Metabolic disorders, psychosocial aspects and cardiac arrhythmias: data-analysis and clinical study

Description

In recent years a bulk of evidence have been produced on the interlink between cardiac metabolism and risk of cardiac arrhythmias. It has been shown also how psychosocial factors are intertwined with glycaemic and lipidic metabolism of the heart in predisposing and triggering cardiac arrhythmias. The description of such molecular interlink has paved the way to important clinical opportunities both for interventional approaches and prevention of the disease.

The aim of these PhD is to explore in clinical available large dataset the association between alteration in metabolism and psychosocial factors in determining the arrhythmic risk. Possible role of drugs, life style modification and psychological therapy in modifying the risk will be explored.

 

Objective:

  • Identify impact of metabolic active medication on arrhythmic risk
  • Define psychosocial aspects linked to arrhythmias susceptibility
  • Describe the correlation between metabolic disorder and psychosocial profile.

This PhD will be developed in three main different WPs:

WP1: In this WP the PhD student will explore in different data base the correlation between metabolic disorders (diabetes, dyslipidaemia) and risk of arrhythmias. The effects of different medications both on metabolism and arrhythmias may be investigated.

WP2: In this WP correlation between psychosocial factors and risk of arrhythmias are considered. As for example the association between the expression of negative emotions and risk of atrial fibrillation.

WP3: In this WP a correlation between psychosocial profile and metabolic disorder will be identified. As example the impact of sleep disorders on the hormonal and metabolic changes leading to arrhythmias.

Method

The PhD project includes a diverse method which will be finalized according to applicant interests and expertise, including data analysis using large cohort data (e.g., the UK Bio Bank), designing clinical study in collaboration with local hospital and primary care, and laboratory metabolomics experiments.

Funding note:

This project is offered to self-funded PhD candidates with a background in epidemiology, health science or data science related to healthcare data with interest in sarcopenia, cardiovascular diseases, metabolomic. Experience of large datasets, statistical analysis, designing clinical study would be highly desirable. A BSc/MSc/MRes in data science, biology, or related fields, or a health-related subject is required.

PhD training:

All postgraduate students undertake the PGR Development Programme which aims to enhance their skills for a successful research experience and career. They are required to maintain an online record of their progress and record their personal and professional development throughout their research degree. In addition to monthly supervision meetings, The Liverpool Centre for Cardiovascular Science holds monthly group research meetings where students are given opportunities to present their research. The PhD student will receive training from clinical and academic experts in appropriate methodologies, including conducting systematic reviews, data analysis, academic writing, and applying for ethics approval to conduct clinical research. The Institute of Life Course and Medical Science is fully committed to promoting gender equality in all activities. In recruitment we emphasize the supportive nature of the working environment and the flexible family support that the University provides. The Institute holds a silver Athena SWAN award in recognition of on-going commitment to ensuring that the Athena SWAN principles are embedded in its activities and strategic initiatives. 

Supervisory team

The supervisory team consists of multi-disciplinary experts in epidemiology, data analysis, metabolomic and supporting patients with sarcopenia, frailty, and cardiovascular conditions. Embedded within the Institute of Life Course and Medical Science, Liverpool Centre for Cardiovascular Science and Institute of Systems, Molecular and Integrative Biology. This project encompasses a multidisciplinary collaboration.

Required skills: use of statistical software, large database analysis, scientific writing.

 

Name and email address to direct enquiries to: riccardo.proietti@liverpool.ac.uk