Biomarker study detects onset of Alzheimer’s up to 30 years before symptoms appear
New research from Johns Hopkins University has identified a variety of biomarkers that can be used to predict the onset of Alzheimer's disease years before symptoms appear. The study presents nine measures, produced from several decades of data, that can signal the onset of the disease up to 30 years before cognitive decline becomes apparent.
Many researchers believe the preclinical phase of Alzheimer's can commence over a decade before the disease becomes clinically visible. As a vast number of prospective Alzheimer's drugs have failed in clinical trials, it is hypothesized that the disease may be best treated in this preclinical stage, before any neurodegeneration progresses to the point of major cognitive decline.
Unfortunately, we do not have any clear diagnostic framework to identify the disease at its earliest stage. Blood tests, PET scans, eye tests, genetics, and even sniff tests, are all being investigated as ways to identify the earliest stages of cognitive decline, but no single biomarker has been wholly confirmed as clinically reliable so far.
This new Johns Hopkins Study reviewed medical data from 290 subjects considered to be at a higher than average risk of developing Alzheimer's or early-onset dementia due to the presence of a relative diagnosed with the disease. The subjects were tracked for almost 20 years, completing annual cognitive tests alongside bi-annual MRI brain scans and cerebrospinal fluid testing.
At the end of the project, 81 subjects had been diagnosed with either Alzheimer's disease or mild cognitive impairment (MCI), allowing the researchers to be able to effectively track the preclinical progress of those conditions across the pre-symptomatic years.
Looking at the cognitive tests, the researchers identified subtle changes that could be detected between 10 and 15 years before symptoms appeared. The MRI data revealed minor, but detectable, decreases in the size of a brain region called the medial temporal lobe. These changes could be tracked between three and nine years before any symptoms appeared.
Most interesting were the cerebrospinal fluid test results which signaled the earliest potential biomarkers for the disease. Increases in the presence of the tau protein in cerebrospinal fluid could be associated with Alzheimer's around 30 years before any cognitive impairment became apparent. Other proteins, including amyloid beta and phosphorylated tau, appeared between 10 and 15 years before symptom onset.
"Several biochemical and anatomic measures can be seen changing up to a decade or more before the onset of clinical symptoms," says Michael Miller, a biomedical engineer working on the project. "The goal is to find the right combination of markers that indicate increased risk for cognitive impairment, and to use that tool to guide eventual interventions to help stave it off."
Sample size is of course a significant limitation in turning this data into an effective diagnostic tool, and while the researchers do suggest the scale of the study is large enough to determine statistical significance, further work is underway to add more data to the model. The study notes an agreement is in place with five different research sites around the world to collect comparable data so the overall model can be improved.
The big challenge here is that this kind of research takes a lot of time. In order to identify patterns that signal the onset of Alzheimer's or MCI, subjects need to be tracked for years, or even decades. Despite this slow progress, the researchers are positive this work will ultimately lead to effective ways to detect Alzheimer's in its earliest stages.
"Our study suggests it may be possible to use brain imaging and spinal fluid analysis to assess risk of Alzheimer's disease at least 10 years or more before the most common symptoms, such as mild cognitive impairment, occur," says Laurent Younes, an author on the newly published study.
The research was published in the journal Frontiers in Aging Neuroscience.
Source: John Hopkins University