gms | German Medical Science

63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

02. - 06.09.2018, Osnabrück

Healthspan pathway maps in model organisms and human

Meeting Abstract

  • Georg Fuellen - Universitätsmedizin Rostock, Institut für Biostatistik und Informatik in Medizin und Alternsforschung, Rostock, Deutschland
  • Steffen Möller - Rostock University Medical Center, Rostock, Deutschland
  • Nadine Saul - Humboldt-Universität Berlin, Berlin, Deutschland
  • Francesca Cirulli - Istituto Superiore di Sanità, Rom, Italien
  • Ludger Jansen - Ruhr-Universität Bochum, Bochum, Deutschland
  • Peter Antal - Budapest University of Technology and Economics, Budapest, Ungarn
  • Walter Luyten - KU Leuven, Löwen, Belgien

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Osnabrück, 02.-06.09.2018. Düsseldorf: German Medical Science GMS Publishing House; 2018. DocAbstr. 153

doi: 10.3205/18gmds162, urn:nbn:de:0183-18gmds1628

Published: August 27, 2018

© 2018 Fuellen et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at



Introduction: Knowing the molecular basis of health can help towards undoing its deterioration, and this should help to focus approaches towards undoing aging on the truly important goal: fostering well-being. However, a precise operational definition of health and healthspan is not straightforward, and its molecular basis is largely unknown.

Methods: Building upon previous work, we define health as the lack of major chronic diseases and dysfunctions. Based on an extensive review of the literature, we aggregate a list of features of health and healthspan, and of the genes and genetic variants associated with them. Clusters of these genes based on molecular interaction and biological process annotation data give rise to maps of healthspan pathways.

Results: We identify healthspan pathways for human, featuring transcription initiation, proliferation and cholesterol/lipid processing, and for C. elegans, featuring biosynthetic response, macro-autophagy and mitochondria. By mapping healthspan-related gene expression data, describing effects of caloric restriction associated with improvements in health, onto the healthspan pathway maps, we confirm, for example, the downregulation of the cell-cycle in C. elegans and of Notch signalling in human. The latter reflects the inflammatory role of Notch.

Discussion: Defining health accurately, and investigating its molecular determinants on a large scale, is still a major challenge. Our literature-based data corpus, including visualization, is being made available as a reference for future investigations.

A preprint of the full paper shall be available at biorxiv and via

Funding: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant agreement No 633589 (Aging with Elegans). This publication reflects only the authors’ views and the Commission is not responsible for any use that may be made of the information it contains.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.