Introduction: Dementia prediction models are necessary to inform the development of dementia risk reduction strategies. Here, we examine the utility of neuropathological-based risk scores to predict clinical dementia.
Methods: Models were developed for predicting Alzheimer's disease (AD) and non-AD neuropathologies using the Honolulu Asia Aging neuropathological sub-study (HAAS; n = 852). Model accuracy for predicting clinical dementia, over 30 years, was tested in the non-autopsied HAAS sample (n = 2960) and the Age, Gene/Environment Susceptibility-Reykjavik Study (n = 4614).
Results: Different models were identified for predicting neurodegenerative and vascular neuropathology (c-statistic range: 0.62 to 0.72). These typically included age, APOE, and a blood pressure-related measure. The neurofibrillary tangle and micro-vascular lesion models showed good accuracy for predicting clinical vascular dementia.
Discussion: There may be shared risk factors across dementia-related lesions, suggesting common pathways. Strategies targeting these models may reduce risk or postpone clinical symptoms of dementia as well as reduce neuropathological burden associated with AD and vascular lesions.
Keywords: Alzheimer's disease; dementia; neuropathology; risk prediction; vascular disease.
© 2022 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.