Markus Scholz

About Markus Scholz:

Markus Scholz Scientific Speaker Institution Institut für Medizinische Informatik, Statistik und Epidemiologie Universität Leipzig Härtelstraße 16-18 04107 Leipzig

LHA ID: 7WARYC93H8-4

Location:  Germany

ORCID: Not specified

Joined: 5th Jul 2021

Expertise: Not specified

Tools: Not specified

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Task Force COVID-19 Leipzig

This project serves as a container for all COVID-19 related assets, developed at the University of Leipzig and its partners.

Programme: NFDI - German National Research Data Infrastructure

Public web page: https://www.nfdi4health.de/task-force-covid-19

Start date: 20th May 2020

NFDI4Health: inactive since

NFDI4Health - the National Research Data Infrastructure for Personal Health Data - deals with data generated in clinical trials, epidemiological and public health studies. The collection and analysis of these data on health and disease status and important factors influencing it are an essential component for the development of new therapies, comprehensive care approaches and preventive measures in a modern health care system. Although these data already meet high content quality standards, they ...

Programme: NFDI - German National Research Data Infrastructure

Public web page: https://www.nfdi4health.de/en

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. ...

Programme: LIFE Management Cluster

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

Start date: 1st Jan 2009

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: LIFE Management Cluster

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

Start date: 1st Jan 2009

HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles

The central objective of HaematoOpt project is to demonstrate that recently developed dynamic mathematical models of normal and leukemic hematopoiesis can be used to practically impact clinical decision- making

Programme: This Project is not associated with a Programme

Public web page: https://haematoopt.de/

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 ...

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

e:Med: inactive since

e:Med has the objective of establishing systems medicine in Germany. e:Med promotes system-oriented research into diseases in order to facilitate improved prevention, more comprehensive diagnostics and individually adjusted therapy schemes in individualized medicine. The program brings together scientists with molecular-genetic, clinical, mathematical and information technology expertise, with the objective of ensuring that research results quickly benefit patients.

Programme: Default Programme

Public web page: https://www.sys-med.de/en/

Covid-19
Task Force COVID-19 Leipzig
No description specified

Submitter: René Hänsel

Studies: Covid-19 Data Source Research, IMISE Covid-19 Bulletins (in German)

Resources: Covid-19 Data Sources Germany, Covid-19 Data Sources worldwide, Entwicklung der COVID-19 Epidemie in Sachsen und Deutschland

IMISE Covid-19 Bulletins (in German)
Task Force COVID-19 Leipzig

A collection of Bulletins of the Institute for Medical Informatics, Statistics and Epidemiology (IMISE) about the COVID-19 pandemic in Leipzig and Saxony. This work was funded in the framework of the project SaxoCOV (Saxonian COVID-19 Research Consortium, SaxoCOV was financed by the Free State of Saxony).”

Submitter: René Hänsel

Investigation: Covid-19

Resources: Entwicklung der COVID-19 Epidemie in Sachsen und Deutschland

Study type: Not specified

GWAMA Phytosterole
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Genome-wide Association Meta-Analyses of 32 phytosterol traits reflecting resorption, cholesterol synthesis and esterification in six studies with up to 9,758 subjects Summary statistics of GWAMA results will be made available upon acceptance of our manuscript.

Submitter: Janne Pott

Investigation: OMICS Investigations

Resources: Summary Statistics - Phytosterols

Study type: Genetic study

Entwicklung der COVID-19 Epidemie in Sachsen und Deutschland
Task Force COVID-19 Leipzig

A collection of Bulletins of the Institute for Medical Informatics, Statistics and Epidemiology (IMISE) about the COVID-19 pandemic in Leipzig and Saxony. This work was funded in the framework of the project SaxoCOV (Saxonian COVID-19 Research Consortium, SaxoCOV was financed by the Free State of Saxony).”

Submitter: René Hänsel

Biological problem addressed: Model Analysis Type

Investigation: Covid-19

Study: IMISE Covid-19 Bulletins (in German)

Summary Statistics - Phytosterols
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

We are releasing the summary data from our GWAMA of phytosterol traits, pending on acceptance of our publication, to empower other researchers to examine variants or loci in which they are interested for associations. These data are intended for research purposes only.

Citation: tba

When using this data acknowledge the source as follows: 'Data on phytosterol X has been contributed by LIFE investigators and has been downloaded from https://www.health-atlas.de/assays/53.'

