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An integrative web platform for user-friendly application of risk prediction models in hereditary cancer predisposition
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

Background and Objective: Predicting individual mutation and cancer risks is essential to assist genetic counsellors in clinical decision making for patients with a hereditary cancer predisposition. … Worldwide a variety of statistical models and empirical data for risk prediction have been developed and published for hereditary breast and ovarian cancer (HBOC), and hereditary non-polyposis colorectal cancer (HNPCC / Lynch syndrome, LS). However, only few models have so far been implemented in convenient and easy-to-use computer applications. We therefore aimed to develop user-friendly applications of selected HBOC and LS risk prediction models, and to make them available through the "Leipzig Health Atlas" (LHA), a web-based multifunctional platform to share research data, novel ontologies, models and software tools with the medical and scientific community. LHA is a project funded within the BMBF initiative "i:DSem – Integrative data semantics in system medicine". Methods and Results: We selected a total of six statistical models and empirical datasets relevant for HBOC and LS: 1) the Manchester Scoring System, 2) the "Mutation Frequency Explorer" of the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC), 3) an extended version of the Claus model, 4) MMRpredict, 5) PREMM1,2,6, and 6) PREMM5. The Manchester Scoring System allows calculation of BRCA1/2 mutation probabilities based on aggregated family history. The "Mutation Frequency Explorer" allows flexible assessment of mutation risks in BRCA1/2 and other genes for different sets of familial cancer histories based on a large dataset from the GC-HBOC. The extended Claus model (as implemented in the commercial predigree drawing software Cyrillic 2.1.3, which is no longer supported and no longer works on newer operating systems) predicts both mutation and breast cancer risks based on structured pedigree data. MMRpredict, PREMM 1,2,6, and PREMM 5 predict mutation risks in mismatch repair genes for patients from families suspected of having LS. All models were implemented using the statistical software "R" and the R-package "Shiny". "Shiny" allows the development of interactive applications by incorporating "R" with HTML and other web technologies. The Shiny apps are accessible on the website of the "Leipzig Health Atlas" (https://www.health-atlas.de) for registered researchers and genetic counselors. Conclusions: The risk prediction apps allow convenient calculation of mutation or cancer risks for an advice-seeking individual based on pedigree data or aggregated information on the familial cancer history. Target users should be specialized health professionals (physicians and genetic counselors) and scientists to ensure correct handling of the tools and careful interpretation of results.

Authors: Silke Zachariae, Sebastian Stäubert, C. Fischer, Markus Löffler, Christoph Engel

Date Published: 8th Mar 2019

Publication Type: InProceedings

Human Diseases: hereditary breast ovarian cancer syndrome, Lynch syndrome, colorectal cancer

Modeling individual time courses of thrombopoiesis during multi-cyclic chemotherapy.
Genetical Statistics and Systems Biology, HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles

Abstract (Expand)

BACKGROUND: Thrombocytopenia is a major side-effect of cytotoxic cancer therapies. The aim of precision medicine is to develop therapy modifications accounting for the individual's risk. … METHODOLOGY/PRINCIPLE FINDINGS: To solve this task, we develop an individualized bio-mechanistic model of the dynamics of bone marrow thrombopoiesis, circulating platelets and therapy effects thereon. Comprehensive biological knowledge regarding cell differentiation, amplification, apoptosis rates, transition times and corresponding regulations are translated into ordinary differential equations. A model of osteoblast/osteoclast interactions was incorporated to mechanistically describe bone marrow support of quiescent cell stages. Thrombopoietin (TPO) as a major regulator is explicitly modelled including pharmacokinetics and-dynamics of TPO injections. Effects of cytotoxic drugs are modelled by transient depletions of proliferating cells. To calibrate the model, we used population data from the literature and close-meshed individual data of N = 135 high-grade non-Hodgkin's lymphoma patients treated with CHOP-like chemotherapies. To limit the number of free parameters, several parsimony assumptions were derived from biological data and tested via Likelihood methods. Heterogeneity of patients was explained by a few model parameters. The over-fitting issue of individual parameter estimation was successfully dealt with a virtual participation of each patient in population-based experiments. The model qualitatively and quantitatively explains a number of biological observations such as the role of osteoblasts in explaining long-term toxic effects, megakaryocyte-mediated feedback on stem cells, bi-phasic stimulation of thrombopoiesis by TPO, dynamics of megakaryocyte ploidies and non-exponential platelet degradation. Almost all individual time series could be described with high precision. We demonstrated how the model can be used to provide predictions regarding individual therapy adaptations. CONCLUSIONS: We propose a mechanistic thrombopoiesis model of unprecedented comprehensiveness in both, biological mechanisms considered and experimental data sets explained. Our innovative method of parameter estimation allows robust determinations of individual parameter settings facilitating the development of individual treatment adaptations during chemotherapy.

