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Katrin Horn

About Katrin Horn:
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Health Atlas ID: 83TNHDVX05-6

Location:  Germany

Expertise: Not specified

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ORCID: https://orcid.org/0000-0002-5307-6936

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Genetical Statistics and Systems Biology

The group is interested in omic-level studies including the genome, methylome, transcriptome, and metabolome of the general population as well as of various diseases including cardiovascular diseases, pneumonia, sepsis, obesity, and brain cancers. Additionally, we aim at transfering results of biomathematical model simulations into clinical practice e.g. by haematopoietic growth-factor opimization during cytotoxic chemotherapy and optimization of EPO applications in chronic kidney disease.

The
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Programme: This Project is not associated with a Programme

Public web page: http://www.imise.uni-leipzig.de/en/Groups/GenStat/

Start date: 1st Jan 2013

LIFE - Leipzig Research Center for Civilization Diseases: inactive since

Goal of the Leipzig Research Center for Civilization Diseases (LIFE) is the investigation of civilization diseases like depression, diabetes, allergies or cardiovascular diseases. For this purpose we collect as much data as possible regarding health and living conditions of the population in Leipzig and provide these data for scientists of the University of Leipzig and other research institutions.

Programme: Epidemiology

Public web page: http://life.uni-leipzig.de/

Start date: 1st Jan 2009

LIFE Heart

The LIFE-Heart study recruited 7,000 patients with suspected coronary heart disease, manifest heart disease or myocardial infarction. All patients received coronary angiography so that the vascular status in the heart is precisely known. In principle, this examination is not feasible in population-related studies. In addition, the patients were thoroughly examined with regard to the general vascular status and the health of the cardiovascular system. Extensive environmental factors were recorded.
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Programme: Epidemiology

Public web page: http://life.uni-leipzig.de/

Start date: 1st Jan 2009

LIFE Adult

This population-based study examined 10,000 participants randomly selected from the Leipzig population (2011 to 2014). A follow-up is to be carried out from 2017 - 2020. The study mainly included people aged between 40 and 79. All participants underwent a 6-hour study program and people over 60 years of age were invited two more times to in-depth study of cognition and depression and the brain (MRI, EEG). Extensive measurements of genome, metabolome and transcriptome are available. The LIFE-ADULT
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Programme: Epidemiology

Public web page: http://life.uni-leipzig.de/en/adults/life_adult.html

Start date: 1st Jan 2009

A biomathematical model of human erythropoiesis and iron metabolism
Genetical Statistics and Systems Biology

Abstract (Expand)

Anaemia therapy or perisurgical support of erythropoiesis often require both, EPO and iron medication. However, excessive iron medication can result in iron overload and it is challenging to control … haemoglobin levels in a desired range. To support this task, we develop a biomathematical model to simulate EPO- and iron medication in humans. We combine our previously established model of human erythropoiesis including comprehensive pharmacokinetic models of EPO applications with a newly developed model of iron metabolism including iron supplementation. Equations were derived by translating known biological mechanisms into ordinary differential equations. Qualitative model behaviour is studied in detail considering a variety of interventions such as bleeding, iron malnutrition and medication. The model can explain time courses of erythrocytes, reticulocytes, haemoglobin, haematocrit, red blood cells, EPO, serum iron, ferritin, transferrin saturation, and transferrin under a variety of scenarios including EPO and iron application into healthy volunteers or chemotherapy patients. Unknown model parameters were determined by fitting the predictions of the model to time series data from literature. We demonstrate how the model can be used to make predictions of untested therapy options such as cytotoxic chemotherapy supported by iron and EPO. Following our ultimate goal of establishing a model of anaemia treatment in chronic kidney disease, we aim at translating our model to this pathological condition in the near future.

Authors: Sibylle Schirm, Markus Scholz

Date Published: 1st Dec 2020

Publication Type: Journal article

Dynamics of cytokines, immune cell counts and disease severity in patients with community-acquired pneumonia - Unravelling potential causal relationships
Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND Community acquired pneumonia (CAP) is a severe and often rapidly deteriorating disease. To better understand its dynamics and potential causal relationships, we analyzed time series data of …f cytokines, blood and clinical parameters in hospitalized CAP patients. METHODS Time series data of 10 circulating cytokines, blood counts and clinical parameters were related to baseline characteristics of 403 CAP patients using univariate mixed models. Bivariate mixed models were applied to analyze correlations between the time series. To identify potential causal relationships, we inferred cross-lagged relationships between pairs of parameters using latent curve models with structured residuals. RESULTS IL-6 levels decreased faster over time in younger patients (Padj = 0.06). IL-8, VCAM-1, and IL-6 correlated strongly with disease severity as assessed by the sequential organ failure assessment (SOFA) score (r = 0.49, 0.48, 0.46, respectively; all Padj \textless 0.001). IL-6 and bilirubin correlated with respect to their mean levels and slopes over time (r = 0.36 and r = 0.46, respectively; Padj \textless 0.001). A number of potential causal relationships were identified, e.g., a negative effect of ICAM-1 on MCP-1, or a positive effect of the level of creatinine on the subsequent VCAM-1 concentration (P \textless 0.001). CONCLUSIONS These results suggest that IL-6 trajectories of CAP patients are associated with age and run parallel to bilirubin levels. The time series analysis also unraveled directed, potentially causal relationships between cytokines, blood parameters and clinical outcomes. This will facilitate the development of mechanistic models of CAP, and with it, improvements in treatment or surveillance strategies for this disease. TRIAL REGISTRATION clinicaltrials.gov NCT02782013, May 25, 2016, retrospectively registered.

