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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

LHA-ID: 7Q0CTG2ND8-7

Funding codes:
  • Freistaat Sachsen
  • ESF
  • BMBF

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

Human Diseases: No Human Disease specified

Leipzig Health Atlas PALs: Markus Scholz

Project Coordinators: No Project coordinators for this Project

Project start date: 1st Jan 2013

Project Hierarchy

Related items

Carl Beuchel

Projects: Genetical Statistics and Systems Biology

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

René Hänsel adminproject_administratorasset_housekeeperasset_gatekeeperprogramme_administrator

Projects: Leipzig Health Atlas, LIFE Adult, LIFE- Leipzig Research Center for Civilization Diseases, LIFE Head and Neck Cancer Group, LIFE Heart, Molecular mechanisms in malignant lymphoma, German Lymphoma Alliance (GLA), Molecular Mechanisms in Malignant Lymphomas - Demonstrators of Personalized Medicine, Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles, German Consortium for Hereditary Breast and Ovarian Cancer, German Consortium for Hereditary Non-Polyposis Colorectal Cancer, MMML-MYC-SYS, Natural Language Processing for Clinical Research, Genetical Statistics and Systems Biology, German Competence Network Sepsis (SepNet), LIFE Child, Genomic and transcriptomic heterogeneity of colorectal tumours arising in Lynch syndrome, Footprints of Sepsis Framed Within Community Acquired Pneumonia in the Blood Transcriptome, ProstataCA

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

https://orcid.org/0000-0001-8344-0658
Janne Pott asset_gatekeeper

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
Markus Scholz palproject_administrator

Projects: LIFE Heart, LIFE- Leipzig Research Center for Civilization Diseases, Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles, Genetical Statistics and Systems Biology

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

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

Different GWAS results using LIFE Adult and LIFE Heart data are presented (Publication, Supplemental Data, & Summary Statistics).

Snapshots: No snapshots

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

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 Heart, Genetical Statistics and Systems Biology, LIFE Adult

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

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

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
...

Contributor: Janne Pott

Assay type: Genome Wide Association

Technology type: SNP Array

Snapshots: No snapshots

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

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.

Contributor: René Hänsel

Assay type: Experimental Assay Type

Technology type: Technology Type

Snapshots: No snapshots

1 hidden item
Summary Statistics for Cortisol
Genetical Statistics and Systems Biology

Summary statistics from meta GWAS of cortisol for
- all samples (adjusted for age, log(BMI) and sex)
- men only (adjusted for age and log(BMI))
- women only (adjusted for age and log(BMI))

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 the source as
...

Creator: Janne Pott

Contributor: Janne Pott

Data file type: OMICs Data

Download
Summary Statistics for DHEAS
Genetical Statistics and Systems Biology

Summary statistics from meta GWAS of DHEAS for
- all samples (adjusted for age, log(BMI) and sex)
- men only (adjusted for age and log(BMI))
- women only (adjusted for age and log(BMI))

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 the source as follows:
...

Creator: Janne Pott

Contributor: Janne Pott

Data file type: OMICs Data

Download
Summary Statistics for Testosterone
Genetical Statistics and Systems Biology

Summary statistics from meta GWAS of testosterone for
- all samples (adjusted for age, log(BMI) and sex)
- men only (adjusted for age and log(BMI))
- women only (adjusted for age and log(BMI))

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 the source as
...

Creator: Janne Pott

Contributor: Janne Pott

Data file type: OMICs Data

Download
Summary Statistics for Estradiol
Genetical Statistics and Systems Biology

Summary statistics from meta GWAS of estradiol for
- all samples (adjusted for age, log(BMI) and sex)
- men only (adjusted for age and log(BMI))
- women only (adjusted for age and log(BMI))

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 the source as
...

Creator: Janne Pott

Contributor: Janne Pott

Data file type: OMICs Data

Download
Summary Statistics for Progesterone
Genetical Statistics and Systems Biology

Summary statistics from meta GWAS of progesterone for
- all samples (adjusted for age, log(BMI) and sex)
- men only (adjusted for age and log(BMI))
- women only (adjusted for age and log(BMI))

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 the source as
...

Creator: Janne Pott

Contributor: Janne Pott

Data file type: OMICs Data

Download
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: Christoph Beger, Holger Kirsten

Contributor: Christoph Beger

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“.

