Development of a multi-scale integrative framework for subtyping hypertension
Background & Objectives
The knowledge generated in the MINDSHIFT research programme will span a wide variety of methodologies and system levels, reflecting the multi-factorial and multi-disciplinary nature of hypertension. Data will include e.g. clinical characteristics, functional and structural measurements and imaging data, blood biomarkers and -omics data; whilst models include human, experimental and computational domains, across the scale range from genes to population. Ultimately, this collective intelligence must benefit the individual patient and the larger population. The objectives for the ESR4 project hence are:
1. To review methodologies and models in hypertension research and develop in collaboration with fellow ESRs an integrative model framework, allowing integration of knowledge across scales.
2. To critically review current definitions of hypertension classes with respect to underlying vascular causes, at the organ and organ-system levels, and develop a more pathophysiology-informed scheme for subtyping hypertension.
3. To develop an integrative approach facilitating optimal communication between patient and physician, to achieve the best possible and sustainable vascular health condition.
The project will involve the following key methodologies:
- systematic literature review on modelling and classification of hypertension, to identify gaps in hypertension subtyping;
- develop quantitative insight into system and organ level causes of systolic and diastolic hypertension, utilising an existing biophysical model of the circulation (www.circadapt.org);
- study the following model domains in collaboration with other ESRs: graph/network models, multiple regression models, biophysical/biochemical models, and control systems models;
- conceive a multi-scale model framework, to capture subtyping information across the genetic-to-patient levels, and design an evaluation protocol to assess the framework’s robustness and validity;
- conceive and implement, in collaboration with patients, an integrated approach (e.g. questionnaire, interviewing, e-health tools) to support and enhance patient-physician interaction, based on the framework’s insights.
For the project, three supporting secondments are planned to develop skills and widen the scientific scope. These include 2 months at the Zennaro lab at UP on genome-wide case-control association studies (GWAS), 5+2 months at TMC Data Science on design, development and verification of model frameworks, and 1+2 months at Microlife AG on user-oriented e-health solutions
- Qualifications: MSc biomedical engineering/sciences, or bioinformatics, or equivalent
- Experience: Data science or biomedical engineering project, if possible combined with patient-based research / interviewing
- Knowledge & skills:Statistics and methodology; systems theory; programming skills; system design and evaluation, bioinformatics/data modelling.
- Abilities: Excellent analytical as well as communication skills, proactive project planning and time management, integration of multi-disciplinary information and context
- Attitude and disposition: Highly enthusiastic about research and willing to learn; creative and collaborative attitude; affinity with patient care/disease prevention/e-health