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188 Publications visible to you, out of a total of 188
Markov State Modelling of Disease Courses and Mortality Risks of Patients with Community-Acquired Pneumonia
Genetical Statistics and Systems Biology

Abstract (Expand)

Community-acquired pneumonia (CAP) is one of the most frequent infectious diseases worldwide, with high lethality. Risk evaluation is well established at hospital admission, and re-evaluation is advised … for patients at higher risk. However, severe disease courses may develop from all levels of severity. We propose a stochastic continuous-time Markov model describing daily development of time courses of CAP severity. Disease states were defined based on the Sequential Organ Failure Assessment (SOFA) score. Model calibration was based on longitudinal data from 2838 patients with a primary diagnosis of CAP from four clinical studies (PROGRESS, MAXSEP, SISPCT, VISEP). We categorized CAP severity into five disease states and estimated transition probabilities for CAP progression between these states and corresponding sojourn times. Good agreement between model predictions and clinical data was observed. Time courses of mortality were correctly predicted for up to 28 days, including validation with patient data not used for model calibration. We conclude that CAP disease course follows a Markov process, suggesting the necessity of daily monitoring and re-evaluation of patient’s risk. Our model can be used for regular updates of risk assessments of patients and could improve the design of clinical trials by estimating transition rates for different risk groups.

Authors: Jens Przybilla, Peter Ahnert, Holger Bogatsch, Frank Bloos, Frank M. Brunkhorst, Critical Care Trials Group SepNet, Study Group Progress, Michael Bauer, Markus Loeffler, Martin Witzenrath, Norbert Suttorp, Markus Scholz

Date Published: 1st Feb 2020

Publication Type: Journal article

MB-COMT promoter DNA methylation is associated with working-memory processing in schizophrenia patients and healthy controls
Genetical Statistics and Systems Biology

Abstract (Expand)

Many genetic studies report mixed results both for the associations between COMT polymorphisms and schizophrenia and for the effects of COMT variants on common intermediate phenotypes of the disorder. … Reasons for this may include small genetic effect sizes and the modulation of environmental influences. To improve our understanding of the role of COMT in the disease etiology, we investigated the effect of DNA methylation in the MB-COMT promoter on neural activity in the dorsolateral prefrontal cortex during working memory processing as measured by fMRI - an intermediate phenotype for schizophrenia. Imaging and epigenetic data were measured in 102 healthy controls and 82 schizophrenia patients of the Mind Clinical Imaging Consortium (MCIC) study of schizophrenia. Neural activity during the Sternberg Item Recognition Paradigm was acquired with either a 3T Siemens Trio or 1.5T Siemens Sonata and analyzed using the FMRIB Software Library (FSL). DNA methylation measurements were derived from cryo-conserved blood samples. We found a positive association between MB-COMT promoter methylation and neural activity in the left dorsolateral prefrontal cortex in a model using a region-of-interest approach and could confirm this finding in a whole-brain model. This effect was independent of disease status. Analyzing the effect of MB-COMT promoter DNA methylation on a neuroimaging phenotype can provide further evidence for the importance of COMT and epigenetic risk mechanisms in schizophrenia. The latter may represent trans-regulatory or environmental risk factors that can be measured using brain-based intermediate phenotypes.

Authors: Esther Walton, Jingyu Liu, Johanna Hass, Tonya White, Markus Scholz, Veit Roessner, Randy Gollub, Vince D. Calhoun, Stefan Ehrlich

Date Published: 6th May 2014

Publication Type: Journal article

Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood.
Genetical Statistics and Systems Biology

Abstract (Expand)

Epidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we … evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (\textgreekb = - 0.76, 95% CI - 2.45 to 1.08 mmHg), 0.06 mmHg lower diastolic blood pressure (\textgreekb = - 0.06, 95% CI - 0.93 to 0.87 mmHg), or pulse pressure (\textgreekb = - 0.65, 95% CI - 1.38 to 0.69 mmHg, all p \textgreater 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses.

