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Graphic showing build-up of amyloid plaque between nerve cells in the brain.
Image showing amyloid plaque build-up in the brain.

The ATN framework is a means of classifying Alzheimer's disease in living people using biomarkers, which are the physiological traits that correspond to a disease. In this case, the biomarkers are features of the human brain which indicate a person is at risk of developing dementia.

The ATN framework groups biomarkers into their distinct pathological processes: amyloid-beta (A), tau (T) and neurodegeneration (N). Amyloid-beta and tau are different types of protein which can accumulate around brain cells, impairing their ability to function. Neurodegeneration is a more general term for the progressive loss of brain function.

Now, funding from DPUK has enabled a team of researchers – including Dr Vanessa Raymont, Professor John Gallacher and Dr Ivan Koychev from DPUK – to predict a person's ATN biomarkers using known risk factors. Dr Koychev said: 'In this paper we wanted to explore if we can predict who, among a group of cognitively healthy older adults, will have high levels of amyloid or tau protein and will have evidence for neurodegeneration – that is, if they were in preclinical Alzheimer's disease.'

The new paper, published in the journal Alzheimer's Research & Therapy, grouped over a thousand participants from the EPAD cohort in the DPUK Data Portal by the ATN biomarkers they possess. The researchers then measured them on a wide range of risk factors including genetics, physical health, sex, age, and lifestyle traits to determine which risk factors are associated with which ATN biomarkers.

The researchers found that each biomarker group differed on the following traits: age, family history, body-mass index (BMI), cognitive (thinking) ability, physical brain damage, and a certain gene subtype called APOE4. This means that knowing details such as a person's age, sex and whether they have the APOE4 gene can predict with 82% accuracy the biomarkers present in their brain without the need for invasive and expensive measurements. This new methodology has improved the accuracy of existing biomarker predictions of Alzheimer's disease by 7%.

Previously, not much was known about how these risk factors corresponded to the ATN biomarkers. Biomarkers are an important tool for dementia researchers as they are often present in a person’s brain long before they present any symptoms of dementia. Studying people at this pre-disease stage enables scientists to develop earlier therapeutic interventions.

Dr Koychev said: 'The findings will improve our ability to detect dementia in the years before symptoms: this is when treatments are believed to be most likely to change its course.'

A common reason potential medicines to treat dementia aren't very effective is because they are given once too much damage has already occurred in the brain. If doctors are able to identify that someone will develop dementia long before symptoms show, then medication can be given much earlier and has more chance of protecting against dementia.

To find out more about using our Data Portal cohorts for your own research, visit the DPUK website to access our guides for cohort data in dementia research.