Authors: Y. Kheifetz, M. Scholz

Date Published: 7th Mar 2019

Publication Type: Not specified

Human Diseases: blood platelet disease

Prevalence of moderately increased albuminuria among individuals with normal HbA1c level but impaired glucose tolerance: Results from the LIFE-Adult-Study.
LIFE Adult

Abstract (Expand)

Aims: Diabetes screening strategies using glycated haemoglobin (HbA1c) as first-instance diagnostic parameter may cause failure to detect individuals with abnormal glucose regulation and possible signs … of microvascular complications despite "rule-out" HbA1c levels. This cross-sectional study examined the diagnostic performance of HbA1c in relation to fasting and two-hour postload plasma glucose (FPG/2 h-PG), and investigated whether individuals with normal HbA1c but abnormal FPG/2 h-PG have a higher prevalence of moderately increased albuminuria as possible sign of early stage kidney damage. Methods: A total of 2695 individuals (age 40-79 years, 48% men) without prior diagnosis of diabetes and complete measurement of HbA1c, FPG, 2 h-PG and urine albumin-creatinine ratio (UACR) were taken from a large population-based epidemiological study in the City of Leipzig, Germany. Results: A total of 2439 individuals (90.5%, 95% CI: 89.4-91.6) had normal HbA1c levels, <39 mmol/mol (<5.7%), while 234 (8.7%, 95% CI: 7.7-9.8) had prediabetes, HbA1c >/=39 and <48 mmol/mol (>/=5.7 and <6.5%), and 22 (0.8%, 95% CI: 0.5-1.2) had diabetes, HbA1c >/=48 mmol/mol (>/=6.5%), according to HbA1c. Among individuals with normal HbA1c, 35.6% (95% CI: 33.7-37.5) had impaired fasting glucose or impaired glucose tolerance and 1.8% (95% CI: 1.4-2.4) had diabetes according to FPG/2 h-PG. Individuals with normal HbA1c but prediabetic or diabetic FPG/2 h-PG had a significantly higher prevalence of moderately increased albuminuria (9.4%, 95% CI: 7.6-11.5 and 13.3%, 95% CI: 5.8-25.4, respectively) than individuals with normal HbA1c and normal FPG/2 h-PG (3.9%, 95% CI: 3.0-5.0). Conclusions: The prevalence of prediabetes according to FPG/2 h-PG among individuals with normal HbA1c is considerably high, and the prevalence of moderately increased albuminuria in this group is significantly elevated. Risk factors for diabetes such as age, gender and BMI may help to better identify this at-risk group.

Authors: M. Zivkovic, A. Tonjes, R. Baber, K. Wirkner, M. Loeffler, C. Engel

Date Published: 1st Mar 2019

Publication Type: Not specified

Human Diseases: glucose metabolism disease

Genome-wide association study of germline variants and breast cancer-specific mortality
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

BACKGROUND We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. METHODS Meta-analyses included summary estimates …tes based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP). RESULTS We did not find any variant associated with breast cancer-specific mortality at P \textless 5 \times 10-8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 \times 10-7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 \times 10-7, HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster. CONCLUSIONS We uncovered germline variants on chromosome 7 at BFDP \textless 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.