Authors: Yan Zheng, Tao Huang, Tiange Wang, Zhendong Mei, Zhonghan Sun, Tao Zhang, Christina Ellervik, Jin-Fang Chai, Xueling Sim, Rob M. van Dam, E-Shyong Tai, Woon-Puay Koh, Rajkumar Dorajoo, Seang-Mei Saw, Charumathi Sabanayagam, Tien Yin Wong, Preeti Gupta, Peter Rossing, Tarunveer S. Ahluwalia, Rebecca K. Vinding, Hans Bisgaard, Klaus Bønnelykke, Yujie Wang, Mariaelisa Graff, Trudy Voortman, Frank J. A. van Rooij, Albert Hofman, Diana van Heemst, Raymond Noordam, Angela C. Estampador, Tibor V. Varga, Cornelia Enzenbach, Markus Scholz, Joachim Thiery, Ralph Burkhardt, Marju Orho-Melander, Christina-Alexandra Schulz, Ulrika Ericson, Emily Sonestedt, Michiaki Kubo, Masato Akiyama, Ang Zhou, Tuomas O. Kilpeläinen, Torben Hansen, Marcus E. Kleber, Graciela Delgado, Mark McCarthy, Rozenn N. Lemaitre, Janine F. Felix, Vincent W. V. Jaddoe, Ying Wu, Karen L. Mohlke, Terho Lehtimäki, Carol A. Wang, Craig E. Pennell, Heribert Schunkert, Thorsten Kessler, Lingyao Zeng, Christina Willenborg, Annette Peters, Wolfgang Lieb, Veit Grote, Peter Rzehak, Berthold Koletzko, Jeanette Erdmann, Matthias Munz, Tangchun Wu, Meian He, Caizheng Yu, Cécile Lecoeur, Philippe Froguel, Dolores Corella, Luis A. Moreno, Chao-Qiang Lai, Niina Pitkänen, Colin A. Boreham, Paul M. Ridker, Frits R. Rosendaal, Renée de Mutsert, Chris Power, Lavinia Paternoster, Thorkild I. A. Sørensen, Anne Tjønneland, Kim Overvad, Luc Djousse, Fernando Rivadeneira, Nanette R. Lee, Olli T. Raitakari, Mika Kähönen, Jorma Viikari, Jean-Paul Langhendries, Joaquin Escribano, Elvira Verduci, George Dedoussis, Inke König, Beverley Balkau, Oscar Coltell, Jean Dallongeville, Aline Meirhaeghe, Philippe Amouyel, Frédéric Gottrand, Katja Pahkala, Harri Niinikoski, Elina Hyppönen, Winfried März, David A. Mackey, Dariusz Gruszfeld, Katherine L. Tucker, Frédéric Fumeron, Ramon Estruch, Jose M. Ordovas, Donna K. Arnett, Dennis O. Mook-Kanamori, Dariush Mozaffarian, Bruce M. Psaty, Kari E. North, Daniel I. Chasman, Lu Qi

