BIOBRIDGE
Integrative Genomics and Chronic Disease Phenotypes:
modelling and simulation tools for clinicians
(FP6-2005-LIFESCIHEALTH-7, LSHG-CT-2006-037939)
Publishable Executive Summary
The Biobridge (http://www.biobridge.eu) project was build-up around a well defined clinical problem
that is the analysis of the systemic effects in three highly prevalent chronic conditions: chronic
obstructive pulmonary disease (COPD), chronic heart failure (CHF) and diabetes type II. Hallmark
features of the systemic effects are skeletal muscle dysfunction and muscle wasting.
The project seeks to enhance the biomedical understanding of the underlying mechanisms
explaining the systemic effects of the target disorders. Recent publications indicate that the
pathogenesis of the systemic effects may share common mechanisms in the three conditions. It
has been suggested that the nitroso-redox unbalance of the cardiovascular system accounts for
functional heterogeneities (O2 uptake/O2 flow mismatching) at tissue level which may explain both
muscle dysfunction (mechanical-energetic uncoupling) and abnormal tissue remodelling seen in
these patients.
It is documented that the presence of systemic effects conforms disease phenotypes associated to
high use of healthcare resources and to poor prognosis. However, the complexities of the
interactions between susceptibility (i.e. genetic determinants) and life style factors (i.e. low physical
activity, tobacco smoking, nutrition, etc...) put on display the insufficiencies of the classical
hypothesis-based research approach to effectively explore the underlying mechanisms determining
the clinical problem. It prompts the need for complementary novel strategies based on integrative
translational research using Systems Biology methodologies. Consequently, Biobridge’s goals
were aligned in two well differentiated dimensions, biomedical and bioinformatics.
The operational aspects of the project required us to focus on one specific use case. We decided
to explore the effects of skeletal muscle endurance training in healthy subjects and in COPD
patients. To this end, we analyzed different levels of the system (blood, skeletal muscle and wholebody bioenergetics) with multidimensional assessments (physiological measurements, genomics,
proteomics and metabolomics) in two different protocols (3-w and 8-w training periods) done in
different sets of subjects. Each of the studies including three subsets of individuals: healthy
sedentary subjects (C), COPD patients without muscle wasting (COPDN) and COPD patients with
muscle wasting (COPDL). A large study aiming at analyzing relationships between body mass
composition and exercise capacity in COPD patients was also undertaken. Animal experiments
and cell culture protocols were done to answer specific questions generated through the
bioinformatics approach. Cardiac failure and diabetes type II were approached through data
mining. Moreover, muscle dysfunction in diabetes type II patients was explored through inference
analysis using public datasets and the results were compared with systemic effects seen in COPD
patients and with those observed in other degenerative muscle diseases.
Besides the novelties emerging from the results of the experimental designs, the project has
generated biological knowledge through the simulation environment. We have also done relevant
contributions in several bioinformatic dimensions. Main achievements in this field were those
related with multilevel data integration; development of SBML standards ensuring interoperability
among different ICT tools; development of deterministic modelling of oxygen transport-central
metabolism and mitochondrial ROS generation; preparing tools for inference analysis and
probabilistic modelling; and, integration of simulation environment into the Biobridge portal. At the
end of the project, Biobridge:
• Is a web-based portal for integrative analysis of biomedical data that can address
diverse, but well defined, use cases through future developments
• The portal is designed for the access to different types of users
• Provides tools for inference analysis
• Is prepared to become a knowledge management application interoperable with other
ICT platforms
The Biobridge consortium included complementary expertises from the academic and commercial
(SMEs) sectors that allowed a multidisciplinary approach to the challenges addressed in the
project. There has been a high degree of adherence to the project with strong interactions among
partners that explains several key achievements during the project, as described below:
• Well structured bio-informatic developments and novelty of experimental results
• Carefully designed publication and dissemination policies
• Social infrastructure for systems medicine
• Well identified goals for further developments beyond Biobridge
Last but not least, the elaboration of future business prospective has also been an important
component generating the formulation of specific strategies for future developments based on
interactions between adoption of novel Integrated Care services for chronic patients based on
open ICT platforms and Systems Biology developments. The concept is displayed in the figure
below illustrating the need for adoption of a new paradigm for biomedical research based on
iterations between healthcare and academic research (“from bedside to bench and back to
bedside “).
The success in deployment of integrated care services in our area and the networking with other
platforms are generating strong synergies that will help to foster the business strategies articulated
in Biobridge. Moreover, the bioinformatics platform allows generalization, such that the simulation
environment generated within the project should be useful to address other clinical problems.
We understand that the analysis of the six work-packages (WPs) included in the project show a
very high and uniform degree of accomplishment of the corresponding tasks relative to the initial
calendar of the description of work.
The results of the project will help to pave the way for predictive medicine for complex
chronic diseases leading to personalized health strategies targeting chronic patients at
early disease stages.