Authors: Maria Escala-Garcia, Qi Guo, Thilo Dörk, Sander Canisius, Renske Keeman, Joe Dennis, Jonathan Beesley, Julie Lecarpentier, Manjeet K. Bolla, Qin Wang, Jean Abraham, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Paul L. Auer, Matthias W. Beckmann, Sabine Behrens, Javier Benitez, Marina Bermisheva, Leslie Bernstein, Carl Blomqvist, Bram Boeckx, Stig E. Bojesen, Bernardo Bonanni, Anne-Lise Børresen-Dale, Hiltrud Brauch, Hermann Brenner, Adam Brentnall, Louise Brinton, Per Broberg, Ian W. Brock, Sara Y. Brucker, Barbara Burwinkel, Carlos Caldas, Trinidad Caldés, Daniele Campa, Federico Canzian, Angel Carracedo, Brian D. Carter, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Georgia Chenevix-Trench, Ting-Yuan David Cheng, Suet-Feung Chin, Christine L. Clarke, Emilie Cordina-Duverger, Fergus J. Couch, David G. Cox, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Peter Devilee, Janet A. Dunn, Alison M. Dunning, Lorraine Durcan, Miriam Dwek, Helena M. Earl, Arif B. Ekici, A. Heather Eliassen, Carolina Ellberg, Christoph Engel, Mikael Eriksson, D. Gareth Evans, Jonine Figueroa, Dieter Flesch-Janys, Henrik Flyger, Marike Gabrielson, Manuela Gago-Dominguez, Eva Galle, Susan M. Gapstur, Montserrat García-Closas, José A. García-Sáenz, Mia M. Gaudet, Angela George, Vassilios Georgoulias, Graham G. Giles, Gord Glendon, David E. Goldgar, Anna González-Neira, Grethe I. Grenaker Alnæs, Mervi Grip, Pascal Guénel, Lothar Haeberle, Eric Hahnen, Christopher A. Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Susan Hankinson, Elaine F. Harkness, Patricia A. Harrington, Steven N. Hart, Jaana M. Hartikainen, Alexander Hein, Peter Hillemanns, Louise Hiller, Bernd Holleczek, Antoinette Hollestelle, Maartje J. Hooning, Robert N. Hoover, John L. Hopper, Anthony Howell, Guanmengqian Huang, Keith Humphreys, David J. Hunter, Wolfgang Janni, Esther M. John, Michael E. Jones, Arja Jukkola-Vuorinen, Audrey Jung, Rudolf Kaaks, Maria Kabisch, Katarzyna Kaczmarek, Michael J. Kerin, Sofia Khan, Elza Khusnutdinova, Johanna I. Kiiski, Cari M. Kitahara, Julia A. Knight, Yon-Dschun Ko, Linetta B. Koppert, Veli-Matti Kosma, Peter Kraft, Vessela N. Kristensen, Ute Krüger, Tabea Kühl, Diether Lambrechts, Loic Le Marchand, Eunjung Lee, Flavio Lejbkowicz, Lian Li, Annika Lindblom, Sara Lindström, Martha Linet, Jolanta Lissowska, Wing-Yee Lo, Sibylle Loibl, Jan Lubiński, Michael P. Lux, Robert J. MacInnis, Melanie Maierthaler, Tom Maishman, Enes Makalic, Arto Mannermaa, Mehdi Manoochehri, Siranoush Manoukian, Sara Margolin, Maria Elena Martinez, Dimitrios Mavroudis, Catriona McLean, Alfons Meindl, Pooja Middha, Nicola Miller, Roger L. Milne, Fernando Moreno, Anna Marie Mulligan, Claire Mulot, Rami Nassir, Susan L. Neuhausen, William T. Newman, Sune F. Nielsen, Børge G. Nordestgaard, Aaron Norman, Håkan Olsson, Nick Orr, V. Shane Pankratz, Tjoung-Won Park-Simon, Jose I. A. Perez, Clara Pérez-Barrios, Paolo Peterlongo, Christos Petridis, Mila Pinchev, Karoliona Prajzendanc, Ross Prentice, Nadege Presneau, Darya Prokofieva, Katri Pylkäs, Brigitte Rack, Paolo Radice, Dhanya Ramachandran, Gadi Rennert, Hedy S. Rennert, Valerie Rhenius, Atocha Romero, Rebecca Roylance, Emmanouil Saloustros, Elinor J. Sawyer, Daniel F. Schmidt, Rita K. Schmutzler, Andreas Schneeweiss, Minouk J. Schoemaker, Fredrick Schumacher, Lukas Schwentner, Rodney J. Scott, Christopher Scott, Caroline Seynaeve, Mitul Shah, Jacques Simard, Ann Smeets, Christof Sohn, Melissa C. Southey, Anthony J. Swerdlow, Aline Talhouk, Rulla M. Tamimi, William J. Tapper, Manuel R. Teixeira, Maria Tengström, Mary Beth Terry, Kathrin Thöne, Rob A. E. M. Tollenaar, Ian Tomlinson, Diana Torres, Thérèse Truong, Constance Turman, Clare Turnbull, Hans-Ulrich Ulmer, Michael Untch, Celine Vachon, Christi J. van Asperen, Ans M. W. van den Ouweland, Elke M. van Veen, Camilla Wendt, Alice S. Whittemore, Walter Willett, Robert Winqvist, Alicja Wolk, Xiaohong R. Yang, Yan Zhang, Douglas F. Easton, Peter A. Fasching, Heli Nevanlinna, Diana M. Eccles, Paul D. P. Pharoah, Marjanka K. Schmidt