Date Published: 7th May 2020

Publication Type: Journal article

Merging concepts - coupling an agent-based model of hematopoietic stem cells with an ODE model of granulopoiesis
Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND\backslashr\backslashnHematopoiesis is a complex process involving different cell types and feedback mechanisms mediated by cytokines. This complexity stimulated various models with different … scopes and applications. A combination of complementary models promises to provide their mutual confirmation and to explain a broader range of scenarios. Here we propose a combination of an ordinary differential equation (ODE) model of human granulopoiesis and an agent-based model (ABM) of hematopoietic stem cell (HSC) organization. The first describes the dynamics of bone marrow cell stages and circulating cells under various perturbations such as G-CSF treatment or chemotherapy. In contrast to the ODE model describing cell numbers, our ABM focuses on the organization of individual cells in the stem population.\backslashr\backslashnRESULTS\backslashr\backslashnWe combined the two models by replacing the HSC compartment of the ODE model by a difference equation formulation of the ABM. In this hybrid model, regulatory mechanisms and parameters of the original models were kept unchanged except for a few specific improvements: (i) Effect of chemotherapy was restricted to proliferating HSC and (ii) HSC regulation in the ODE model was replaced by the intrinsic regulation of the ABM. Model simulations of bleeding, chronic irradiation and stem cell transplantation revealed that the dynamics of hybrid and ODE model differ markedly in scenarios with stem cell damage. Despite these differences in response to stem cell damage, both models explain clinical data of leukocyte dynamics under four chemotherapy regimens.\backslashr\backslashnCONCLUSIONS\backslashr\backslashnABM and ODE model proved to be compatible and were combined without altering the structure of both models. The new hybrid model introduces model improvements by considering the proliferative state of stem cells and enabling a cell cycle-dependent effect of chemotherapy. We demonstrated that it is able to explain and predict granulopoietic dynamics for a large variety of scenarios such as irradiation, bone marrow transplantation, chemotherapy and growth factor applications. Therefore, it promises to serve as a valuable tool for studies in a broader range of clinical applications, in particular where stem cell activation and proliferation are involved.

Authors: Axel Krinner, Ingo Roeder, Markus Loeffler, Markus Scholz

Date Published: 2013

Publication Type: Journal article

Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline.
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Abstract (Expand)

Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for … rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m(2)/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m(2) at follow-up among those with eGFRcrea 60 mL/min/1.73m(2) or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or LARP4B. Individuals at high compared to those at low genetic risk (8-14 vs 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function.

Authors: M. Gorski, B. Jung, Y. Li, P. R. Matias-Garcia, M. Wuttke, S. Coassin, C. H. L. Thio, M. E. Kleber, T. W. Winkler, V. Wanner, J. F. Chai, A. Y. Chu, M. Cocca, M. F. Feitosa, S. Ghasemi, A. Hoppmann, K. Horn, M. Li, T. Nutile, M. Scholz, K. B. Sieber, A. Teumer, A. Tin, J. Wang, B. O. Tayo, T. S. Ahluwalia, P. Almgren, S. J. L. Bakker, B. Banas, N. Bansal, M. L. Biggs, E. Boerwinkle, E. P. Bottinger, H. Brenner, R. J. Carroll, J. Chalmers, M. L. Chee, M. L. Chee, C. Y. Cheng, J. Coresh, M. H. de Borst, F. Degenhardt, K. U. Eckardt, K. Endlich, A. Franke, S. Freitag-Wolf, P. Gampawar, R. T. Gansevoort, M. Ghanbari, C. Gieger, P. Hamet, K. Ho, E. Hofer, B. Holleczek, V. H. Xian Foo, N. Hutri-Kahonen, S. J. Hwang, M. A. Ikram, N. S. Josyula, M. Kahonen, C. C. Khor, W. Koenig, H. Kramer, B. K. Kramer, B. Kuhnel, L. A. Lange, T. Lehtimaki, W. Lieb, R. J. F. Loos, M. A. Lukas, L. P. Lyytikainen, C. Meisinger, T. Meitinger, O. Melander, Y. Milaneschi, P. P. Mishra, N. Mononen, J. C. Mychaleckyj, G. N. Nadkarni, M. Nauck, K. Nikus, B. Ning, I. M. Nolte, M. L. O'Donoghue, M. Orho-Melander, S. A. Pendergrass, B. W. J. H. Penninx, M. H. Preuss, B. M. Psaty, L. M. Raffield, O. T. Raitakari, R. Rettig, M. Rheinberger, K. M. Rice, A. R. Rosenkranz, P. Rossing, J. I. Rotter, C. Sabanayagam, H. Schmidt, R. Schmidt, B. Schottker, C. A. Schulz, S. Sedaghat, C. M. Shaffer, K. Strauch, S. Szymczak, K. D. Taylor, J. Tremblay, L. Chaker, P. van der Harst, P. J. van der Most, N. Verweij, U. Volker, M. Waldenberger, L. Wallentin, D. M. Waterworth, H. D. White, J. G. Wilson, T. Y. Wong, M. Woodward, Q. Yang, M. Yasuda, L. M. Yerges-Armstrong, Y. Zhang, H. Snieder, C. Wanner, C. A. Boger, A. Kottgen, F. Kronenberg, C. Pattaro, I. M. Heid

