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Author: Toralf Kirsten6
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

Der Leipzig Health Atlas
LHA - 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

Longitudinal anthropometry of children and adolescents using 3D-body scanning.
LIFE - Leipzig Research Center for Civilization Diseases, LIFE Child

Abstract (Expand)

3D-body scanning anthropometry is a suitable method for characterization of physiological development of children and adolescents, and for understanding onset and progression of disorders like overweight … and obesity. Here we present a novel body typing approach to describe and to interpret longitudinal 3D-body scanning data of more than 800 children and adolescents measured in up to four follow-ups in intervals of 1 year, referring to an age range between 6 and 18 years. We analyzed transitions between body types assigned to lower-, normal- and overweight participants upon development of children and adolescents. We found a virtually parallel development of the body types with only a few transitions between them. Body types of children and adolescents tend to conserve their weight category. 3D body scanning anthropometry in combination with body typing constitutes a novel option to investigate onset and progression of obesity in children.

Authors: H. Loeffler-Wirth, M. Vogel, T. Kirsten, F. Glock, T. Poulain, A. Korner, M. Loeffler, W. Kiess, H. Binder

Date Published: 14th Sep 2018

Publication Type: Not specified

Human Diseases: obesity

Body typing of children and adolescents using 3D-body scanning.
LIFE Child

Abstract (Expand)

Three-dimensional (3D-) body scanning of children and adolescents allows the detailed study of physiological development in terms of anthropometrical alterations which potentially provide early onset … markers for obesity. Here, we present a systematic analysis of body scanning data of 2,700 urban children and adolescents in the age range between 5 and 18 years with the special aim to stratify the participants into distinct body shape types and to describe their change upon development. In a first step, we extracted a set of eight representative meta-measures from the data. Each of them collects a related group of anthropometrical features and changes specifically upon aging. In a second step we defined seven body types by clustering the meta-measures of all participants. These body types describe the body shapes in terms of three weight (lower, normal and overweight) and three age (young, medium and older) categories. For younger children (age of 5-10 years) we found a common 'early childhood body shape' which splits into three weight-dependent types for older children, with one or two years delay for boys. Our study shows that the concept of body types provides a reliable option for the anthropometric characterization of developing and aging populations.

Authors: H. Loeffler-Wirth, M. Vogel, T. Kirsten, F. Glock, T. Poulain, A. Korner, M. Loeffler, W. Kiess, H. Binder

Date Published: 21st Oct 2017

Publication Type: Not specified

Human Diseases: obesity

The LIFE-Adult-Study: objectives and design of a population-based cohort study with 10,000 deeply phenotyped adults in Germany.
LIFE Adult, Genetical Statistics and Systems Biology

Abstract (Expand)

BACKGROUND: The LIFE-Adult-Study is a population-based cohort study, which has recently completed the baseline examination of 10,000 randomly selected participants from Leipzig, a major city with 550,000 … inhabitants in the east of Germany. It is the first study of this kind and size in an urban population in the eastern part of Germany. The study is conducted by the Leipzig Research Centre for Civilization Diseases (LIFE). Our objective is to investigate prevalences, early onset markers, genetic predispositions, and the role of lifestyle factors of major civilization diseases, with primary focus on metabolic and vascular diseases, heart function, cognitive impairment, brain function, depression, sleep disorders and vigilance dysregulation, retinal and optic nerve degeneration, and allergies. METHODS/DESIGN: The study covers a main age range from 40-79 years with particular deep phenotyping in elderly participants above the age of 60. The baseline examination was conducted from August 2011 to November 2014. All participants underwent an extensive core assessment programme (5-6 h) including structured interviews, questionnaires, physical examinations, and biospecimen collection. Participants over 60 underwent two additional assessment programmes (3-4 h each) on two separate visits including deeper cognitive testing, brain magnetic resonance imaging, diagnostic interviews for depression, and electroencephalography. DISCUSSION: The participation rate was 33 %. The assessment programme was accepted well and completely passed by almost all participants. Biomarker analyses have already been performed in all participants. Genotype, transcriptome and metabolome analyses have been conducted in subgroups. The first follow-up examination will commence in 2016.

