Translational medicine identifies novel gene targets in vascular disease
sysVASC
The EU funded sysVASC project is a bench to bedside program with a systems biology approach to identify molecular targets for cardiovascular disease treatment. Eagle Genomics lead the data analysis work package. The Eagle Genomics' task was to organize and harness the value of sysVASC scientific and patient data in the context of publicly available information on therapeutic gene targets. This allowed rapid prioritization of candidate targets for further experimental analysis.
Objectives
Cardiovascular disease (CVD) describes a multitude of clinical conditions and varies in degrees of severity. It is believed that the development of the disease is triggered by early functional and structural changes in the vessels that lead to multiple discomfort symptoms and even organ damage.
The early disease pathways (pathophysiological changes) of CVD are not very well understood. While earlier stages are, in part, reversible, their diagnosis is challenging due to the patients experiencing no symptoms. Screenings may need specialized equipment to characterize the underlying problem and often are not carried out due to the lack of symptoms. The vascular damage accumulates for years before patients are identified and offered therapeutic treatment. Advanced stages or critical events are not always the immediate consequence of earlier disease processes which adds further complexity to the disease and its diagnosis.
Approach
The sysVASC consortium compiled the required clinical resources, technological infrastructure, including advanced biotechnology tools, multi-disciplinary skills and expertise to tackle the challenge of defining a comprehensive, systems medicine-based characterisation of CVD to aid identification of novel therapeutic targets.
Eagle Genomics used the e[datascientist] platform to ingest, curate and annotate sysVASC and public patient data to build a catalogue of patient biomolecular data, clinical phenotypes and therapeutic targets. This restricted data repository provided sysVASC consortium members with federated access to all project resources. With the data prepared and integrated, biomolecular screens were performed using machine learning to predict associations between genes and clinical phenotypes.
The team simultaneously captured categories required for data valuation (association of target with CVD, druggability of target, safety/criticality of target and novelty of target) and built a hierarchical AI valuation model.
The model was used to score all human genes according to their value as novel therapeutic targets for CVD. Candidate targets emerging from sysVASC biomolecular association screens were analyzed in the context of the overall value distribution thus allowing us to prioritize those candidates to progress to the next stage of experimental validation.
Results
Asymptomatic vascular damage accumulates for years before patients are identified and subjected to therapeutic measures. The limited knowledge on early vascular disease triggers is reflected in the lack of therapeutic options. sysVASC aims to overcome this limitation by connecting comprehensive systems approaches to explain pathological mechanisms, which will yield molecular targets for therapeutic intervention.
Eagle Genomics’ e[datascientist] platform has enabled sysVASC to increase insight into the following aspects of macrovascular disease:
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Health risk: The major clinical cardiovascular types, myocardial infarction and stroke, are triggered by pathological changes in large vessels.
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Clinical challenge: Despite pathological changes in large arteries patients may remain asymptomatic. Identification of patients at highest risk remains challenging.
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Research models: A wide range of animal models are available that copy human macrovascular disease that can help the extend research and improve screening for the various cardiovascular types.
Cardiovascular disease (CVD) is a general term that describes all diseases of the heart and/or circulating blood vessels and is the leading cause of mortality and morbidity worldwide. The main types of CVD are coronary artery disease (CAD), stroke, peripheral arterial disease and aortic disease. An estimated 17.7 million people died from CVDs in 2015, representing 31% of all global deaths. Of these deaths, an estimated 7.4 million were due to coronary artery disease and 6.7 million were due to stroke.
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