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Genetical Statistics and Systems Biology

Overview
Motivation:

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.

Description:

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 group aims to develop and apply statistical and bioinformatic methods in genetics. This comprises e.g. the planning and conduction of studies, the management and analysis of high-dimensional molecular genetic data (germ line mutations, tumour cell line mutations, expression data, metabolomics), population genetics and integrative genome analyses. The work is accompanied by statistical or continuous modelling of diseases or physiological processes. For this purpose, we cooperate with different national and international study groups of different disease entities or phenotypes.

Programme: This Project is not associated with a Programme

Health Atlas ID: 7Q0CTG2ND8-7

Funding codes:
  • BMBF
  • ESF
  • Freistaat Sachsen

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

Organisms: Homo sapiens

Human Diseases: No Human Disease specified

Health Atlas PALs: Markus Scholz

Project Coordinators: No Project coordinators for this Project

Project start date: 1st Jan 2013

Project Hierarchy

Related items

OMICS Investigations
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Resutls of different OMICS-level using LIFE Adult and LIFE Heart data are presented (Publications, Supplemental Data, & Summary Statistics).

Snapshots: No snapshots

GWAS Pulse Wave Velocity
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

We analysed if measuring PWV in different segments of the body leads to association with different genetic variants, as well as different heritability and different genetic correlation with other biological traits. Furthermore we searched for shared genetic architecture concerning PWV, blood pressure (BP) and coronary artery disease (CAD) and examined the causal relationship between PWV and BP.

Person responsible: Janne Pott

Snapshots: No snapshots

Study type: Genetic study

GWAS Carotid Plaque Burden
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

We defined six operationalizations of CPB considering plaques in common carotid arteries, carotid bulb, and internal carotid arteries (maximal plaque area, mean plaque area, sum of plaque areas at all six regions, maximal degree of stenosis, mean degree of stenosis, and sum of stenosis at all six regions).
Link to publication (PMID, DOI), Supplemental Figures and Tables, and Summary Statistics of GWAS will be made available upon acceptance of our manuscript.

Person responsible: Janne Pott

Snapshots: No snapshots

Study type: Genetic study

GWAS Steroid Hormones
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Supplement Data for Publication including Supplement Material & Results (eQTL annotation, Mendelian Randomization (MR), further significant loci), Figures (correlation plot of steroid hormones, scatter plot of genetic effect sizes, regional association plots, scatter plots of MR) and Tables (Correlations, GWAS summary statistics, interaction tests, MR results)

Person responsible: Janne Pott

Snapshots: No snapshots

Study type: Genetic study

1 hidden item
Summary Statistic for PWV GWAS
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

Summary statistics from GWAS of baPWV, bfPWV, cfPWV
All samples (adjusted for age, sex and log_sys)

These data is intended for research purposes only.

Citation: tbc

When using this data acknowledge the source as follows: 'Data on PWV has been contributed by LIFE-Adult investigators and has been downloaded from https://www.health-atlas.de/assays/34'

For any enquiries about the datasets, please contact Michael Rode (michael.rode@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de)
...

Submitter: Michael Rode

Resource type: Genome Wide Association

Technology type: SNP Array

Snapshots: No snapshots

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

We are releasing the summary data from our GWAS of carotid plaque burden 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:

When using this data acknowledge the source as follows: 'Data on carotid plaque burden has been contributed by LIFE-Adult investigators and has been downloaded from https://www.health-atlas.de/assays/31 '

For any
...

Submitter: Janne Pott

Resource type: Genome Wide Association

Technology type: SNP Array

Snapshots: No snapshots

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

Snapshots: No snapshots

Supplement Data
LIFE Adult, Genetical Statistics and Systems Biology, LIFE Heart

The primary goal of this study was to identify genetic loci associated with steroid hormone levels (cortisol, DHEA-S, testosterone, estradiol, progesterone, 17-hydroxyprogesterone, androstenedione, and aldosterone). In a secondary analysis, we searched for causal effects of steroid hormones on coronary artery disease.

