Identifying longitudinal cognitive resilience from cross-sectional amyloid, tau, and neurodegeneration
Year: 2024
Type: article
Abstract: BACKGROUND: Leveraging Alzheimer's disease (AD) imaging biomarkers and longitudinal cognitive data may allow us to establish evidence of cognitive resilience (CR) to AD pathology in-vivo. Here, we applied latent class mixture modeling, adjusting for sex, baseline age, and neuroimaging biomarkers of amyloid, tau and neurodegeneration, to a sample of cognitively unimpaired older adults to identify longitudinal trajectories of CR. METHODS: We identified 200 Harvard Aging Brain Study (HABS) participants (mean age = 71.89 years, SD = 9.41 years, 59% women) who were cognitively unimpaired at baseline with 2 or more timepoints of cognitive assessment following a single amyloid-PET, tau-PET and structural MRI. We examined latent class mixture models with longitudinal cognition as the dependent variable and time from baseline, baseline age, sex, neocortical Aβ, entorhinal tau, and adjusted hippocampal volume as independent variables. We then examined group differences in CR-related factors across the identified subgroups from a favored model. Finally, we applied our favored model to a dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI; n = 160, mean age = 73.9 years, SD = 7.6 years, 60% women). RESULTS: The favored model identified 3 latent subgroups, which we labelled as Normal (71% of HABS sample), Resilient (22.5%) and Declining (6.5%) subgroups. The Resilient subgroup exhibited higher baseline cognitive performance and a stable cognitive slope. They were differentiated from other groups by higher levels of verbal intelligence and past cognitive activity. In ADNI, this model identified a larger Normal subgroup (88.1%), a smaller Resilient subgroup (6.3%) and a Declining group (5.6%) with a lower cognitive baseline. CONCLUSION: These findings demonstrate the value of data-driven approaches to identify longitudinal CR groups in preclinical AD. With such an approach, we identified a CR subgroup who reflected expected characteristics based on previous literature, higher levels of verbal intelligence and past cognitive activity.
Source: Alzheimer s Research & Therapy
Authors: Rory Boyle, Diana L. Townsend, Hannah M. Klinger, Catherine E. Scanlon, Ziwen Yuan, Gillian T. Coughlan, Mabel Seto, Zahra Shirzadi, Wai-Ying Wendy Yau, Roos J. Jutten, Christoph Schneider, Michelle E. Farrell, Bernard J. Hanseeuw, Elizabeth C. Mormino, Hyun-Sik Yang, Kathryn V. Papp, Rebecca E. Amariglio, Heidi I. L. Jacobs, Julie C. Price, Jasmeer P. Chhatwal, Aaron P. Schultz, Michael J. Properzi, Dorene M. Rentz, Keith A. Johnson, Reisa A. Sperling, Timothy J. Hohman, Michael C. Donohue, Rachel F. Buckley, for the Alzheimer’s Disease Neuroimaging Initiative
Institutions: Harvard University, Massachusetts General Hospital, Brigham and Women's Hospital, Cliniques Universitaires Saint-Luc, UCLouvain, Stanford Medicine, Stanford University, Maastricht University, Vanderbilt University Medical Center, University of Southern California, The University of Melbourne
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,990
Awards: G104586243, The inactive X: discovering sex genes that influence female vulnerability to Alzheimer's disease, EFFECTS OF TRAUMATIC BRAIN INJURY (TBI) AND POST TRAUMATIC STRESS DISORDER (PTSD) ON ALZHEIMER'S DISEASE (AD) IN VETERANS USING IMAGING AND BIOMARKERS IN THE AD NEUROIMAGING INITIATIVE (ADNI)", Alzheimer's Disease Neuroimaging Initiative, Alzheimer's Disease Sequencing Project Phenotype Harmonization Consortium, Building predictive algorithms to identify resilience and resistance to Alzheimer's disease, Impact of Amyloid and Tau on the Aging Brain: The Harvard Aging Brain Study, Elevated systolic blood pressure, body mass index, and amyloid as drivers of tau and cognitive decline in preclinical Alzheimers disease: critical windows in mid- to late-life
OpenAlex ID: W4400298413