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Leipzig Health Atlas

Overview
Description:

The Leipzig Health Atlas (LHA) 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 in which our team has scientific and clinical expertise.

Programme: This Project is not associated with a Programme

LHA-ID: 7VV367KHEC-9

Funding codes:
  • 031L0026

Public web page: https://www.health-atlas.de

Organisms: Homo sapiens

Human Diseases: No Human Disease specified

Leipzig Health Atlas PALs: Markus Löffler

Project start date: 1st Apr 2016

Project end date: 28th Feb 2021

Related items

Christoph Beger adminproject_administratorasset_housekeeper

Projects: Leipzig Health Atlas, LIFE- Leipzig Research Center for Civilization Diseases, Onto-Med Research Group, COVID-19 Leipzig

Institutions: Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig

https://orcid.org/0000-0002-1166-0368
LHA Data Portal Bot

Projects: Leipzig Health Atlas, LIFE- Leipzig Research Center for Civilization Diseases, German Lymphoma Alliance (GLA), German Competence Network Sepsis (SepNet)

Institutions: University of Leipzig

René Hänsel adminproject_administratorasset_housekeeperasset_gatekeeperprogramme_administrator

Projects: Leipzig Health Atlas, German Consortium for Hereditary Breast and Ovarian Cancer, LIFE- Leipzig Research Center for Civilization Diseases, LIFE Adult, German Lymphoma Alliance (GLA), LIFE Head and Neck Cancer Group, Footprints of Sepsis Framed Within Community Acquired Pneumonia in the Blood Transcriptome, Genetical Statistics and Systems Biology, Genomic and transcriptomic heterogeneity of colorectal tumours arising in Lynch syndrome, German Consortium for Hereditary Non-Polyposis Colorectal Cancer, German Glioma Network, German Competence Network Sepsis (SepNet), Natural Language Processing for Clinical Research, LIFE Heart, Molecular mechanisms in malignant lymphoma, 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, LIFE Child, MMML-MYC-SYS, ProstataCA, COVID-19 Leipzig

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

https://orcid.org/0000-0001-8344-0658
Admin Istrator admin

Projects: Leipzig Health Atlas

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

Markus Löffler pal

Projects: Leipzig Health Atlas, LIFE Adult, German Lymphoma Alliance (GLA), LIFE Head and Neck Cancer Group, German Competence Network Sepsis (SepNet), Molecular mechanisms in malignant lymphoma, Molecular Mechanisms in Malignant Lymphomas - Demonstrators of Personalized Medicine, MMML-MYC-SYS, HaematoSys - Systems biology of haematopoiesis and haematopoietic neoplasia, SMITH

Institutions: Institute for Medical Informatics, Statistics and Epidemiology

PhenoMan Evaluation with Synthetic FHIR Data
Leipzig Health Atlas, Onto-Med Research Group, SMITH

We evaluated if the PhenoMan returns correct/complete result sets and if it is working with real data. To simulate a FHIR health data store with real data we used Synthea(TM) to generate a large data set and imported it into a HAPI FHIR JPA Server. Based on the synthetic data set we developed ten example queries with different structure and complexity with PhenoMan and SQL. We compared the results of the queries in means of execution time and equality of results.

The detailed steps of the evaluation
...

Person responsible: Christoph Beger

Snapshots: No snapshots

Study type: Not specified

Ontological Modelling of Basic Eligibility Criteria
Leipzig Health Atlas, Onto-Med Research Group, SMITH
No description specified

Person responsible: Alexandr Uciteli

Snapshots: No snapshots

Study type: Not specified

Ontological Modelling of Type 2 Diabetes Mellitus (T2DM) Phenotype
Leipzig Health Atlas, Onto-Med Research Group, SMITH
No description specified

Person responsible: Alexandr Uciteli

Snapshots: No snapshots

Study type: Not specified

PhenoMan Evaluation - Synthetic FHIR Data
Leipzig Health Atlas, Onto-Med Research Group, SMITH

This assay bundles all synthetic FHIR data of the PhenoMan evaluation. The data arised from a subset of a Synthea(TM) generated data set.
We truncated some resource types like Encounter and Provider to reduce the size of the data set and to speed up the import in a FHIR health data store.

