The physical properties of proteins in the spinal fluid and blood of people with Alzheimer’s disease may constitute valuable biomarkers to help diagnose disease progression and predict patients’ outcomes, new research from The Ohio State University suggests.
The biomarkers may help researchers develop better treatments in the future, especially for later stages of the disease.
The study “Computational integration of nanoscale physical biomarkers and cognitive assessments for Alzheimer’s disease diagnosis and prognosis” was published in the journal Science Advances.
Researchers discovered that certain physical properties of protein aggregates in the cerebral spinal fluid and blood of Alzheimer’s disease patients are altered, and these changes correlate with disease severity. For example, as severity increases, the proteins become longer, more rigid, and more clustered.
The team of scientists, led by Mingjun Zhang, a professor of biomedical engineering at Ohio State, used a computational algorithm that incorporated information on the biomarkers as well as scores on patients’ cognitive assessments. Based on the changes in the physical biomarkers and the cognitive assessment scores of patients over time, the algorithm identified disease stages and progression, the researchers found.
“With a tool like this you may predict how fast this disease will go, and currently we can’t do that – we just know everyone is different,” Zhang said in a press release. “Looking at multiple indicators of the disease all at once increases the reliability of the diagnosis and prognosis.”
The study used samples of spinal fluid and blood from Alzheimer’s patients followed by study co-author Douglas Scharre, a professor of clinical neurology and psychiatry in the Neurological Institute at Ohio State’s Wexner Medical Center, as well as information from a medical database.
“Currently available medications treat only symptoms of the disease and work best with an early diagnosis. Improved diagnostic tools could help doctors sort out more quickly which patients have Alzheimer’s disease and which are experiencing cognitive decline for other reasons,” Scharre said.
“The experimental tools aren’t ready for clinical use yet, but could lead to improvements in treatment in multiple ways,” he added.
An easily detectable biomarker that changes according to the disease stage would help researchers evaluate more accurately the impact of their investigational therapies.
“A biomarker that shows that in three months, or three weeks even, that this drug is not doing a darn thing or is slowing down the disease will help us to not waste time in finding better treatments,” Scharre said.
This strategy builds on what doctors currently do is assessing several different factors to determine disease stage and potential treatments.
“We’ve taken what they do and converted it to a computational model with different weights for different factors,” Zhang said. “We’re using engineering techniques to look at a human disease process, a dynamic process.”
“Looking for physical changes in proteins is a growing area of interest for those seeking disease biomarkers,” said Jeff Kuret, study co-author and professor of biological chemistry and pharmacology at Ohio State.
“This kind of test is especially promising for Alzheimer’s because it’s a relatively slow-moving illness and one in which the ability to determine stages of disease could lead to better, more personalized treatments down the road. To be able to follow individual patients from pre-symptomatic through all stages of Alzheimer’s progression would be incredibly helpful,” he added.
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