Date Published: 1st Mar 2019

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Genome-wide association study identifies an acute myeloid leukemia susceptibility locus near BICRA
Genetical Statistics and Systems Biology

Abstract

Not specified

Authors: Christopher J. Walker, Christopher C. Oakes, Luke K. Genutis, Brian Giacopelli, Sandya Liyanarachchi, Deedra Nicolet, Ann-Kathrin Eisfeld, Markus Scholz, Pamela Brock, Jessica Kohlschmidt, Krzysztof Mrózek, Marius Bill, Andrew J. Carroll, Jonathan E. Kolitz, Bayard L. Powell, Eunice S. Wang, Dietger W. Niederwieser, Richard M. Stone, John C. Byrd, Sebastian Schwind, Albert de La Chapelle, Clara D. Bloomfield

Date Published: 1st Mar 2019

Publication Type: Journal article

Association of Human FOS Promoter Variants with the Occurrence of Knee-Osteoarthritis in a Case Control Association Study
Genetical Statistics and Systems Biology

Abstract (Expand)

Our aim was to analyse (i) the presence of single nucleotide polymorphisms (SNPs) in the JUN and FOS core promoters in patients with rheumatoid arthritis (RA), knee-osteoarthritis (OA), and normal … controls (NC); (ii) their functional influence on JUN/FOS transcription levels; and (iii) their associations with the occurrence of RA or knee-OA. JUN and FOS promoter SNPs were identified in an initial screening population using the Non-Isotopic RNase Cleavage Assay (NIRCA); their functional influence was analysed using reporter gene assays. Genotyping was done in RA (n = 298), knee-OA (n = 277), and NC (n = 484) samples. For replication, significant associations were validated in a Finnish cohort (OA: n = 72, NC: n = 548). Initially, two SNPs were detected in the JUN promoter and two additional SNPs in the FOS promoter in perfect linkage disequilibrium (LD). JUN promoter SNP rs4647009 caused significant downregulation of reporter gene expression, whereas reporter gene expression was significantly upregulated in the presence of the FOS promoter SNPs. The homozygous genotype of FOS promoter SNPs showed an association with the susceptibility for knee-OA (odds ratio (OR) 2.12, 95% confidence interval (CI) 1.2^-3.7, p = 0.0086). This association was successfully replicated in the Finnish Health 2000 study cohort (allelic OR 1.72, 95% CI 1.2^-2.5, p = 0.006). FOS Promoter variants may represent relevant susceptibility markers for knee-OA.

Authors: René Huber, Holger Kirsten, Annu Näkki, Dirk Pohlers, Hansjörg Thude, Thorsten Eidner, Matthias Heinig, Korbinian Brand, Peter Ahnert, Raimund W. Kinne

Date Published: 1st Mar 2019

Publication Type: Journal article

Towards customer-induced service orchestration - requirements for the next step of customer orientation
Management of health information systems

Abstract

Not specified

Authors: Rainer Alt, Jan Fabian Ehmke, Reinhold Haux, Tino Henke, Dirk Christian Mattfeld, Andreas Oberweis, Barbara Paech, Alfred Winter

Date Published: 1st Mar 2019

Publication Type: Journal article

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