Submitter: Christoph Beger

Assay type: Result Dataset of Clinical Study

Technology type: Technology Type

Snapshots: No snapshots

Basic Eligibility Criteria of an Example Blood Pressure Study
Leipzig Health Atlas, Onto-Med Research Group, SMITH
No description specified

Submitter: Alexandr Uciteli

Biological problem addressed: Model Analysis Type

Snapshots: No snapshots

Ontological Modelling of T2DM Phenotype using Phenotype Manager (PhenoMan)
Leipzig Health Atlas, Onto-Med Research Group, SMITH

We modelled the algorithm for determining Type 2 Diabetes Mellitus (T2DM) cases presented by PheKB.org using Phenotype Manager (PhenoMan).

Submitter: Alexandr Uciteli

Biological problem addressed: Model Analysis Type

Snapshots: No snapshots

T2DM Ontology
Leipzig Health Atlas, Onto-Med Research Group, SMITH

T2DM Phenotype Algorithm Specification Ontology (PASO) developed using PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Download
T2DM Case 5 Reasoner Report
Leipzig Health Atlas, Onto-Med Research Group, SMITH

Example Reasoner Report generated by PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Download
T2DM Case 4 Reasoner Report
Leipzig Health Atlas, Onto-Med Research Group, SMITH

Example Reasoner Report generated by PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Download
T2DM Case 3 Reasoner Report
Leipzig Health Atlas, Onto-Med Research Group, SMITH

Example Reasoner Report generated by PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Download
T2DM Case 2 Reasoner Report
Leipzig Health Atlas, Onto-Med Research Group, SMITH

Example Reasoner Report generated by PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Download
Core Ontology of Phenotypes
Leipzig Health Atlas, Onto-Med Research Group

Core Ontology of Phenotypes. Contribute to Onto-Med/COP development by creating an account on GitHub.

Creators: Alexandr Uciteli, Heinrich Herre, Christoph Beger

Submitter: Christoph Beger

External Link
Ontological Modelling and Reasoning of Phenotypes
Leipzig Health Atlas, Onto-Med Research Group, SMITH

Abstract (Expand)

The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and epidemiological … studies. The development of computable phenotype algorithms to solve these tasks is a challenging problem, caused by various reasons. Firstly, the term ‘phenotype’ has no generally agreed definition and its meaning depends on context. Secondly, the phenotypes are most commonly specified as non-computable descriptive documents. Recent attempts have shown that ontologies are a suitable way to handle phenotypes and that they can support clinical research and decision making. The SMITH Consortium is dedicated to rapidly establish an integrative medical informatics framework to provide physicians with the best available data and knowledge and enable innovative use of healthcare data for research and treatment optimization. In the context of a methodological use case “phenotype pipeline” (PheP), a technology to automatically generate phenotype classifications and annotations based on electronic health records (EHR) is developed. A large series of phenotype algorithms will be implemented. This implies that for each algorithm a classification scheme and its input variables have to be defined. Furthermore, a phenotype engine is required to evaluate and execute developed algorithms. In this article we present a Core Ontology of Phenotypes (COP) and a software Phenotype Manager (PhenoMan), which implements a novel ontology-based method to model and calculate phenotypes. Our solution includes an enhanced iterative reasoning process combining classification tasks with mathematical calculations at runtime. The ontology as well as the reasoning method were successfully evaluated based on different phenotypes (including SOFA score, socioeconomic status, body surface area and WHO BMI classification) and several data sets.

Authors: Alexandr Uciteli, Christoph Beger, Toralf Kirsten, Frank A. Meineke, Heinrich Herre

Date Published: 20th Dec 2019

Publication Type: Proceedings

Der Leipzig Health Atlas
Leipzig Health Atlas

Abstract (Expand)

