Predicting the onsets of symptoms in Alzheimer’s disease through Amyloid PET

As per a certain study carried out at the Medical School of the University of Washington, a new algorithm, which is created based on the neuroimaging data of the amyloid levels, is able to estimate when individuals with Alzheimer’s risk will possibly develop this disease before the symptoms of cognitive decline come in sight.

Having been published in the Journal of Neurology, this study involves the use of the data obtained from some sort of brain scan, which is known as the amyloid Positron Emission Tomography (PET), in order to measure the levels of amyloid beta, which is the key protein of Alzheimer’s disease.

How Was the Algorithm Created?

Amyloid proteins silently accumulate in the brain for up to twenty years, before the initial symptoms like absentmindedness or confusion occur in patients with Alzheimer’s Dementia. Amyloid PET scans are currently in common use in Alzheimer’s research. The algorithm put forward in the study, however, is a new method of analyzing such scans in order to estimate when the symptoms would appear. Just by making use of the age of the individual and a single PET scan, attempts are made to estimate how close the individual is to dementia, and how much time there is left before cognitive decline starts.

What Was the Method to Obtain the Data Used in the Algorithm?

Associate Professor Doctor Suzanne Schindler, head author of the study, and her colleagues Charles F. and Joanne Knight of the University of Washington analyzed the amyloid PET scans taken from 236 people who participated in the Alzheimer’s research studies through the Alzheimer’s Disease Research Center.

The average age of the participants was 67 at the beginning of the study. At least two brain scans were administered on all participants with an average interval of four and a half years. The researchers implemented a commonly-used measurement in the scans, which is known as the standardized uptake value ratio, in order to estimate the amount of amyloid in each participant at each point of time.

The researchers also obtained more than 1300 clinical evaluations on 180 participants. The evaluations were typically carried out once in every one to three years. Many participants were cognitively normal at the beginning of the data collection; therefore, repetitive evaluations enabled the researchers to determine when the cognitive abilities of each participant started to decline.

Breaking Point in the Accumulation of Amyloid

Doctor Schindler previously carried out a number of studies in regards to how the data in the amyloid PET scans could be used to estimate the age at which the symptoms of Alzheimer’s would appear. Based on her studies, she concluded that there is a breaking point for the amyloid accumulation, that the amyloid accumulation follows a predictable trajectory beyond this point, and that each individual reaches this breaking point at different ages. For the breaking point, Schindler said “You may reach the breaking point at the age of 50; this can also happen at the age of 80, or it may never happen at all. However, once you have passed the breaking point, you accumulate high levels of amyloid that can cause dementia. If we know that how much amyloid a person has right now, we can calculate when he reached the breaking point and estimate how much time it will take for him to develop the symptoms.”

Results of the Study

The study found out that it takes a longer time for the individuals, who reach the breaking point at younger ages, to develop the cognitive symptoms of Alzheimer’s Dementia, compared to those who reach this point at later ages. For instance, it took approximately 20 years for the participants who reached the breaking point at the age of 50 to develop the symptoms, and less than 10 years for those who reached this point at the age of 80.

Doctor Schindler explains the result obtained from the study as follows: “Upon the analysis of the brains of the relatively younger people who die of Alzheimer’s, they look quite healthy except for Alzheimer’s. Nevertheless, the brains of those who are relatively older get damaged mostly due to other reasons, which causes their cognitive resources to be lower. Therefore, less amyloid is required to cause cognitive decline.”

The strongest aspect of the study is that it can reach accurate results with considerably fewer data. The algorithm only requires the age and a single brain scan of the individual in order to estimate the duration to pass until the onset of the symptoms of dementia. Furthermore, the age for the onset of symptoms estimated by the model, and the real age of diagnosis coincide with each other almost identically. The value of correlation between the estimated age and the real age of diagnosis on a scale of correlation from 0 (no correlation) to 1 (perfect correlation): Above 0.9.

Effects of Genetic Factors on the Amyloid Breaking Point

The APOE4 genetic variant follows the age as the strongest risk factor for Alzheimer’s Dementia. People carrying a copy of the variant are two to three times more likely to develop Alzheimer’s dementia, compared to general population. In this study, individuals with the high-risk variant reached the breaking point at younger ages; nevertheless, once this point has been passed, they followed the same trajectory as everyone else.

On this matter, Doctor Schindler said: “When the amyloid accumulation is below the breaking point, you can see an increase of amyloid in people with APOE4, while it does not change in those without APOE4. This means that APOE4 carriers will reach the breaking point sooner. People with two copies of APOE4 reached the breaking point nearly 10 years earlier than those without the copy. However, beyond this point, we see no differences between APOE4 carriers and non-carriers.”

The biggest limitation of the study is that the amyloid PET method is a costly initiative for routine clinical use. Nonetheless, this algorithm may help accelerate the process of developing drugs by regulating clinical trials.

REFERENCES:
– Schindler, S., Li, Y., Buckles, V. D., Gordon, B. A., Benzinger, T. L., Wang, G., … & Xiong, C. (2021). Predicting Symptom Onset in Sporadic Alzheimer Disease with Amyloid PET. Neurology.