A prediction model based on imaging data for three Alzheimer’s disease biomarkers — amyloid, tau, and neurodegeneration (ATN) — improved prognosis for memory decline over about 5 years in older adults, a longitudinal cohort study showed.
An ATN classification system for Alzheimer’s disease proposed by the National Institute on Aging (NIA) and the Alzheimer’s Association (AA) in 2018 led to a small but statistically significant improvement in predicting memory decline, compared with a model that used only clinical and genetic variables, reported Clifford Jack Jr., MD, of the Mayo Clinic in Rochester, Minnesota, and colleagues in JAMA.
“This work validates the clinical utility of the NIA-AA research framework approach to Alzheimer’s disease, where the disease is defined by the presence of the two hallmark proteinopathies — amyloid plaques and tau neurofibrillary tangles — and not by the presence of symptoms,” Jack told MedPage Today.
“The ultimate measure of clinical utility in this area is prediction of cognitive decline,” he continued. “In this work, we show that ATN biomarker profiles consistent with either Alzheimer’s disease, or with Alzheimer’s plus one or more other diseases, can predict cognitive decline.”
The ATN scheme is intended to differentiate Alzheimer’s from other dementias. It classifies amyloid, tau, and neurodegeneration measures as abnormal (+) or normal (−), resulting in eight possible clinical profiles.
In this study, Jack and co-authors followed 480 older adults from the Mayo Clinic Study on Aging for a median of 4.8 years. Participants had amyloid PET, tau PET, and MRI cortical thickness measures from April 2015 to November 2017.
Median ages ranged from 67 in people who were negative for amyloid, tau, and neurodegeneration to 83 in people who were positive for all three variables. Most participants (92%) were cognitively normal; the other 8% had mild cognitive impairment. Nearly all participants (99%) were white and 56% were male.
The group positive for all markers (A+T+N+) had the largest proportion of people with mild cognitive impairment (30%). The proportion of APOE ε4 carriers was greater in the four A+ groups than the four A- groups (40% vs 21%, P<0.001).
ATN biomarkers improved the prediction of memory performance over a clinical model from an R2 of 0.26 to 0.31 (P<0.001). Memory declined fastest in the A+T+N+, A+T+N-, and A+T-N+ groups, compared with the five other ATN groups (P=0.002).
In the clinical prediction model, age (P<0.001) and APOE ε4 status (P=0.006) were significantly associated with faster rates of memory decline, but sex, education, and cardiovascular/metabolic scores were not.
The ATN framework “is still a research construct, and its validation and ultimate utility depend on data supporting its link to clinical outcomes,” noted Steve Salloway, MD, MS, of Brown University in Providence, Rhode Island, and co-authors in an accompanying editorial. In this study, the groups of patients who had more extensive Alzheimer’s pathology had faster rates of decline, and “these findings indicate a potentially useful role of Alzheimer’s biomarkers in forecasting clinical course deterioration among these patients,” they wrote.
The results may be most immediately relevant for use in clinical trials, allowing patients to be categorized into distinct prognostic groups, they added.
About 50% of the memory change with older age was associated with underlying Alzheimer’s pathology in this analysis, “yet it remains unclear what factors may account for the other 50% and whether they are linked to distinct other pathologies or reflect nonspecific effects of aging,” Salloway and colleagues observed.
This initial look at the ATN classification system has several limitations, the editorial noted. Because clinical variables did not include cognitive measures, the predictive value of tau PET and neurodegeneration MRI may have been overvalued. And age was not fully controlled for: more than 73% of study participants older than age 80 were N+, compared with 24% of those in their 60s.
ATN neuroimaging — an MRI scan and two PET scans — is “expensive and will not be practical to add to many research projects,” they pointed out, and the added value of each specific amyloid, tau, and neurodegeneration measure requires more evaluation. It’s unknown whether these results will generalize to other PET and cerebral spinal fluid biomarkers, or to more diverse patient populations than the Mayo cohort.
But despite these caveats, “the study by Jack et al represents an important contribution not only to advancing the conceptualization of Alzheimer’s, but also for putting this new framework to the test rapidly in a relatively large sample of participants,” Salloway’s group concluded.
Study funding was provided by the NIH, the Alexander Family Professorship of Alzheimer’s Disease Research, and the GHR Foundation.
Researchers reported relationships with Eli Lily, Roche, the Dominantly Inherited Alzheimer Network–Trials Unit, Biogen, Lilly Pharmaceuticals, Lundbeck, Bayer Schering Pharma, Piramal Life Science, Merck Research, GE Healthcare, Siemens Molecular Imaging, Align Technology Inc, LHC Group Inc, Mesa Laboratories Inc, Natus Medical Inc, Varex Imaging Corp. CRISPR Therapeutics, Gilead Sciences Inc, Globus Medical Inc, Inovio Biomedical Corp, Ionis Pharmaceuticals, Johnson & Johnson, Medtronic Inc, Parexel International Corp, Hoffman-La Roche Inc, Merck Inc, Genentech Inc, and Eisai Inc.