Understanding the genetic causes of spontaneous coronary artery dissection

Ms Ingrid Tarr, University of New South Wales

Postgraduate Scholarship

Years funded: 2025 - 2027

Advancing genetic understanding of spontaneous coronary artery dissection

Spontaneous coronary artery dissection (SCAD) is a potentially fatal cause of acute coronary syndrome which typically occurs in young, otherwise healthy women. Until very recently, it has been under-diagnosed and under-researched, unsurprisingly, large knowledge gaps remain. Recent genetic studies have identified strong evidence of a role for common genetic variants in SCAD risk. The individual variants identified have known relationships with other traits suggesting genetic overlap, including antagonistic genetic relationships with atherosclerosis. On the other hand, very few plausible candidate genes for an approximately monogenic cause of SCAD have been identified. Rare variants in genes associated with vasculopathies have been identified, generally in sporadic SCAD patients, suggesting a potential role for rare variants in some proportion of cases.

Exploring rare and common genetic variants in SCAD

This project aims to explore the role of rare variants, identify additional common variants, investigate the interaction between rare and common variants, and gain insight into genetic differences between men and women experiencing SCAD.

To achieve this, I will analyse the largest known cohort of pedigrees with multiple SCAD-affected individuals to identify plausible rare variants and to analyse these in the context of the burden of common variants, via a polygenic risk score. I will secondly analyse a cohort of male SCAD patients, who represent a small fraction of SCAD cases, to further target rare variants, and by comparing these males to our existing cohort of female SCAD patients who have undergone in-depth genetic analysis, gain insight into the genetic differences between male and female patients. Finally, I will apply cutting edge bioinformatic analyses to publicly available datasets for traits related to SCAD to gain new insight into common variants associated with SCAD.

The outcome of this work will be an advanced genetic understanding of disease, which will inform mechanistic studies and will ultimately be clinically translatable through offering genetic diagnoses and risk prediction for patients and relatives, thus working towards personalised management for a poorly understood condition.