Project Summary
This Project aims to Identify patients at risk of developing an irregular heart rhythm (atrial fibrillation) by identifying early changes to predict atrial dysfunction. Additionally, the aim is to find new therapies to treat the underlying cardiomyopathy rather than waiting for them to develop atrial fibrillation.
What is the issue for NSW?
Atrial Fibrillation is the most common clinical arrhythmia and is a major health care and economic burden; it is the second most common reason for cardiovascular admission to hospital (exceeded only by coronary artery disease.) The incidence of atrial fibrillation is projected to double in the next twenty years. To overcome this growing healthcare burden we need to tackle the problem at its source, by identification and treatment of the underlying atrial cardiomyopathy and thereby prevent patients developing atrial fibrillation in the first place.
What does the research aim to do and how?
This study will develop a novel algorithm, combining established clinical factors with electrocardiographic and cardiac imaging parameters, to diagnose patients with atrial cardiomyopathy. Patient genetics will also be evaluated to develop polygenic risk scores.
Using in vitro organoid models, this study will also develop a high throughput drug screening platform to identify new (or repurposed) drugs to treat atrial cardiomyopathy and prevent atrial fibrillation from occurring in the first place.
This research will:
- Establish a clinically useful definition for atrial cardiomyopathy
- Establish cohorts that can be evaluated in future for defining the natural history of atrial cardiomyopathy
- Identify therapeutic targets to improve treatment of atrial cardiomyopathy, preventing its progression to atrial fibrillation.
Collaborating Organisations:
Western Sydney Local Health District
The University of Sydney
Westmead Hospital
Victor Chang Cardiac Research Institute
South Western Clinical School, UNSW
St Vincent’s Hospital Sydney
Hunter New England Local Health District
The University of Newcastle
The University of New South Wales
The Centre for Big Data in health research, UNSWS
Nepean Blue Mountains Local Health District