For any enquiries about ...

Submitter: Janne Pott

Resource type: Experimental Assay Type

Technology type: SNP Array

Investigation: OMICS Investigations

Study: GWAMA Phytosterole

Summary Statistics
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

We are releasing the summary data from our meta-analyses of steroid hormones, to empower other researchers to examine variants or loci in which they are interested for association with these hormonal traits. These data are intended for research purposes only.

Citation: Pott et al. (2019) Genetic Association Study of Eight Steroid Hormones and Implications for Sexual Dimorphism of Coronary Artery Disease. J Clin Endocrinol Metab 104: 5008–5023. PubMed ID: 31169883

When using this data acknowledge ...

Submitter: Janne Pott

Resource type: Genome Wide Association

Technology type: SNP Array

Investigation: OMICS Investigations

Study: GWAS Steroid Hormones

The Leipzig Health Atlas-An Open Platform to Present, Archive, and Share Biomedical Data, Analyses, and Models Online.
LHA - Leipzig Health Atlas

Abstract (Expand)

BACKGROUND: Clinical trials, epidemiological studies, clinical registries, and other prospective research projects, together with patient care services, are main sources of data in the medical research … domain. They serve often as a basis for secondary research in evidence-based medicine, prediction models for disease, and its progression. This data are often neither sufficiently described nor accessible. Related models are often not accessible as a functional program tool for interested users from the health care and biomedical domains. OBJECTIVE: The interdisciplinary project Leipzig Health Atlas (LHA) was developed to close this gap. LHA is an online platform that serves as a sustainable archive providing medical data, metadata, models, and novel phenotypes from clinical trials, epidemiological studies, and other medical research projects. METHODS: Data, models, and phenotypes are described by semantically rich metadata. The platform prefers to share data and models presented in original publications but is also open for nonpublished data. LHA provides and associates unique permanent identifiers for each dataset and model. Hence, the platform can be used to share prepared, quality-assured datasets and models while they are referenced in publications. All managed data, models, and phenotypes in LHA follow the FAIR principles, with public availability or restricted access for specific user groups. RESULTS: The LHA platform is in productive mode (https://www.health-atlas.de/). It is already used by a variety of clinical trial and research groups and is becoming increasingly popular also in the biomedical community. LHA is an integral part of the forthcoming initiative building a national research data infrastructure for health in Germany.

Authors: T. Kirsten, F. A. Meineke, H. Loeffler-Wirth, C. Beger, A. Uciteli, S. Staubert, M. Lobe, R. Hansel, F. G. Rauscher, J. Schuster, T. Peschel, H. Herre, J. Wagner, S. Zachariae, C. Engel, M. Scholz, E. Rahm, H. Binder, M. Loeffler

Date Published: 3rd Aug 2022

Publication Type: Journal article

On the Parametrization of Epidemiologic Models-Lessons from Modelling COVID-19 Epidemic.
Genetical Statistics and Systems Biology, Task Force COVID-19 Leipzig

Abstract (Expand)

Numerous prediction models of SARS-CoV-2 pandemic were proposed in the past. Unknown parameters of these models are often estimated based on observational data. However, lag in case-reporting, changing … testing policy or incompleteness of data lead to biased estimates. Moreover, parametrization is time-dependent due to changing age-structures, emerging virus variants, non-pharmaceutical interventions, and vaccination programs. To cover these aspects, we propose a principled approach to parametrize a SIR-type epidemiologic model by embedding it as a hidden layer into an input-output non-linear dynamical system (IO-NLDS). Observable data are coupled to hidden states of the model by appropriate data models considering possible biases of the data. This includes data issues such as known delays or biases in reporting. We estimate model parameters including their time-dependence by a Bayesian knowledge synthesis process considering parameter ranges derived from external studies as prior information. We applied this approach on a specific SIR-type model and data of Germany and Saxony demonstrating good prediction performances. Our approach can estimate and compare the relative effectiveness of non-pharmaceutical interventions and provide scenarios of the future course of the epidemic under specified conditions. It can be translated to other data sets, i.e., other countries and other SIR-type models.

