Scientists have developed a new blood test to predict when someone is likely to show symptoms of Alzheimer’s disease, an advance that may help speed up preventive treatments.
Some 55 million people worldwide live with dementia and Alzheimer’s accounts for 60-70 per cent of the cases. The number of affected people is projected to double every 20 years and reach nearly 140 million by 2050.
In the absence of a cure, predictive models can help develop therapies to prevent or slow the onset of Alzheimer’s symptoms in those at risk.
A new model based on a blood test can predict the onset of Alzheimer’s symptoms within a margin of three to four years, researchers say in a new study.
“Our work shows the feasibility of using blood tests, which are substantially cheaper and more accessible than brain imaging scans or spinal fluid tests, for predicting the onset of Alzheimer’s symptoms,” Suzanne Schindler, an author of the study published in Nature Medicine, said.
“The goal is to be able to tell individual patients when they’re likely to develop symptoms which will help them and their doctors to develop a plan to prevent or slow symptoms,” Dr Schindler, from the Washington University School of Medicine in St Louis, said.
The model assesses levels of a protein called p-tau217 in an individual’s plasma, the liquid part of the blood, to estimate the age when they are likely to begin experiencing Alzheimer’s disease symptoms.
The protein’s levels are strongly linked to the accumulation of misfolded amyloid and tau protein clusters in the brain, which are key hallmarks of Alzheimer’s.
“Amyloid and tau levels are similar to tree rings – if we know how many rings a tree has, we know how many years old it is,” Kellen Petersen, another author of the study, explained. “It turns out that amyloid and tau also accumulate in a consistent pattern and the age at which they become positive strongly predicts when someone is going to develop Alzheimer’s symptoms. We found that this is also true of plasma p-tau217, which reflects both amyloid and tau levels.”
Researchers used their new model to predict the age of symptom onset within a margin of error of three-four years.
It showed that older individuals had a shorter time from when elevated p-tau217 appeared to the start of symptoms compared to younger participants.
If a person had elevated p-tau217 in their plasma at age 60, for example, they developed symptoms 20 years later.
“These clock models could make clinical trials more efficient by identifying individuals who are likely to develop symptoms within a certain period of time,” Dr Petersen noted. “With further refinement, these methodologies have the potential to predict symptom onset accurately enough that we could use them in individual clinical care.”