Submitter: René Hänsel

Resource type: Experimental Assay Type

Technology type: Technology Type

Snapshots: No snapshots

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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

Summary Statistics for BS_WTH_THIGH_AVERAGE
Genetical Statistics and Systems Biology, LIFE Adult
No description specified

Creator: Andreas Kühnapfel

Submitter: Andreas Kühnapfel

Data file type: Not specified

Summary Statistics for BS_WTH
Genetical Statistics and Systems Biology, LIFE Adult
No description specified

Creator: Andreas Kühnapfel

Submitter: Andreas Kühnapfel

Data file type: Not specified

Summary Statistics for BS_WT
Genetical Statistics and Systems Biology, LIFE Adult
No description specified

Creator: Andreas Kühnapfel

Submitter: Andreas Kühnapfel

Data file type: Not specified

Summary Statistics for BS_WRIST_GTH_AVERAGE
Genetical Statistics and Systems Biology, LIFE Adult
No description specified

Creator: Andreas Kühnapfel

Submitter: Andreas Kühnapfel

Data file type: Not specified

Summary Statistics for BS_WRIST_GTH
Genetical Statistics and Systems Biology, LIFE Adult
No description specified

Creator: Andreas Kühnapfel

Submitter: Andreas Kühnapfel

Data file type: Not specified

2 hidden items
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
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

Bulletin COVID-19 Leipzig 2021-01-10
COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony.

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

Submitter: Christoph Beger

Download
Bulletin COVID-19 Leipzig 2020-12-11
COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony.

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

Submitter: Christoph Beger

Download
Bulletin COVID-19 Leipzig 2020-12-30
COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony.

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

Submitter: Christoph Beger

Download
Bulletin COVID-19 Leipzig 2020-11-15
COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony.

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

Submitter: Christoph Beger

Download
Bulletin COVID-19 Leipzig 2020-04-07
COVID-19 Leipzig, Genetical Statistics and Systems Biology

Summary of the current COVID-19 pandemic development in Leipzig and Saxony.

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

Submitter: Christoph Beger

Download
Carl Beuchel

Projects: LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, Genetical Statistics and Systems Biology

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

Katrin Horn

Projects: LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, LIFE Heart, Genetical Statistics and Systems Biology

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

https://orcid.org/0000-0002-5307-6936
René Hänsel adminproject_administratorasset_housekeeperasset_gatekeeperprogramme_administrator

Projects: LHA - Leipzig Health Atlas, LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, LIFE HNC - Head and Neck Cancer Group, LIFE Heart, MMML - Molecular mechanisms in malignant lymphoma, GLA - German Lymphoma Alliance, MMML Demonstrators - Molecular Mechanisms in Malignant Lymphomas - Demonstrators of Personalized Medicine, HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles, GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer, GC-HNPCC - German Consortium for Hereditary Non-Polyposis Colorectal Cancer, MMML-MYC-SYS, NLP4CR - Natural Language Processing for Clinical Research, Genetical Statistics and Systems Biology, SepNet - German Competence Network Sepsis, LIFE Child, HNPCC-Sys - Genomic and transcriptomic heterogeneity of colorectal tumours arising in Lynch syndrome, GGN - German Glioma Network, CAPSys - Footprints of Sepsis Framed Within Community Acquired Pneumonia in the Blood Transcriptome, ProstataCA, SMITH - Smart Medical Information Technology for Healthcare, COVID-19 Leipzig, Management of health information systems

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

https://orcid.org/0000-0001-8344-0658
Andreas Kühnapfel

Projects: LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, LIFE Heart, Genetical Statistics and Systems Biology

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

https://orcid.org/0000-0003-3668-0784
Janne Pott project_administratorasset_housekeeper

Projects: LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, LIFE Heart, Genetical Statistics and Systems Biology

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

https://orcid.org/0000-0002-5983-5331

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