A BREAKTHROUGH in research surrounding disease risk prediction for diseases like heart disease and Alzheimer’s dementia has been made.
Researchers across the University of Edinburgh, Optima Partners and Biogen have used AI to analyse large amounts of medical data from the UK BioBank to identify protein patterns linked to disease risk.
This method saw positive results as researchers accurately predicted someone’s risk of disease 10 years before a diagnosis.
A marker of inflammation called GDF15 was one of the proteins that was investigated and was found to be linked to 11 out of 23 of the diseases being studied.
The research advises on how the protein patterns could be compared with results from currently used patient blood tests to detect a patients risk of a specific disease later in life.
This would allow a plan to be developed and measures to be taken much sooner to improve the patients outcome.
Data was analysed using almost 50,000 individuals blood samples from between 2006 and 2010 which helped improve predictions for disease up to 15 years.
Dr Danni Gadd, the first author of the study, stated: “Our research represents a promising step forward in risk prediction.
“It’s encouraging to see how much potential there is from a single blood sample that allow us to predict a range of disease outcomes.
“Being able to detect early warning signs for a broad set of conditions may lead to opportunities for early intervention and prevention, marking a significant moment for the healthcare industry.”
Dr Chris Foley, managing director and chief scientist of Optima Partners said: “More work is still needed to convert these findings for practical use in clinical settings.
“However, our discoveries set strong foundations for the inclusion of new risk prediction signatures to shed a light on possible pathways and mechanisms that underlie diseases.
“Pattern recognition like this would not be possible without modern machine learning technology and its capacity to analyse data at this scale and will in turn allow us to address some of the most pressing healthcare challenges of our time.”