Date Published: 30th Oct 2020

Publication Type: Journal article

Metabolite-Investigator: an integrated user-friendly workflow for metabolomics multi-study analysis
Genetical Statistics and Systems Biology

Abstract (Expand)

Motivation Many diseases have a metabolic background, which is increasingly investigated due to improved measurement techniques allowing high-throughput assessment of metabolic features in several body … fluids. Integrating data from multiple cohorts is of high importance to obtain robust and reproducible results. However, considerable variability across studies due to differences in sampling, measurement techniques and study populations needs to be accounted for. Results We present Metabolite-Investigator, a scalable analysis workflow for quantitative metabolomics data from multiple studies. Our tool supports all aspects of data pre-processing including data integration, cleaning, transformation, batch analysis as well as multiple analysis methods including uni- and multivariable factor-metabolite associations, network analysis and factor prioritization in one or more cohorts. Moreover, it allows identifying critical interactions between cohorts and factors affecting metabolite levels and inferring a common covariate model, all via a graphical user interface. Availability and implementation We constructed Metabolite-Investigator as a free and open web-tool and stand-alone Shiny-app. It is hosted at https://apps.health-atlas.de/metabolite-investigator/, the source code is freely available at https://github.com/cfbeuchel/Metabolite-Investigator. Supplementary information Supplementary data are available at Bioinformatics online.

Authors: Carl Beuchel, Holger Kirsten, Uta Ceglarek, Markus Scholz

Date Published: 16th Nov 2020

Publication Type: Journal article

Mice overexpressing CD97 in intestinal epithelial cells provide a unique model for mammalian postnatal intestinal cylindrical growth
Genetical Statistics and Systems Biology

Abstract (Expand)

Postnatal enlargement of the mammalian intestine comprises cylindrical and luminal growth, associated with crypt fission and crypt/villus hyperplasia, respectively, which subsequently predominate before … and after weaning. The bipartite adhesion G protein-coupled receptor CD97 shows an expression gradient along the crypt-villus axis in the normal human intestine. We here report that transgenic mice overexpressing CD97 in intestinal epithelial cells develop an upper megaintestine. Intestinal enlargement involves an increase in length and diameter but does not affect microscopic morphology, as typical for cylindrical growth. The megaintestine is acquired after birth and before weaning, independent of the genotype of the mother, excluding altered availability of milk constituents as driving factor. CD97 overexpression does not regulate intestinal growth factors, stem cell markers, and Wnt signaling, which contribute to epithelial differentiation and renewal, nor does it affect suckling-to-weaning transition. Consistent with augmented cylindrical growth, suckling but not adult transgenic mice show enlarged crypts and thus more crypt fissions caused by a transient increase of the crypt transit-amplifying zone. Intestinal enlargement by CD97 requires its seven-span transmembrane/cytoplasmic C-terminal fragment but not the N-terminal fragment binding partner CD55. In summary, ectopic expression of CD97 in intestinal epithelial cells provides a unique model for intestinal cylindrical growth occurring in breast-fed infants.