Authors: Maciej Rosolowski, Volker Oberle, Peter Ahnert, Petra Creutz, Martin Witzenrath, Michael Kiehntopf, Markus Loeffler, Norbert Suttorp, Markus Scholz

Date Published: 1st Dec 2020

Publication Type: Journal article

Integration of mathematical model predictions into routine workflows to support clinical decision making in haematology
Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND Individualization and patient-specific optimization of treatment is a major goal of modern health care. One way to achieve this goal is the application of high-resolution diagnostics together …r with the application of targeted therapies. However, the rising number of different treatment modalities also induces new challenges: Whereas randomized clinical trials focus on proving average treatment effects in specific groups of patients, direct conclusions at the individual patient level are problematic. Thus, the identification of the best patient-specific treatment options remains an open question. Systems medicine, specifically mechanistic mathematical models, can substantially support individual treatment optimization. In addition to providing a better general understanding of disease mechanisms and treatment effects, these models allow for an identification of patient-specific parameterizations and, therefore, provide individualized predictions for the effect of different treatment modalities. RESULTS In the following we describe a software framework that facilitates the integration of mathematical models and computer simulations into routine clinical processes to support decision-making. This is achieved by combining standard data management and data exploration tools, with the generation and visualization of mathematical model predictions for treatment options at an individual patient level. CONCLUSIONS By integrating model results in an audit trail compatible manner into established clinical workflows, our framework has the potential to foster the use of systems-medical approaches in clinical practice. We illustrate the framework application by two use cases from the field of haematological oncology.

Authors: Katja Hoffmann, Katja Cazemier, Christoph Baldow, Silvio Schuster, Yuri Kheifetz, Sibylle Schirm, Matthias Horn, Thomas Ernst, Constanze Volgmann, Christian Thiede, Andreas Hochhaus, Martin Bornhäuser, Meinolf Suttorp, Markus Scholz, Ingmar Glauche, Markus Loeffler, Ingo Roeder

Date Published: 1st Dec 2020

Publication Type: Journal article

Genome-wide association meta-analysis for early age-related macular degeneration highlights novel loci and insights for advanced disease
Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND Advanced age-related macular degeneration (AMD) is a leading cause of blindness. While around half of the genetic contribution to advanced AMD has been uncovered, little is known about the … genetic architecture of early AMD. METHODS To identify genetic factors for early AMD, we conducted a genome-wide association study (GWAS) meta-analysis (14,034 cases, 91,214 controls, 11 sources of data including the International AMD Genomics Consortium, IAMDGC, and UK Biobank, UKBB). We ascertained early AMD via color fundus photographs by manual grading for 10 sources and via an automated machine learning approach for > 170,000 photographs from UKBB. We searched for early AMD loci via GWAS and via a candidate approach based on 14 previously suggested early AMD variants. RESULTS Altogether, we identified 10 independent loci with statistical significance for early AMD: (i) 8 from our GWAS with genome-wide significance (P < 5 × 10- 8), (ii) one previously suggested locus with experiment-wise significance (P < 0.05/14) in our non-overlapping data and with genome-wide significance when combining the reported and our non-overlapping data (together 17,539 cases, 105,395 controls), and (iii) one further previously suggested locus with experiment-wise significance in our non-overlapping data. Of these 10 identified loci, 8 were novel and 2 known for early AMD. Most of the 10 loci overlapped with known advanced AMD loci (near ARMS2/HTRA1, CFH, C2, C3, CETP, TNFRSF10A, VEGFA, APOE), except two that have not yet been identified with statistical significance for any AMD. Among the 17 genes within these two loci, in-silico functional annotation suggested CD46 and TYR as the most likely responsible genes. Presence or absence of an early AMD effect distinguished the known pathways of advanced AMD genetics (complement/lipid pathways versus extracellular matrix metabolism). CONCLUSIONS Our GWAS on early AMD identified novel loci, highlighted shared and distinct genetics between early and advanced AMD and provides insights into AMD etiology. Our data provide a resource comparable in size to the existing IAMDGC data on advanced AMD genetics enabling a joint view. The biological relevance of this joint view is underscored by the ability of early AMD effects to differentiate the major pathways for advanced AMD.

Authors: Thomas W. Winkler, Felix Grassmann, Caroline Brandl, Christina Kiel, Felix Günther, Tobias Strunz, Lorraine Weidner, Martina E. Zimmermann, Christina A. Korb, Alicia Poplawski, Alexander K. Schuster, Martina Müller-Nurasyid, Annette Peters, Franziska G. Rauscher, Tobias Elze, Katrin Horn, Markus Scholz, Marisa Cañadas-Garre, Amy Jayne McKnight, Nicola Quinn, Ruth E. Hogg, Helmut Küchenhoff, Iris M. Heid, Klaus J. Stark, Bernhard H. F. Weber

Date Published: 1st Dec 2020

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

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