Die Notwendigkeit des Managements von Forschungsdaten ist von der Forschungscommunity erkannt – Sponsoren, Gesetzgeber, Verlage erwarten und fördern die Einhaltung der guten wissenschaftlichen Praxis, … was nicht nur die Archivierung umfasst, sondern auch die Verfügbarkeit von Forschungsdaten- und ergebnissen im Sinne der FAIR-Prinzipien. Der Leipzig Health Atlas (LHA) ist ein Projekt zur Präsentation und zum Austausch eines breiten Spektrums von Publikationen, (bio) medizinischen Daten (z.B. klinisch, epidemiologisch, molekular), Modellen und Tools z.B. zur Risikoberechnung in der Gesundheitsforschung. Die Verbundpartner decken hierbei einen breiten Bereich wissenschaftlicher Disziplinen ab, beginnend von medizinischer Systembiologie über klinische und epidemiologische Forschung bis zu ontologischer und dynamischer Modellierung. Derzeit sind 18 Forschungskonsortien beteiligt (u.a. zu den Domänen Lymphome, Gliome, Sepsis, Erblicher Darm- und Brustkrebs), die Daten aus klinischen Studien, Patientenkohorten, epidemiologischen Kohorten, teilweise mit umfangreichen molekularen und genetischen Profilen, sammeln. Die Modellierung umfasst algorithmische Phänotypklassifizierung, Risikovorhersage und Krankheitsdynamik. Wir konnten in einer ersten Entwicklungsphase zeigen, dass unsere webbasierte Plattform geeignet ist, um (1) Methoden zur Verfügung zu stellen, um individuelle Patientendaten aus Publikationen für eine Weiternutzung zugänglich zu machen, (2) algorithmische Werkzeuge zur Phänotypisierung und Risikoprofilerstellung zu präsentieren, (3) Werkzeuge zur Durchführung dynamischer Krankheits- und Therapiemodelle interaktiv verfügbar zu machen und (4) strukturierte Metadaten zu quantitativen und qualitativen Merkmalen bereit zu stellen. Die semantische Datenintegration liefert hierzu die Technologien (Ontologien und Datamining Werkzeuge) für die (semantische) Datenintegration und Wissensanreicherung. Darüber hinaus stellt sie Werkzeuge zur Verknüpfung eigener Daten, Analyseergebnisse, öffentlich zugänglicher Daten- und Metadaten-Repositorien sowie zur Verdichtung komplexer Daten zur Verfügung. Eine Arbeitsgruppe zur Applikationsentwicklung und –validierung entwickelt innovative paradigmatische Anwendungen für (1) die klinische Entscheidungsfindung für Krebsstudien, die genetische Beratung, für Risikovorhersagemodelle sowie Gewebe- und Krankheitsmodelle und (2) Anwendungen (sog. Apps), die sich auf die Charakterisierung neuer Phänotypen (z.B. ‚omics‘-Merkmale, Körpertypen, Referenzwerte) aus epidemiologischen Studien konzentrieren. Diese Anwendungen werden gemeinsam mit klinischen Experten, Genetikern, Systembiologen, Biometrikern und Bioinformatikern spezifiziert. Der LHA stellt Integrationstechnologie bereit und implementiert die Anwendungen für die User Communities unter Verwendung verschiedener Präsentationswerkzeuge bzw. Technologien (z.B. R-Shiny, i2b2, Kubernetes, SEEK). Dazu ist es erforderlich, die Daten und Metadaten vor dem Hochladen zu kuratieren, Erlaubnisse der Datenbesitzer einzuholen, die erforderlichen Datenschutzkriterien zu berücksichtigen und semantische Annotationen zu überprüfen. Zudem werden die zugelieferten Modellalgorithmen in einer qualitätsgesicherten Weise aufbereitet und, soweit anwendbar, online interaktiv zur Verfügung gestellt. Der LHA richtet sich insbesondere an die Zielgruppen Kliniker, Epidemiologen, Molekulargenetiker, Humangenetiker, Pathologen, Biostatistiker und Modellierer ist aber unter www.healthatlas.de öffentlich zugänglich – aus rechtlichen Gründen erfordert der Zugriff auf bestimmte Applikationen und Datensätze zusätzliche Autorisierung. Das Projekt wird über das BMBF Programm i:DSem (Integrative Datensemantik für die Systemmedizin, Förderkennzeichen 031L0026) gefördert.

Authors: F. A. Meineke, Sebastian Stäubert, Matthias Löbe, C. Beger, René Hänsel, A. Uciteli, H. Binder, T. Kirsten, M. Scholz, H. Herre, C. Engel, Markus Löffler

Date Published: 19th Sep 2019

Publication Type: Misc

Teratogenic Rubella Virus Alters the Endodermal Differentiation Capacity of Human Induced Pluripotent Stem Cells.
Leipzig Health Atlas

Abstract (Expand)