Authors: Gabriela Aust, Christiane Kerner, Susann Gonsior, Doreen Sittig, Hartmut Schneider, Peter Buske, Markus Scholz, Norman Dietrich, Sindy Oldenburg, Olga N. Karpus, Jörg Galle, Salah Amasheh, Jörg Hamann

Date Published: 15th Jul 2013

Publication Type: Journal article

Model-based design of chemotherapeutic regimens that account for heterogeneity in leucopoenia
Genetical Statistics and Systems Biology

Abstract (Expand)

Patients treated with multicycle chemotherapy can exhibit large interindividual heterogeneity of haematotoxicity. We describe how a biomathematical model of human granulopoiesis can be used to design … risk-adapted dose-dense chemotherapies, leading to more similar leucopoenias in the population. Calculations were performed on a large data set for cyclophosphamide/doxorubicin/vincristine/prednisone (CHOP)-like chemotherapies for aggressive non-Hodgkin lymphoma. Age, gender, Eastern Cooperative Oncology Group performance status, lactate dehydrogenase and the degree of leucopoenia within the first therapy cycle were used to stratify patients into groups with different expected severity of leucopoenia. We estimated risk-specific bone marrow toxicities depending on the drug doses administered. These toxicities were used to derive risk-adapted therapy schedules. We determined different doses of cyclophosphamide and additional etoposide for patients treated with CHOP-14. Alternatively, the model predicted that further reductions of cycle duration were feasible in groups with low toxicity. We also used the model to identify appropriate granulocyte colony-stimulating factor (G-CSF) schedules. In conclusion, we present a method to estimate the potential of risk-specific dose adaptation of different cytotoxic drugs in order to design chemotherapy protocols that result in decreased diversity of leucopoenia between patients, to develop dose-escalation strategies in cases of low leucopoenic reaction and to determine optimal G-CSF support.

Authors: Markus Scholz, Christoph Engel, Markus Loeffler

Date Published: 1st Mar 2006

Publication Type: Journal article

Model-based individual managing of thrombocytopenia during multi-cyclic chemotherapy
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, Markus Scholz, Markus Löffler

Date Published: 9th Jun 2017

Publication Type: Not specified

Human Diseases: thrombocytopenia

Model-based optimization of G-CSF treatment during cytotoxic chemotherapy.
Genetical Statistics and Systems Biology

Abstract (Expand)

PURPOSE: Although G-CSF is widely used to prevent or ameliorate leukopenia during cytotoxic chemotherapies, its optimal use is still under debate and depends on many therapy parameters such as dosing … and timing of cytotoxic drugs and G-CSF, G-CSF pharmaceuticals used and individual risk factors of patients. METHODS: We integrate available biological knowledge and clinical data regarding cell kinetics of bone marrow granulopoiesis, the cytotoxic effects of chemotherapy and pharmacokinetics and pharmacodynamics of G-CSF applications (filgrastim or pegfilgrastim) into a comprehensive model. The model explains leukocyte time courses of more than 70 therapy scenarios comprising 10 different cytotoxic drugs. It is applied to develop optimized G-CSF schedules for a variety of clinical scenarios. RESULTS: Clinical trial results showed validity of model predictions regarding alternative G-CSF schedules. We propose modifications of G-CSF treatment for the chemotherapies 'BEACOPP escalated' (Hodgkin's disease), 'ETC' (breast cancer), and risk-adapted schedules for 'CHOP-14' (aggressive non-Hodgkin's lymphoma in elderly patients). CONCLUSIONS: We conclude that we established a model of human granulopoiesis under chemotherapy which allows predictions of yet untested G-CSF schedules, comparisons between them, and optimization of filgrastim and pegfilgrastim treatment. As a general rule of thumb, G-CSF treatment should not be started too early and patients could profit from filgrastim treatment continued until the end of the chemotherapy cycle.

