By Maria Ly
Early diagnosis will ultimately be essential in the management and treatment of Alzheimer’s disease. Examination of Alzheimer’s biomarkers can improve the prediction of short-term memory decline in middle-age and elderly individuals, according to new researchfrom Mayo Clinic.
A new diagnostic framework developed in collaboration with the National Institute on Aging and the Alzheimer’s Association, paired with new tools at Mayo Clinic, is showing promise in diagnosing Alzheimer’s earlier and more accurately, researchers write in “Associations of Amyloid, Tau, and Neurodegeneration Biomarker Profiles With Rates of Memory Decline Among Individuals Without Dementia” in the Journal of the American Medical Association (JAMA).
In exploring associations between beta-amyloid, tau and neurodegeneration, or AT(N), biomarkers and memory decline in a population-based cohort, Clifford Jack Jr., M.D., and colleagues write, “This study illustrates the potential clinical utility of AT(N) biomarkers to improve prediction of short-term memory decline over commonly available clinical and genetic information.”
AT(N) is the classification of the major existing Alzheimer’s disease biomarkers into three categories: A, the beta-amyloid biomarker; T, the tau biomarker; and (N), the biomarkers of neurodegeneration or neuronal injury, Dr. Jack writes.
The study consisted of 480 Mayo Clinic Study of Aging participants without dementia age 60 or older in Olmsted County, Minnesota, with 99 percent self-reporting as white. Using the Rochester Epidemiology Project enumeration, participants for the Mayo Clinic Study of Aging are randomly selected by 10-year age and sex strata to equally represent both males and females.
All participants received amyloid PET, tau PET, and MRI cortical thickness tests at their baseline (i.e., index) date. The results of these tests were used to determine the AT(N) biomarker profile in each participant.
The main outcome was within person change-over-time in a memory composite score. The memory composite was derived from the Wechsler Memory Scale-Revised Logical Memory-11, Wechsler Memory Scale-Revised Visual reproduction-11 and the Auditory Verbal Learning Test delayed recall.
Participants were classified as having either abnormal or normal presence of amyloid, tau and neurodegeneration. That information was then paired with the memory test results, which helped researchers determine if biomarkers can be used to predict future memory decline.
The study suggests that groups with the fastest rates of memory decline all had test results with abnormal amyloid. The three groups with the fastest rates of memory decline were participants who tested beta-amyloid positive, plus tau positive and neurodegeneration negative, tau negative and neurodegeneration positive, or both tau and neurodegeneration positive. The discovery illustrates a dominant association of memory decline with amyloidosis, but only with the combination of tauopathy, neurodegeneration or both.
“Given the pathologic heterogeneity of the aging brain, the observation that AT(N) biomarker abnormalities were associated with 46 percent of mean memory decline rates by ages was interesting because [amyloid] and [tau] biomarkers are related only to Alzheimer’s disease,” Dr. Jack and his colleagues write.
Biomarkers also predicted which groups were least likely to decline. Participants without the presence of beta-amyloid, tau or neurodegeneration showed minimal decline through age 85.
A prediction model that included amyloid PET, tau PET and MRI cortical thickness imaging resulted in a small yet significant improvement in predicting memory decline in older persons without dementia. However, researchers note, “The length of follow-up from index visit (1-3 years) in this study was fairly short for processes of this nature, and studies with longer follow-up times will be needed.”
AT(N) biomarkers can improve the prediction of short-term memory decline and will help doctors diagnose patients accurately before the disease progresses.
“AT(N) biomarker groups provided more precise prediction of memory decline rates beyond clinical variables that are more readily available to clinicians,” the researchers write.