The study of congenital virus infections in humans requires suitable ex vivo platforms for the species-specific events during embryonal development. A prominent example for these infections is rubella … virus (RV) which most commonly leads to defects in ear, heart, and eye development. We applied teratogenic RV to human induced pluripotent stem cells (iPSCs) followed by differentiation into cells of the three embryonic lineages (ecto-, meso-, and endoderm) as a cell culture model for blastocyst- and gastrulation-like stages. In the presence of RV, lineage-specific differentiation markers were expressed, indicating that lineage identity was maintained. However, portrait analysis of the transcriptomic expression signatures of all samples revealed that mock- and RV-infected endodermal cells were less related to each other than their ecto- and mesodermal counterparts. Markers for definitive endoderm were increased during RV infection. Profound alterations of the epigenetic landscape including the expression level of components of the chromatin remodeling complexes and an induction of type III interferons were found, especially after endodermal differentiation of RV-infected iPSCs. Moreover, the eye field transcription factors RAX and SIX3 and components of the gene set vasculogenesis were identified as dysregulated transcripts. Although iPSC morphology was maintained, the formation of embryoid bodies as three-dimensional cell aggregates and as such cellular adhesion capacity was impaired during RV infection. The correlation of the molecular alterations induced by RV during differentiation of iPSCs with the clinical signs of congenital rubella syndrome suggests mechanisms of viral impairment of human development.

Authors: N. C. Bilz, E. Willscher, H. Binder, J. Bohnke, M. L. Stanifer, D. Hubner, S. Boulant, U. G. Liebert, C. Claus

Date Published: 10th Aug 2019

Publication Type: Not specified

Population Levels Assessment of the Distribution of Disease-Associated Variants With Emphasis on Armenians - A Machine Learning Approach.
Leipzig Health Atlas

Abstract (Expand)

Background: During the last decades a number of genome-wide association studies (GWASs) has identified numerous single nucleotide polymorphisms (SNPs) associated with different complex diseases. However, … associations reported in one population are often conflicting and did not replicate when studied in other populations. One of the reasons could be that most GWAS employ a case-control design in one or a limited number of populations, but little attention was paid to the global distribution of disease-associated alleles across different populations. Moreover, the majority of GWAS have been performed on selected European, African, and Chinese populations and the considerable number of populations remains understudied. Aim: We have investigated the global distribution of so far discovered disease-associated SNPs across worldwide populations of different ancestry and geographical regions with a special focus on the understudied population of Armenians. Data and Methods: We have used genotyping data from the Human Genome Diversity Project and of Armenian population and combined them with disease-associated SNP data taken from public repositories leading to a final dataset of 44,234 markers. Their frequency distribution across 1039 individuals from 53 populations was analyzed using self-organizing maps (SOM) machine learning. Our SOM portrayal approach reduces data dimensionality, clusters SNPs with similar frequency profiles and provides two-dimensional data images which enable visual evaluation of disease-associated SNPs landscapes among human populations. Results: We find that populations from Africa, Oceania, and America show specific patterns of minor allele frequencies of disease-associated SNPs, while populations from Europe, Middle East, Central South Asia, and Armenia mostly share similar patterns. Importantly, different sets of SNPs associated with common polygenic diseases, such as cancer, diabetes, neurodegeneration in populations from different geographic regions. Armenians are characterized by a set of SNPs that are distinct from other populations from the neighboring geographical regions. Conclusion: Genetic associations of diseases considerably vary across populations which necessitates health-related genotyping efforts especially for so far understudied populations. SOM portrayal represents novel promising methods in population genetic research with special strength in visualization-based comparison of SNP data.

Authors: M. Nikoghosyan, S. Hakobyan, A. Hovhannisyan, H. Loeffler-Wirth, H. Binder, A. Arakelyan

Date Published: 21st May 2019

Publication Type: Not specified

Autoimmunity and autoinflammation: A systems view on signaling pathway dysregulation profiles.
Leipzig Health Atlas

Abstract (Expand)