Authors: S. Schirm, C. Engel, S. Loibl, M. Loeffler, M. Scholz

Date Published: 6th Nov 2017

Publication Type: Journal article

Modeling combined chemo- and immunotherapy of high-grade non-Hodgkin lymphoma.
LIFE - Leipzig Research Center for Civilization Diseases, Genetical Statistics and Systems Biology

Abstract (Expand)

Moderate, but not massive intensification of CHOP-21 improves outcome in aggressive non-Hodgkin lymphoma. Adding immunotherapy with Rituximab was a break-through, but levels differences in chemotherapy. … Ongoing trials attempt to optimize R-CHOP type regimens. We present a mathematical model of chemo-immunotherapy to explain published and aiming at predicting future trials comparing R-CHOP variants. We hypothesize that, for cure, the immune system must dominate residual tumor cells at the end of treatment. Chemotherapy reduces both tumor and immune cells. Rituximab immunotherapy boosts the immune response. We translate this reasoning into a differential equations model. Model parameters are estimated using data of randomized clinical trials in elderly patients. The model explains observed hazard ratios between treatments. It explains why too intense chemotherapy could be detrimental. The model is validated predicting six published independent studies. As an application, we varied treatment schedules and predict that current R-CHOP variants have only limited optimization potential.

Authors: K. Rosch, M. Scholz, D. Hasenclever

Date Published: 16th Dec 2015

Publication Type: Not specified

Human Diseases: lymphoma

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

Modelling chemotherapy effects on granulopoiesis.
GLA - German Lymphoma Alliance, Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND: Although the growth-factor G-CSF is widely used to prevent granulotoxic side effects of cytotoxic chemotherapies, its optimal use is still unknown since treatment outcome depends on many … parameters such as dosing and timing of chemotherapies, pharmaceutical derivative of G-CSF used and individual risk factors. We showed in the past that a pharmacokinetic and -dynamic model of G-CSF and human granulopoiesis can be used to predict the performance of yet untested G-CSF schedules. However, only a single chemotherapy was considered so far. RESULTS: Model assumptions proved to be feasible in explaining granulotoxicity of 10 different chemotherapeutic drugs or drug-combinations applied in 33 different schedules with and without G-CSF. Risk groups of granulotoxicity were traced back to differences in toxicity parameters. CONCLUSION: We established a comprehensive model of combined G-CSF and chemotherapy action in humans which allows us to predict and compare the outcome of alternative G-CSF schedules. We aim to apply the model in different clinical contexts to optimize and individualize G-CSF treatment.

Authors: S. Schirm, C. Engel, M. Loeffler, M. Scholz

Date Published: 24th Dec 2014

Publication Type: Not specified

Human Diseases: leukopenia

Modelling lymphoma therapy and outcome
Genetical Statistics and Systems Biology

Abstract (Expand)

Dose and time intensifications of chemotherapy improved the outcome of lymphoma therapy. However, recent study results show that too intense therapies can result in inferior tumour control. We hypothesise … that the immune system plays a key role in controlling residual tumour cells after treatment. More intense therapies result in a stronger depletion of immune cells allowing an early re-growth of the tumour.We propose a differential equations model of the dynamics and interactions of tumour and immune cells under chemotherapy. Major model features are an exponential tumour growth, a modulation of the production of effector cells by the presence of the tumour (immunogenicity), and mutual destruction of tumour and immune cells. Chemotherapy causes damage to both, immune and tumour cells. Growth rate, chemosensitivity, immunogenicity, and initial size of the tumour are assumed to be patient-specific, resulting in heterogeneity regarding therapy outcome. Maximum-entropy distributions of these parameters were estimated on the basis of clinical survival data. The resulting model can explain the outcome of five different chemotherapeutic regimens and corresponding hazard-ratios.We conclude that our model explains observed paradox effects in lymphoma therapy by the simple assumption of a relevant anti-tumour effect of the immune system. Heterogeneity of therapy outcomes can be explained by distributions of model parameters, which can be estimated on the basis of clinical survival data. We demonstrate how the model can be used to make predictions regarding yet untested therapy options.