Authors: Y. Kheifetz, H. Kirsten, M. Scholz

Date Published: 2nd Jul 2022

Publication Type: Journal article

Human Diseases: COVID-19

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

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

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

Prevalence of atrial fibrillation dependent on coronary artery status: Insights from the LIFE-Heart Study.
Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND: Coronary artery disease (CAD) is a significant risk factor for atrial fibrillation (AF). Experimental studies demonstrated that atrial ischemia induced by right coronary artery (RCA) stenosis … promote AF triggers and development of electro-anatomical substrate for AF. AIM: To analyze the association between AF prevalence and coronary arteries status in the LIFE-Heart Study. METHODS: This analysis included patients with available coronary catheterization data recruited between 2006 and 2014. Patients with acute myocardial infarction were excluded. CAD was defined as stenosis >/=75%, while coronary artery sclerosis (CAS) was defined as non-critical plaque(s) <75%. RESULTS: In total, 3.458 patients (median age 63 years, 34% women) were included into analysis. AF was diagnosed in 238 (6.7%) patients. There were 681 (19.7%) patients with CAS and 1.411 (40.8%) with CAD (27.5% with single, 32.4% with double, and 40.1% with triple vessel CAD). In multivariable analysis, there was a significant association between prevalent AF and coronary artery status (OR 0.64, 95% CI 0.53-0.78, Ptrend < .001). Similarly, AF risk was lower in patients with higher CAD extent (OR 0.54, 95%CI 0.35-0.83, Ptrend = .005). Compared to single vessel CAD, the risk of AF was lower in double (OR 0.42, 95%CI 0.19-0.95, P = .037) and triple CAD (OR 0.31, 95%CI 0.13-0.71, P = .006). Finally, no association was found between AF prevalence and CAD origin among patients with single vessel CAD. CONCLUSION: In the LIFE-Heart Study, CAS but not CAD was associated with increased risk of AF.

Authors: J. Kornej, S. Henger, T. Seewoster, A. Teren, R. Burkhardt, H. Thiele, J. Thiery, M. Scholz

Date Published: 27th Oct 2020

Publication Type: Journal article

Higher BMI, but not obesity-related genetic polymorphisms, correlates with lower structural connectivity of the reward network in a population-based study.
Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND: Obesity is of complex origin, involving genetic and neurobehavioral factors. Genetic polymorphisms may increase the risk for developing obesity by modulating dopamine-dependent behaviors, … such as reward processing. Yet, few studies have investigated the association of obesity, related genetic variants, and structural connectivity of the dopaminergic reward network. METHODS: We analyzed 347 participants (age range: 20-59 years, BMI range: 17-38 kg/m(2)) of the LIFE-Adult Study. Genotyping for the single nucleotid polymorphisms rs1558902 (FTO) and rs1800497 (near dopamine D2 receptor) was performed on a microarray. Structural connectivity of the reward network was derived from diffusion-weighted magnetic resonance imaging at 3 T using deterministic tractography of Freesurfer-derived regions of interest. Using graph metrics, we extracted summary measures of clustering coefficient and connectivity strength between frontal and striatal brain regions. We used linear models to test the association of BMI, risk alleles of both variants, and reward network connectivity. RESULTS: Higher BMI was significantly associated with lower connectivity strength for number of streamlines (beta = -0.0025, 95%-C.I.: [-0.004, -0.0008], p = 0.0042), and, to lesser degree, fractional anisotropy (beta = -0.0009, 95%-C.I. [-0.0016, -0.00008], p = 0.031), but not clustering coefficient. Strongest associations were found for left putamen, right accumbens, and right lateral orbitofrontal cortex. As expected, the polymorphism rs1558902 in FTO was associated with higher BMI (F = 6.9, p < 0.001). None of the genetic variants was associated with reward network structural connectivity. CONCLUSIONS: Here, we provide evidence that higher BMI correlates with lower reward network structural connectivity. This result is in line with previous findings of obesity-related decline in white matter microstructure. We did not observe an association of variants in FTO or near DRD2 receptor with reward network structural connectivity in this population-based cohort with a wide range of BMI and age. Future research should further investigate the link between genetics, obesity and fronto-striatal structural connectivity.

Authors: F. Beyer, R. Zhang, M. Scholz, K. Wirkner, M. Loeffler, M. Stumvoll, A. Villringer, A. V. Witte

Date Published: 25th Oct 2020

Publication Type: Journal article

Summary statistics for stigmasterol (part 2)
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Summary statistics from GWAMA of stigmasterol (stf_chf, free stigmasterol to free cholesterol; stt_cht, total stigmasterol to total cholesterol; stf_laf, free stigmasterol to free lanosterol; stt_laf, total stigmasterol to free lanosterol). These data are intended for research purposes only, and available upon publication. For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de).