INTRODUCTION: Autoinflammatory and autoimmune disorders are characterized by aberrant changes in innate and adaptive immunity that may lead from an initial inflammatory state to an organ specific damage. … These disorders possess heterogeneity in terms of affected organs and clinical phenotypes. However, despite the differences in etiology and phenotypic variations, they share genetic associations, treatment responses and clinical manifestations. The mechanisms involved in their initiation and development remain poorly understood, however the existence of some clear similarities between autoimmune and autoinflammatory disorders indicates variable degrees of interaction between immune-related mechanisms. METHODS: Our study aims at contributing to a holistic, pathway-centered view on the inflammatory condition of autoimmune and autoinflammatory diseases. We have evaluated similarities and specificities of pathway activity changes in twelve autoimmune and autoinflammatory disorders by performing meta-analysis of publicly available gene expression datasets generated from peripheral blood mononuclear cells, using a bioinformatics pipeline that integrates Self Organizing Maps and Pathway Signal Flow algorithms along with KEGG pathway topologies. RESULTS AND CONCLUSIONS: The results reveal that clinically divergent disease groups share common pathway perturbation profiles. We identified pathways, similarly perturbed in all the studied diseases, such as PI3K-Akt, Toll-like receptor, and NF-kappa B signaling, that serve as integrators of signals guiding immune cell polarization, migration, growth, survival and differentiation. Further, two clusters of diseases were identified based on specifically dysregulated pathways: one gathering mostly autoimmune and the other mainly autoinflammatory diseases. Cluster separation was driven not only by apparent involvement of pathways implicated in adaptive immunity in one case, and inflammation in the other, but also by processes not explicitly related to immune response, but rather representing various events related to the formation of specific pathophysiological environment. Thus, our data suggest that while all of the studied diseases are affected by activation of common inflammatory processes, disease-specific variations in their relative balance are also identified.

Authors: A. Arakelyan, L. Nersisyan, D. Poghosyan, L. Khondkaryan, A. Hakobyan, H. Loffler-Wirth, E. Melanitou, H. Binder

Date Published: 4th Nov 2017

Publication Type: Not specified

16th Leipzig Research Festival for Life Sciences
No description specified

Start Date: 30th Jan 2020

End Date: 30th Jan 2020

Event Website: https://conference.uni-leipzig.de/researchfestival/

Country:  Germany

City: Leipzig

„Forschungsdaten in Sachsen: Planen – Organisieren – Nachnutzen“ – 1. sächsische FDM-Tagung

The conference will focus on current contributions to research data management in Saxony. On the basis of practical reports and a poster session, it will be shown what research data management can achieve and what advantages it can offer. An advanced training course on data management planning will help to explore the possibilities and challenges of the FDM for oneself and for research projects. Finally, important aspects and questions will be discussed with each other and with experts at several
...

Start Date: 19th Sep 2019

End Date: 19th Sep 2019

Event Website: https://saxfdm.de/termin/erste-saechsische-tagung-zum-forschungsdatenmanagement/

Country:  Germany

City: Dresden

Abstract: The Leipzig Health Atlas – A Repository for Research Data and Models
Leipzig Health Atlas

The publication of research results is part of good scientific practice and is increasingly ex-pected and demanded. The FAIR data principles of data sharing are an important guideline - even if medical data sharing makes it necessary to define access restrictions.

Creators: René Hänsel, Christoph Beger, Frank A. Meineke

Submitter: Christoph Beger

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Poster: The Leipzig Health Atlas - A Repository for Research Data and Models
Leipzig Health Atlas

The Leipzig Health Atlas (LHA) offers a platform for presentation and exchange of publications, (bio-) medical data, models and software tools
from the field of health research. The LHA is based on the FAIR Data Principles (Findable, Accessible, Interoperable, Reusable). Currently,
more than 18 research consortia contribute data from the domains lymphoma, glioma, sepsis, hereditary colorectal and breast cancer, and
others. Target groups are clinicians, epidemiologists, molecular geneticists, human
...

Creators: René Hänsel, Christoph Beger, Frank A. Meineke

Submitter: Christoph Beger

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Poster: Der Leipzig Health Atlas
Leipzig Health Atlas

The need to manage research data is recognised by the research community - sponsors, legislators, publishers expect and encourage good scientific practice, which not only includes archiving, but also the availability of research data and results in line with FAIR principles.
The publication gives a brief overview of the Leipzig Health Atlas (LHA), which is a project for the presentation and exchange of a wide range of publications, (bio) medical data (e.g. clinical, epidemiological, molecular),
...

Creators: René Hänsel, Sebastian Stäubert, Matthias Löbe, Christoph Beger

Submitter: Christoph Beger

Download
Abstract: Der Leipzig Health Atlas
Leipzig Health Atlas

The need to manage research data is recognised by the research community - sponsors, legislators, publishers expect and encourage good scientific practice, which not only includes archiving, but also the availability of research data and results in line with FAIR principles.
The publication gives a brief overview of the Leipzig Health Atlas (LHA), which is a project for the presentation and exchange of a wide range of publications, (bio) medical data (e.g. clinical, epidemiological, molecular),
...

Creators: René Hänsel, Sebastian Stäubert, Matthias Löbe, Christoph Beger

Submitter: Christoph Beger

Download

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Leipzig Health Atlas

The Leipzig Health Atlas 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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