{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Nguyen Ho PT"],"funding":["NIA NIH HHS","ZonMw"],"pagination":["5506-5517"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7616996"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["19(12)"],"pubmed_abstract":["<h4>Introduction</h4>Reliable models to predict amyloid beta (Aβ) positivity in the general aging population are lacking but could become cost-efficient tools to identify individuals at risk of developing Alzheimer's disease.<h4>Methods</h4>We developed Aβ prediction models in the clinical Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study (n = 4,119) including a broad range of easily ascertainable predictors (demographics, cognition and daily functioning, health and lifestyle factors). Importantly, we determined the generalizability of our models in the population-based Rotterdam Study (n = 500).<h4>Results</h4>The best performing model in the A4 Study (area under the curve [AUC] = 0.73 [0.69-0.76]), including age, apolipoprotein E (APOE) ε4 genotype, family history of dementia"],"journal":["Alzheimer's & dementia : the journal of the Alzheimer's Association"],"pubmed_title":["Predicting amyloid-beta pathology in the general population."],"pmcid":["PMC7616996"],"funding_grant_id":["#10510032120003","#73305095007","10510032120003","P01 AG036694","73305095007","733050817"],"pubmed_authors":["Vernooij MW","Nguyen Ho PT","van Rooij FJA","Roshchupkin GV","Ikram MA","van Arendonk J","Neitzel J","Steketee RME"],"additional_accession":[]},"is_claimable":false,"name":"Predicting amyloid-beta pathology in the general population.","description":"<h4>Introduction</h4>Reliable models to predict amyloid beta (Aβ) positivity in the general aging population are lacking but could become cost-efficient tools to identify individuals at risk of developing Alzheimer's disease.<h4>Methods</h4>We developed Aβ prediction models in the clinical Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study (n = 4,119) including a broad range of easily ascertainable predictors (demographics, cognition and daily functioning, health and lifestyle factors). Importantly, we determined the generalizability of our models in the population-based Rotterdam Study (n = 500).<h4>Results</h4>The best performing model in the A4 Study (area under the curve [AUC] = 0.73 [0.69-0.76]), including age, apolipoprotein E (APOE) ε4 genotype, family history of dementia","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Dec","modification":"2026-06-01T17:45:43.325Z","creation":"2025-04-04T12:25:33.413Z"},"accession":"S-EPMC7616996","cross_references":{"pubmed":["37303116"],"doi":["10.1002/alz.13161"]}}