Citation: tba

When ...

Creators: Katrin Horn, Markus Scholz, Janne Pott

Submitter: Janne Pott

Data file type: Other OMICs Data

Summary statistics for stigmasterol (part 1)
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Summary statistics from GWAMA of stigmasterol (ste, esterified stigmasterol; stf, free stigmasterol; stt, total stigmasterol; stf_ste, free to esterified stigmasterol). These data are intended for research purposes only, and available upon publication. For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de).

Citation: tba

When using this data acknowledge the source as follows: 'Data on stigmasterol ...

Creators: Katrin Horn, Markus Scholz, Janne Pott

Submitter: Janne Pott

Data file type: Other OMICs Data

Summary statistics for sitosterol (part 2)
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Summary statistics from GWAMA of sitosterol (sif_chf, free sitosterol to free cholesterol; sit_cht, total sitosterol to total cholesterol; sif_laf, free sitosterol to free lanosterol; sit_laf, total sitosterol to free lanosterol). These data are intended for research purposes only, and available upon publication. For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de).

Citation: tba

When using this ...

Creators: Katrin Horn, Markus Scholz, Janne Pott

Submitter: Janne Pott

Data file type: Other OMICs Data

Summary statistics for sitosterol (part 1)
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Summary statistics from GWAMA of sitosterol (sie, esterified sitosterol; sif, free sitosterol; sit, total sitosterol; sif_sie, free to esterified sitosterol). These data are intended for research purposes only, and available upon publication. For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de).

Citation: tba

When using this data acknowledge the source as follows: 'Data on sitosterol has been ...

Creators: Katrin Horn, Markus Scholz, Janne Pott

Submitter: Janne Pott

Data file type: Other OMICs Data

Summary statistics for campesterol (part 2)
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Summary statistics from GWAMA of campesterol (caf_chf, free campesterol to free cholesterol; cat_cht, total campesterol to total cholesterol; caf_laf, free campesterol to free lanosterol; cat_laf, total campesterol to free lanosterol). These data are intended for research purposes only, and available upon publication. For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de).

Citation: tba

When using ...

Creators: Katrin Horn, Markus Scholz, Janne Pott

Submitter: Janne Pott

Data file type: Other OMICs Data

Summary statistics for campesterol (part 1)
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Summary statistics from GWAMA of campesterol (cae, esterified campesterol; caf, free campesterol; cat, total campesterol; caf_cae, free to esterified campesterol). These data are intended for research purposes only, and available upon publication. For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de).

Citation: tba

When using this data acknowledge the source as follows: 'Data on campesterol has been ...

Creators: Katrin Horn, Markus Scholz, Janne Pott

Submitter: Janne Pott

Data file type: Other OMICs Data

Summary statistics for brassicasterol (part 2)
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Summary statistics from GWAMA of brassicasterol (brf_chf, free brassicasterol to free cholesterol; brt_cht, total brassicasterol to total cholesterol; brf_laf, free brassicasterol to free lanosterol; brt_laf, total brassicasterol to free lanosterol). These data are intended for research purposes only, and available upon publication. For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de).

Citation: ...

Creators: Katrin Horn, Markus Scholz, Janne Pott

Submitter: Janne Pott

Data file type: Other OMICs Data

Summary statistics for brassicasterol (part 1)
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Summary statistics from GWAMA of brassicasterol (bre, esterified brassicasterol; brf, free brassicasterol; brt, total brassicasterol; brf_bre, free to esterified brassicasterol). These data are intended for research purposes only, and available upon publication. For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de).

Citation: tba

When using this data acknowledge the source as follows: 'Data on ...

Creators: Katrin Horn, Markus Scholz, Janne Pott

Submitter: Janne Pott

Data file type: Other OMICs Data

Metabolite Investigator v0.1.2 (Docker Image)
Genetical Statistics and Systems Biology

#UPDATE

This archive has been replaced by the GitLab docker registry. Follow the Link under Data Portal (https://gitlab.com/imise-genstat/metabolite-investigator-archive/container_registry/1612096) to find all previous versions of the app (starting from 0.1.6). The images can be downloaded and run using a working docker environment using the following commands:

Using the initial release version 0.1.6 as an example

docker pull registry.gitlab.com/imise-genstat/metabolite-investigator-archive:0.1.6 ...