Creators: René Hänsel, Markus Scholz

Contributor: René Hänsel

Metabolite-Investigator: Shiny-Tool for investigation of metabolite-covariate relationships
Genetical Statistics and Systems Biology

The main goal is to provide a principled analysis workflow addressing specific issues of mass-spectrometry metabolite measurements in the context of testing in multiple studies with a high number of hypotheses

Shiny-Application of an analysis pipeline for preprocessing, association and covariate selection of metabolite data with clinical and lifestyle factors in one or more seperate studies. Preprocessing steps include transformation, outlier filtering and batch-adjustment. Analyses include uni-
...

Creator: Carl Beuchel

Contributor: Carl Beuchel

View content
Clinical and lifestyle related factors influencing whole blood metabolite levels -- A comparative analysis of three large cohorts
Genetical Statistics and Systems Biology

Abstract (Expand)

Objective Human blood metabolites are influenced by a number of lifestyle and environmental factors. Identification of these factors and the proper quantification of their relevance provides insights …s into human biological and metabolic disease processes, is key for standardized translation of metabolite biomarkers into clinical applications, and is a prerequisite for comparability of data between studies. However, so far only limited data exist from large and well-phenotyped human cohorts and current methods for analysis do not fully account for the characteristics of these data. The primary aim of this study was to identify, quantify and compare the impact of a comprehensive set of clinical and lifestyle related factors on metabolite levels in three large human cohorts. To achieve this goal, we improve current methodology by developing a principled analysis approach, which could be translated to other cohorts and metabolite panels. Methods 63 Metabolites (amino acids, acylcarnitines) were quantified by liquid chromatography tandem mass spectrometry in three cohorts (total N~=~16,222). Supported by a simulation study evaluating various analytical approaches, we developed an analysis pipeline including preprocessing, identification, and quantification of factors affecting metabolite levels. We comprehensively identified uni- and multivariable metabolite associations considering 29 environmental and clinical factors and performed metabolic pathway enrichment and network analyses. Results Inverse normal transformation of batch corrected and outlier removed metabolite levels accompanied by linear regression analysis proved to be the best suited method to deal with the metabolite data. Association analyses revealed numerous uni- and multivariable significant associations. 15 of the analyzed 29 factors explained {\textgreater}1{\%} of variance for at least one of the metabolites. Strongest factors are application of steroid hormones, reticulocytes, waist-to-hip ratio, sex, haematocrit, and age. Effect sizes of factors are comparable across studies. Conclusions We introduced a principled approach for the analysis of MS data allowing identification, and quantification of effects of clinical and lifestyle factors with metabolite levels. We detected a number of known and novel associations broadening our understanding of the regulation of the human metabolome. The large heterogeneity observed between cohorts could almost completely be explained by differences in the distribution of influencing factors emphasizing the necessity of a proper confounder analysis when interpreting metabolite associations.

Authors: Carl Beuchel, Susen Becker, Julia Dittrich, Holger Kirsten, Anke Toenjes, Michael Stumvoll, Markus Loeffler, Holger Thiele, Frank Beutner, Joachim Thiery, Uta Ceglarek, Markus Scholz

Date Published: 17th Aug 2019

Journal: Molecular Metabolism

Human Diseases: Not specified

Genetic association study of eight steroid hormones and implications for sexual dimorphism of coronary artery disease
LIFE Heart, Genetical Statistics and Systems Biology, LIFE Adult

Abstract (Expand)