Authors: M. Loeffler, C. Engel, P. Ahnert, D. Alfermann, K. Arelin, R. Baber, F. Beutner, H. Binder, E. Brahler, R. Burkhardt, U. Ceglarek, C. Enzenbach, M. Fuchs, H. Glaesmer, F. Girlich, A. Hagendorff, M. Hantzsch, U. Hegerl, S. Henger, T. Hensch, A. Hinz, V. Holzendorf, D. Husser, A. Kersting, A. Kiel, T. Kirsten, J. Kratzsch, K. Krohn, T. Luck, S. Melzer, J. Netto, M. Nuchter, M. Raschpichler, F. G. Rauscher, S. G. Riedel-Heller, C. Sander, M. Scholz, P. Schonknecht, M. L. Schroeter, J. C. Simon, R. Speer, J. Staker, R. Stein, Y. Stobel-Richter, M. Stumvoll, A. Tarnok, A. Teren, D. Teupser, F. S. Then, A. Tonjes, R. Treudler, A. Villringer, A. Weissgerber, P. Wiedemann, S. Zachariae, K. Wirkner, J. Thiery

Date Published: 22nd Jul 2015

Publication Type: Not specified

Human Diseases: disease of mental health, mental depression, vascular disease, allergic hypersensitivity disease, sleep disorder, retinal degeneration

The comprehensive IT-Infrastructure for epidemiological Research in LIFE
LIFE - Leipzig Research Center for Civilization Diseases

Abstract (Expand)

Introduction LIFE is a large epidemiological study aiming at causes of common civilization diseases including adiposity, dementia, and depression. Participants of the study are probands and patients. … Probands are randomly selected and invited from the set of Leipzig (Germany) inhabitants while patients with known diseases are recruited from several local hospitals. The management of these participants, their invitation and contact after successful attendance as well as the support of nearly all ambulance processes requires a complex ambulance management. Each participant is examined by a set of investigation instruments including interviews, questionnaires, device-specific investigations, specimen extrac- tions and analyses. This necessitates a complex management of the participantspecific examination program but also specific input forms and systems allowing to capture administrative (measurement and process environment or specific set-ups) and scientific data. Additionally, the taken and prepared specimens need to be labeled and registered from which participant they stem and in which fridge or bio-tank they are stored. At the end, all captured data from ambu- lance management, investigation instruments and laboratory analyses need to be integrated before they can be analyzed. These complex processes and requirements necessitate a comprehensive IT-infrastructure. Methods Our IT-infrastructure modularly consists of several software applications. A main application is responsible for the complex participant and ambulance man- agement. The participant management cope with selected participant data and contact information. To protect participant’s privacy, a participant identifier (PID) is created for each participant that is associated to all data which is managed and captured in the following. In ambulance management, each participant is associated with a predefined investigation program. This investigation program is represented in our systems by a tracking card that is available as print-out and electronically. The electronic version of tracking cards is utilized by two software applications, the Assessment Battery and the CryoLab. The former system coordinates the input of scientific data into online input forms. The input forms are designed in the open source system LimeSurvey. Moreover, the Assessment Battery is used to monitor the input process, i.e., it shows which investigations are already completed and which of them are still to do. The Cryolab system registers and tracks all taken specimens and is used to annotate extraction and specific preparation processes, e.g., for DNA isolation. Moreover, it tracks specimen storage in fridges and bio-tanks. A central component is the metadata repository collecting metadata from ambulance management and data input systems. It is the base for the integra- tion of relevant scientific data into a central research database. The integration follows a mapping-based approach. The research database makes raw data and special pre-computations called derivatives available for later data analysis. Results & Discussion We designed and implemented a complex and comprehensive IT-infrastructure for the epidemiological research in LIFE. This infrastructure consists of several software applications which are loosely coupled over specified interfaces. Most of the software applications are new implementations; only for capturing scientific data external software application are applied.

Authors: Toralf Kirsten, A. Kiel, M. Kleinert, R. Speer, M. Rühle, Hans Binder, Markus Löffler

Date Published: 30th Sep 2013

Publication Type: Not specified

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