Creators: Markus Scholz, Jonas Wagner, Carl Beuchel, Holger Kirsten

Submitter: Carl Beuchel

Data file type: Other OMICs Data

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Network of discovered loci, eQTLs and metabolites
Genetical Statistics and Systems Biology

Data for visualisation of associations and causal relationsships of SNPs, gene expression, and metabolites based on 1,856 individuals of the LIFE Heart study

Creator: Markus Scholz

Submitter: Christoph Beger

Data file type: Other OMICs Data

Human Diseases: kidney disease

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1 hidden item
Shiny App for managing next-cycle thrombopenia
HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles

Implementation of recently developed dynamic mathematical models of normal and leukemic hematopoiesis to practically impact clinical decision- making.

Fitting available individual patients information, prediction of next-cycle thrombopenia caused by CHOEP treatment based on the individual fits of the preceeding treatment cycles, changing next-cycle relative dosing, posponement of the next cycle, changing follow-up period, visualization of data and simulation

Creator: Markus Scholz

Submitter: René Hänsel

External Link
Network of discovered loci, eQTLs and metabolites
Genetical Statistics and Systems Biology

This is an interactive version of figure 4 of the publication „Integration of Genome-Wide SNP Data and Gene-Expression Profiles Reveals Six Novel Loci and Regulatory Mechanisms for Amino Acids and Acylcarnitines in Whole Blood“.

Creator: Markus Scholz

Submitter: René Hänsel

External Link
Epidemiological COVID-19 model LeipzigIMISE-SECIR
Genetical Statistics and Systems Biology, Task Force COVID-19 Leipzig

A principled approach to parametrize SIR-type epidemiologic models of different complexities by embedding the model structure as a hidden layer into a general Input-Output Non-Linear Dynamical System (IO-NLDS). Non-explicitly modelled impacts on the system are imposed as inputs of the system. Observable data are coupled to hidden states of the model by appropriate data models considering possible biases of the data. We estimate model parameters including their time-dependence by a Bayesian knowledge ...

Creators: Markus Scholz, Holger Kirsten, Yuri Kheifetz

Submitter: Holger Kirsten

eQTL-Search
Genetical Statistics and Systems Biology

This shiny app facilitates the download and searching of the summary statistics from "Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci" (https://doi.org/10.1093/hmg/ddv194).

Creators: Markus Scholz, Carl Beuchel, Holger Kirsten

Submitter: Carl Beuchel

External Link
CAP Severity Scores
Genetical Statistics and Systems Biology

This Shiny-App implements the calculation of several CAP (Community-Aquired-Pneumonia) severity scores for one or multiple patients based on user-updated data.

Creators: Markus Scholz, Maciej Rosolowski, Carl Beuchel

Submitter: Carl Beuchel

External Link View content
HT12ProcessoR: Preprocessing ILLUMINA HT12v4 data intended for project up to thousands of samples
Genetical Statistics and Systems Biology

Preprocessing Illumina HT12v4 gene expression data including quality filtering, data transformation and normalisation and batch-effect removal as well as visualisation

Creators: Markus Scholz, Holger Kirsten

Submitter: Christoph Beger

External Link
The Platform for modeling of hematopoiesis and personalized control of hematopoietical side effects during chemotherapy
Genetical Statistics and Systems Biology
No description specified

Creators: Markus Scholz, Carl Beuchel, Yuri Kheifetz, Sibylle Schirm

Submitter: Carl Beuchel

External Link View content
Bulletin COVID-19 Leipzig 2022-03-22
Task Force COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony. This work was done as part of the NFDI4Health Task Force COVID-19 (nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 451265285.

nfdi4health.de

Creators: Holger Kirsten, Torsten Thalheim, Markus Scholz, Markus Löffler

Submitter: René Hänsel

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Bulletin COVID-19 Leipzig 2022-11-28
Task Force COVID-19 Leipzig

Summary of the current COVID-19 pandemic development in Leipzig and Saxony. This work was done as part of the NFDI4Health Task Force COVID-19 (nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 451265285.

nfdi4health.de

Creators: Holger Kirsten, Markus Löffler, Markus Scholz, Torsten Thalheim, Radosław dzikowski, Yuri Kheifetz, Tyll Krüger, Tomasz Ożański, Marcin Bodych, Maciej Filiński

