1. In this prospective cohort, Alzheimer’s Disease biomarkers derived from imaging, namely amyloid, tau, and cortical thickness estimates, had a moderate impact in predicting memory decline compared to a clinical model.
2. Patients that were positive for amyloid and at least one other biomarker had a faster rate of decline than other groups.
Evidence Rating Level: 2 (Good)
Study Rundown: As numerous clinical trials to treat Alzheimer’s Disease (AD) have failed, researchers have posited that early detection and treatment may be necessary to achieve clinically meaningful improvements. The National Institute of Aging and Alzheimer’s Association created an Amyloid, Tau, and Cortical Thickness (ATN) scoring system that uses imaging-based biomarkers to estimate dementia risk, though it is unclear if these biomarkers are useful for predicting the rate of memory decline. In this prospective cohort, ATN biomarkers had a significant but moderate impact in predicting memory decline compared to a clinical model. Patients that were A+T+N+, A+T+N-, and A+T-N+ had more rapid memory decline than other groups. ATN classifications were relatively stable over a period of a few years.
Though the ATN system was able to outperform the clinical model, the marginal increase in predictive power suggests that these biomarkers may still not be optimal for understanding risk associated with AD-related memory loss. Limitations, however, include the relatively short nature of the study over a half decade compared to the decades long process of AD pathogenesis, sole focus on memory decline and not other dementia symptoms, and a highly homogeneous population ethnically.
In-Depth [prospective cohort]: 480 participants older than 60 years of age were recruited to the Mayo Clinic Study of Aging (MCSA) from Olmstead County, Minnesota (99% self-reported as white) and were randomly selected by 10-year age and sex strata so that men and women were represented equally. Patients without medical contraindication were invited to participate in imaging studies from April 2016 to November 2017 and had at least one follow-up evaluation before November 2018. Patients underwent amyloid and tau PET imaging, MRI to determine cortical thickness, and clinical evaluation, including age, sex, education, APOE4 status, and composite cardiovascular and metabolic conditions score. A numeric composite of memory function composed of the Wechsler Memory Scale–Revised Logical Memory–II (delayed recall), Wechsler Memory Scale–Revised Visual Reproduction–II (delayed recall), and Auditory Verbal Learning Test (delayed recall) was used as the primary endpoint and was represented by z-score using the standard deviation of the population. In the clinical prediction model, age and APOE4 status were associated with faster rates of cognitive decline (p < 0.05) while sex, education, and cardiovascular/metabolic status were not (p > 0.05). While the clinical model correlated with memory z-scores at r2 of 0.26, the ATN model offered a significant but modest improvement at r2 of 0.31 (p < 0.001). A+T+N+, A+T+N-, and A+T-N+ had greater rates of cognitive decline then the other 5 groups (p = 0.002). 88 patients had imaging follow-up at a median of 15 months later, and ATN status remained stable in 82% of these patients. A and T classifications were very stable at 98% and 97%, respectively, while N measures were stable at 84%.
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