Hypertrophic cardiomyopathy (HCM) affects approximately 1 in 500 people and is a leading cause of inherited heart disease. The condition is characterised by abnormal thickening of the heart muscle, which can increase the risk of heart failure, arrhythmias, stroke and sudden cardiac death. Although many cases are caused by inherited genetic variants, there is considerable variation in how the disease develops and progresses, even among individuals carrying the same genetic change. 

Current clinical tools used to assess risk in patients with HCM rely largely on conventional two-dimensional imaging measurements. However, these approaches do not fully capture the complexity and diversity of disease expression, limiting clinicians’ ability to accurately predict outcomes and tailor treatment to individual patients. 

Lara‘s research aims to address this challenge by combining advanced cardiac imaging, machine learning and genetic data to develop more personalised approaches to risk prediction. Her fellowship project, Precision Phenotyping of Hypertrophic Cardiomyopathy: A Machine Learning Approach to Gene-Environment Interactions and Risk Prediction, will investigate why patients with HCM experience different disease trajectories and outcomes. 

The project will also explore how genetic and environmental factors interact to influence disease severity and progression. By examining these gene-environment interactions, Lara hopes to better understand the biological mechanisms underlying variability in HCM and identify opportunities for more personalised prevention and treatment strategies. 

Lara is undertaking this fellowship as part of the Chain Florey Training Programme, which supports early-career clinician scientists working at the interface of discovery science and patient care through structured research training, mentorship and protected academic time. Alongside the fellowship, she will continue her cardiology training, with 60% clinical training and 40% protected research time. This integrated approach enables her to maintain her clinical expertise while developing advanced skills in computational cardiovascular research, providing a strong foundation for the interdisciplinary work supported by the BHF Fellowship and her progression towards an independent clinician scientist career. 

The BHF Fellowship provides dedicated support for outstanding early-career researchers undertaking innovative cardiovascular research with the potential to transform patient care. Through this fellowship, Lara will build on her expertise at the intersection of cardiology, genetics, imaging and data science, helping to develop new approaches to understanding and managing inherited heart disease.