Submitter: René Hänsel

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Bulletin COVID-19 Leipzig 2021-03-18
Task Force COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony. This work was done as part of the NFDI4Health Task Force COVID-19 (nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 451265285.

nfdi4health.de

Creators: Holger Kirsten, Markus Scholz, Markus Löffler, Peter Ahnert, Anne Dietrich, Dirk Hasenclever, Matthias Horn, Yuri Kheifetz, Tyll Krüger, Sibylle Schirm

Submitter: Christoph Beger

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Bulletin COVID-19 Leipzig 2020-10-16
Task Force COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony. This work was done as part of the NFDI4Health Task Force COVID-19 (nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 451265285.

nfdi4health.de

Creators: Holger Kirsten, Markus Löffler, Markus Scholz, Peter Ahnert, Matthias Horn, Yuri Kheifetz, Kolja Nenoff, Sibylle Schirm

Submitter: Christoph Beger

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Bulletin COVID-19 Leipzig 2020-06-30
Task Force COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony. This work was done as part of the NFDI4Health Task Force COVID-19 (nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 451265285.

nfdi4health.de

Creators: Holger Kirsten, Markus Löffler, Markus Scholz, Peter Ahnert, Matthias Horn, Yuri Kheifetz, Kolja Nenoff, Sibylle Schirm

Submitter: Christoph Beger

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Bulletin COVID-19 Leipzig 2020-05-28
Task Force COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony. This work was done as part of the NFDI4Health Task Force COVID-19 (nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 451265285.

nfdi4health.de

Creators: Holger Kirsten, Markus Scholz, Markus Löffler, Peter Ahnert, Matthias Horn, Yuri Kheifetz, Kolja Nenoff, Sibylle Schirm

Submitter: Christoph Beger

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Bulletin COVID-19 Leipzig 2020-05-04
Task Force COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony. This work was done as part of the NFDI4Health Task Force COVID-19 (nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 451265285.

nfdi4health.de

Creators: Holger Kirsten, Markus Scholz, Markus Löffler, Peter Ahnert, Matthias Horn, Yuri Kheifetz, Sibylle Schirm

Submitter: Christoph Beger

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Bulletin COVID-19 Leipzig 2020-04-26
Task Force COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony. This work was done as part of the NFDI4Health Task Force COVID-19 (nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 451265285.

nfdi4health.de

Creators: Holger Kirsten, Markus Scholz, Markus Löffler, Peter Ahnert, Matthias Horn, Yuri Kheifetz, Sibylle Schirm

Submitter: Christoph Beger

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Bulletin COVID-19 Leipzig 2020-04-13
Task Force COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony. This work was done as part of the NFDI4Health Task Force COVID-19 (nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 451265285.

nfdi4health.de

Creators: Holger Kirsten, Markus Scholz, Markus Löffler, Peter Ahnert, Matthias Horn, Yuri Kheifetz, Sibylle Schirm

Submitter: Christoph Beger

Download
Bulletin COVID-19 Leipzig 2020-04-19
Task Force COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony. This work was done as part of the NFDI4Health Task Force COVID-19 (nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 451265285.

nfdi4health.de

Creators: Holger Kirsten, Markus Scholz, Markus Löffler, Peter Ahnert, Matthias Horn, Yuri Kheifetz, Sibylle Schirm

Submitter: Christoph Beger

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LIFE Management Cluster
No description specified

Projects: LIFE Heart, LIFE - Leipzig Research Center for Civilization Diseases, LIFE HNC - Head and Neck Cancer Group, SepNet - German Competence Network Sepsis, GC-HNPCC - German Consortium for Hereditary Non-Polyposis Colorectal Cancer, LIFE Child, GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer, LIFE Adult

Web page: https://www.uniklinikum-leipzig.de/einrichtungen/life

NFDI - German National Research Data Infrastructure

In the German National Research Data Infrastructure (NFDI), valuable data from science and research are systematically accessed, networked and made usable in a sustainable and qualitative manner for the entire German science system. Up to now, they have mostly been available on a decentralised, project-related or temporary basis. The NFDI aims to create a permanent digital repository of knowledge as an indispensable prerequisite for new research questions, findings and innovations. Relevant data ...

Projects: NFDI4Health, Task Force COVID-19 Leipzig, NFDI4Health - TA3 Services, Clinical Trials Leipzig

Web page: https://www.nfdi.de/?lang=en

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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.

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