Lianlian Du, Elizabeth M Planalp, Tobey J Betthauser, Erin M Jonaitis, Bruce P Hermann, Leonardo A Rivera-Rivera, Karly A Cody, Nathaniel A Chin, Robert V Cadman, Kevin M Johnson, Aaron Field, Howard A Rowley, Kimberly D Mueller, Sanjay Asthana, Laura Eisenmenger, Bradley T Christian, Sterling C Johnson, Rebecca E Langhough
{"title":"Onset ages of cerebrovascular disease and amyloid and effects on cognition in risk-enriched cohorts.","authors":"Lianlian Du, Elizabeth M Planalp, Tobey J Betthauser, Erin M Jonaitis, Bruce P Hermann, Leonardo A Rivera-Rivera, Karly A Cody, Nathaniel A Chin, Robert V Cadman, Kevin M Johnson, Aaron Field, Howard A Rowley, Kimberly D Mueller, Sanjay Asthana, Laura Eisenmenger, Bradley T Christian, Sterling C Johnson, Rebecca E Langhough","doi":"10.1093/braincomms/fcaf158","DOIUrl":null,"url":null,"abstract":"<p><p>The temporal relationship between cerebrovascular disease (V), indicated by white matter hyperintensities, and beta-amyloid (A) in Alzheimer's disease remains unclear, prompting speculation about their potential interdependence. Longitudinal data were employed to estimate onset ages and corresponding disease chronicity for A and V (where disease chronicity is calculated as age at measurement minus estimated age of biomarker abnormality onset). In a large, predominantly cognitively unimpaired dataset (<i>n</i> = 877, ages 43-93 years), a V+ threshold was identified, and Sampled Iterative Local Approximation (SILA) was utilized to illustrate the predictable accumulation trajectory of V post-onset. Investigating the temporal association between A and V onset ages and accumulation trajectories in preclinical years, four operationalizations of time were examined across two initially cognitively unimpaired samples (<i>n</i> = 240 primary sample from Wisconsin Registry for Alzheimer's Prevention; <i>n</i> = 123 replication sample from Wisconsin Alzheimer's Disease Research Center): (i) chronological age, (ii) estimated V+ chronicity, (iii) years since baseline scan, and (iv) estimated A+ chronicity. Results indicated that while both diseases are age-related, their onsets and trajectories are independent of each other. In addition, results indicated that V and A accumulation trajectories were highly predictable relative to onset of positivity for each biomarker. Cognitive decline across multiple cognitive domains was fastest when both V and A were present based on last available amyloid PET and MRI scan, with greater A chronicity being a more salient predictor of cognitive decline in these samples.</p>","PeriodicalId":93915,"journal":{"name":"Brain communications","volume":"7 3","pages":"fcaf158"},"PeriodicalIF":4.1000,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12056727/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/braincomms/fcaf158","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The temporal relationship between cerebrovascular disease (V), indicated by white matter hyperintensities, and beta-amyloid (A) in Alzheimer's disease remains unclear, prompting speculation about their potential interdependence. Longitudinal data were employed to estimate onset ages and corresponding disease chronicity for A and V (where disease chronicity is calculated as age at measurement minus estimated age of biomarker abnormality onset). In a large, predominantly cognitively unimpaired dataset (n = 877, ages 43-93 years), a V+ threshold was identified, and Sampled Iterative Local Approximation (SILA) was utilized to illustrate the predictable accumulation trajectory of V post-onset. Investigating the temporal association between A and V onset ages and accumulation trajectories in preclinical years, four operationalizations of time were examined across two initially cognitively unimpaired samples (n = 240 primary sample from Wisconsin Registry for Alzheimer's Prevention; n = 123 replication sample from Wisconsin Alzheimer's Disease Research Center): (i) chronological age, (ii) estimated V+ chronicity, (iii) years since baseline scan, and (iv) estimated A+ chronicity. Results indicated that while both diseases are age-related, their onsets and trajectories are independent of each other. In addition, results indicated that V and A accumulation trajectories were highly predictable relative to onset of positivity for each biomarker. Cognitive decline across multiple cognitive domains was fastest when both V and A were present based on last available amyloid PET and MRI scan, with greater A chronicity being a more salient predictor of cognitive decline in these samples.