CONTEXT: Steroid hormones are important regulators of physiological processes in humans and are under genetic control. A link to coronary artery disease (CAD) is supposed. OBJECTIVE: Our main objective …e was to identify genetic loci influencing steroid hormone levels. As secondary aim, we searched for causal effects of steroid hormones on CAD. DESIGN: We conducted genome-wide meta-association studies for eight steroid hormones: cortisol, DHEA-S, estradiol and testosterone in two independent cohorts (LIFE-Adult, LIFE-Heart, max. n=7667), and progesterone, 17-hydroxyprogesterone, androstenedione and aldosterone in LIFE-Heart only (max. n=2070). All genome-wide significant loci were tested for sex interactions. Further, we tested if previously reported CAD SNPs were associated with our steroid hormone panel and investigated causal links between hormone levels and CAD status using Mendelian Randomization (MR) approaches. RESULTS: We discovered 15 novel associated loci for 17-hydroxyprogesterone, progesterone, DHEA-S, cortisol, androstenedione, and estradiol. Five of these loci relate to genes directly involved in steroid metabolism: CYP21A1, CYP11B1, CYP17A1, STS, and HSD17B12, almost completing the set of steroidogenic enzymes with genetic associations. Sexual dimorphisms were found for seven of the novel loci. Other loci correspond, e.g., to the WNT4/β-catenin pathway. MR revealed that cortisol, androstenedione, 17-hydroxyprogesterone and DHEA-S had causal effects on CAD. We also observed enrichment of cortisol and testosterone associations among known CAD hits. CONCLUSION: Our study greatly improves insight into genetic regulation of steroid hormones and their dependency on sex. These results could serve as a basis for analyzing sex-dimorphisms in other complex diseases.

Authors: Janne Pott, YJ. Bae, K. Horn, A. Teren, Andreas Kühnapfel, H. Kirsten, U. Ceglarek, Markus Löffler, J. Thiery, J. Kratzsch, Markus Scholz

Date Published: 6th Jun 2019

Journal: Journal of Clinical Endocrinology & Metabolism

Human Diseases: coronary artery disease

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.
Genetical Statistics and Systems Biology

Abstract (Expand)

Profiling amino acids and acylcarnitines in whole blood spots is a powerful tool in the laboratory diagnosis of several inborn errors of metabolism. Emerging data suggests that altered blood levels of … amino acids and acylcarnitines are also associated with common metabolic diseases in adults. Thus, the identification of common genetic determinants for blood metabolites might shed light on pathways contributing to human physiology and common diseases. We applied a targeted mass-spectrometry-based method to analyze whole blood concentrations of 96 amino acids, acylcarnitines and pathway associated metabolite ratios in a Central European cohort of 2,107 adults and performed genome-wide association (GWA) to identify genetic modifiers of metabolite concentrations. We discovered and replicated six novel loci associated with blood levels of total acylcarnitine, arginine (both on chromosome 6; rs12210538, rs17657775), propionylcarnitine (chromosome 10; rs12779637), 2-hydroxyisovalerylcarnitine (chromosome 21; rs1571700), stearoylcarnitine (chromosome 1; rs3811444), and aspartic acid traits (chromosome 8; rs750472). Based on an integrative analysis of expression quantitative trait loci in blood mononuclear cells and correlations between gene expressions and metabolite levels, we provide evidence for putative causative genes: SLC22A16 for total acylcarnitines, ARG1 for arginine, HLCS for 2-hydroxyisovalerylcarnitine, JAM3 for stearoylcarnitine via a trans-effect at chromosome 1, and PPP1R16A for aspartic acid traits. Further, we report replication and provide additional functional evidence for ten loci that have previously been published for metabolites measured in plasma, serum or urine. In conclusion, our integrative analysis of SNP, gene-expression and metabolite data points to novel genetic factors that may be involved in the regulation of human metabolism. At several loci, we provide evidence for metabolite regulation via gene-expression and observed overlaps with GWAS loci for common diseases. These results form a strong rationale for subsequent functional and disease-related studies.

Authors: R. Burkhardt, H. Kirsten, F. Beutner, L. M. Holdt, A. Gross, A. Teren, A. Tonjes, S. Becker, K. Krohn, P. Kovacs, M. Stumvoll, D. Teupser, J. Thiery, U. Ceglarek, Markus Scholz

Date Published: 25th Sep 2015

Journal: PLoS Genet

Human Diseases: kidney disease

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding locidagger.
Genetical Statistics and Systems Biology

Abstract (Expand)

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most … genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes.

Authors: H. Kirsten, H. Al-Hasani, L. Holdt, A. Gross, F. Beutner, K. Krohn, K. Horn, P. Ahnert, R. Burkhardt, K. Reiche, J. Hackermuller, Markus Löffler, D. Teupser, J. Thiery, Markus Scholz

Date Published: 15th Aug 2015

Journal: Hum Mol Genet

Human Diseases: Not specified

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

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)

Creator: René Hänsel

Contributor: René Hänsel

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