu Wang, Zachary Fredericksen, Vernon S. Pankratz, Noralane M. Lindor, Paolo Peterlongo, Siranoush Manoukian, Bernard Peissel, Daniela Zaffaroni, Bernardo Bonanni, Loris Bernard, Riccardo Dolcetti, Laura Papi, Laura Ottini, Paolo Radice, Mark H. Greene, Jennifer T. Loud, Irene L. Andrulis, Hilmi Ozcelik, Anna U. Mulligan, Gord Glendon, Mads Thomassen, Anne-Marie Gerdes, Uffe B. Jensen, Anne-Bine Skytte, Torben A. Kruse, Georgia Chenevix-Trench, Fergus J. Couch, Jacques Simard, Douglas F. Easton

Date Published: 1st Feb 2012

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Imaging genetics of FOXP2 in dyslexia
Genetical Statistics and Systems Biology

Abstract (Expand)

Dyslexia is a developmental disorder characterised by extensive difficulties in the acquisition of reading or spelling. Genetic influence is estimated at 50-70%. However, the link between genetic … variants and phenotypic deficits is largely unknown. Our aim was to investigate a role of genetic variants of FOXP2, a prominent speech and language gene, in dyslexia using imaging genetics. This technique combines functional magnetic resonance imaging (fMRI) and genetics to investigate relevance of genetic variants on brain activation. To our knowledge, this represents the first usage of fMRI-based imaging genetics in dyslexia. In an initial case/control study (n = 245) for prioritisation of FOXP2 polymorphisms for later use in imaging genetics, nine SNPs were selected. A non-synonymously coding mutation involved in verbal dyspraxia was also investigated. SNP rs12533005 showed nominally significant association with dyslexia (genotype GG odds ratio recessive model = 2.1 (95% confidence interval 1.1-3.9), P = 0.016). A correlated SNP was associated with altered expression of FOXP2 in vivo in human hippocampal tissue. Therefore, influence of the rs12533005-G risk variant on brain activity was studied. fMRI revealed a significant main effect for the factor ’genetic risk’ in a temporo-parietal area involved in phonological processing as well as a significant interaction effect between the factors ’disorder’ and ’genetic risk’ in activation of inferior frontal brain areas. Hence, our data may hint at a role of FOXP2 genetic variants in dyslexia-specific brain activation and demonstrate use of imaging genetics in dyslexia research. Dyslexia is a developmental disorder characterised by extensive difficulties in the acquisition of reading or spelling. Genetic influence is estimated at 50-70%. However, the link between genetic variants and phenotypic deficits is largely unknown. Our aim was to investigate a role of genetic variants of FOXP2, a prominent speech and language gene, in dyslexia using imaging genetics. This technique combines functional magnetic resonance imaging (fMRI) and genetics to investigate relevance of genetic variants on brain activation. To our knowledge, this represents the first usage of fMRI-based imaging genetics in dyslexia. In an initial case/control study (n = 245) for prioritisation of FOXP2 polymorphisms for later use in imaging genetics, nine SNPs were selected. A non-synonymously coding mutation involved in verbal dyspraxia was also investigated. SNP rs12533005 showed nominally significant association with dyslexia (genotype GG odds ratio recessive model = 2.1 (95% confidence interval 1.1-3.9), P = 0.016). A correlated SNP was associated with altered expression of FOXP2 in vivo in human hippocampal tissue. Therefore, influence of the rs12533005-G risk variant on brain activity was studied. fMRI revealed a significant main effect for the factor ’genetic risk’ in a temporo-parietal area involved in phonological processing as well as a significant interaction effect between the factors ’disorder’ and ’genetic risk’ in activation of inferior frontal brain areas. Hence, our data may hint at a role of FOXP2 genetic variants in dyslexia-specific brain activation and demonstrate use of imaging genetics in dyslexia research.

Authors: Arndt Wilcke, Carolin Ligges, Jana Burkhardt, Michael Alexander, Christiane Wolf, Elfi Quente, Peter Ahnert, Per Hoffmann, Albert Becker, Bertram Müller-Myhsok, Sven Cichon, Johannes Boltze, Holger Kirsten

Date Published: 1st Feb 2012

Publication Type: Journal article

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