Authors: Katja Roesch, Dirk Hasenclever, Markus Scholz

Date Published: 1st Feb 2014

Publication Type: Journal article

Monitoring Disease Progression and Therapeutic Response in a Disseminated Tumor Model for Non-Hodgkin Lymphoma by Bioluminescence Imaging
Genetical Statistics and Systems Biology

Abstract (Expand)

Xenograft tumor models are widely studied in cancer research. Our aim was to establish and apply a model for aggressive CD20-positive B-cell non-Hodgkin lymphomas, enabling us to monitor tumor growth … and shrinkage in a noninvasive manner. By stably transfecting a luciferase expression vector, we created two bioluminescent human non-Hodgkin lymphoma cell lines, Jeko1(luci) and OCI-Ly3(luci), that are CD20 positive, a prerequisite to studying rituximab, a chimeric anti-CD20 antibody. To investigate the therapy response in vivo, we established a disseminated xenograft tumor model injecting these cell lines in NOD/SCID mice. We observed a close correlation of bioluminescence intensity and tumor burden, allowing us to monitor therapy response in the living animal. Cyclophosphamide reduced tumor burden in mice injected with either cell line in a dose-dependent manner. Rituximab alone was effective in OCI-Ly3(luci)-injected mice and acted additively in combination with cyclophosphamide. In contrast, it improved the therapeutic outcome of Jeko1(luci)-injected mice only in combination with cyclophosphamide. We conclude that well-established bioluminescence imaging is a valuable tool in disseminated xenograft tumor models. Our model can be translated to other cell lines and used to examine new therapeutic agents and schedules.

Authors: Margarethe Köberle, Kristin Müller, Manja Kamprad, Friedemann Horn, Markus Scholz

Date Published: 2015

Publication Type: Journal article

Monitoring of WT1 expression in PB and CD34(+) donor chimerism of BM predicts early relapse in AML and MDS patients after hematopoietic cell transplantation with reduced-intensity conditioning
Genetical Statistics and Systems Biology

Abstract (Expand)

Relapse of malignant disease remains the major complication in patients with acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS) after hematopoietic cell transplantation (HCT) with … reduced-intensity conditioning (RIC). In this study, we investigated the predictive value of disease-specific markers (DSMs), donor chimerism (DC) analysis of unsorted (UDC) or CD34(+) sorted cells and Wilms’ tumor gene 1 (WT1) expression. Eighty-eight patients with AML or MDS were monitored after allogenic HCT following 2 Gy total-body irradiation with (n=84) or without (n=4) fludarabine 3 \times 30 mg/m(2), followed by cyclosporin A and mycophenolate mofetil. DSMs were determined by fluorescence in situ hybridization (FISH) and WT1 expression by real-time polymerase chain reaction. Chimerism analysis was performed on unsorted or CD34(+) sorted cells, by FISH or short tandem repeat polymerase chain reaction. Twenty-one (24%) patients relapsed within 4 months after HCT. UDC, CD34(+) DC and WT1 expression were each significant predictors of relapse with sensitivities ranging from 53 to 79% and specificities of 82-91%. Relapse within 28 days was excluded almost entirely on the basis of WT1 expression combined with CD34(+) DC kinetics. Monitoring of WT1 expression and CD34(+) DC predict relapse of AML and MDS after RIC-HCT.

Authors: T. Lange, M. Hubmann, Ralph Burkhardt, G-N Franke, M. Cross, Markus Scholz, S. Leiblein, H. K. Al-Ali, J. Edelmann, Joachim Thiery, D. Niederwieser

Date Published: 1st Mar 2011

Publication Type: Journal article

Myocardial Infarction-Associated Circular RNA Predicting Left Ventricular Dysfunction.
Genetical Statistics and Systems Biology, LIFE Heart

Abstract

Not specified

Authors: M. Vausort, A. Salgado-Somoza, L. Zhang, P. Leszek, M. Scholz, A. Teren, R. Burkhardt, J. Thiery, D. R. Wagner, Y. Devaux

Date Published: 13th Sep 2016

Publication Type: Journal article

Human Diseases: left ventricular noncompaction, myocardial infarction

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