Dr. Winnie Chua and Professor Jon Deeks are studying blood biomarkers to predict atrial fibrillation, which affects 1 in 4 people over 40 and can cause stroke, heart failure, and dementia. They found that two markers, BNP and FGF23, combined with age, sex, and BMI, predict AF occurrence and recurrence more accurately than current methods.
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I'm Dr. Winnie Chua, and I'm a postdoctoral researcher at the Institute of Cardiovascular Sciences.
And I'm Jon Deeks. I'm Professor of Biostatistics at the Institute of Applied Health Research.
Together, we are working to discover and evaluate biomarkers associated with atrial fibrillation so that we can protect every heartbeat, transforming patient care to fight stroke, heart failure, and sudden death. 1 in 4 people above the age of 40 will develop atrial fibrillation during their lifetime. We now know that people with atrial fibrillation are more likely to have a stroke, develop heart failure, sudden death, as well as experience cognitive decline and dementia. To prevent these cardiovascular-related complications, detecting and treating atrial fibrillation early is key. One of the ways we can do this is by using biomarkers.
Biomarkers are increasingly being used in medicine to screen for disease, to make diagnoses, to predict which treatments will work best in which patients, and to monitor how well treatments work and monitor side effects. Doing good studies of biomarkers, large, strong, robust studies, is really important to understand their statistical properties, which enables us to optimise their use for the benefit of patients.
These biomarkers are often measured in body fluids such as blood, and they contain a lot of important information about our heart's health.
When used well, biomarkers will help us be able to diagnose heart disease, detect its severity, and to work out which treatment should be given to each patient. Predicting who's going to develop atrial fibrillation and whether or not it recurs is currently very difficult. We're looking to evaluate a whole set of new biomarkers which we are hoping will enable us to predict the occurrence and recurrence of atrial fibrillation much better, which should lead us to be able to give better management to patients.
We have recently discovered that a peptide called BNP, as well as a hormone called FGF23, when combined with simple characteristics such as age, sex, and body mass index, is able to help us predict patients with atrial fibrillation well. And we are currently in the midst of validating this model in wider and bigger datasets.
