<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Spencer BE</submitter><funding>NIA NIH HHS</funding><funding>Alzheimer&amp;apos;s Disease Neuroimaging Initiative</funding><funding>National Institutes of Health</funding><funding>National Institute on Aging</funding><funding>NIH HHS</funding><funding>National Institute of Biomedical Imaging and Bioengineering</funding><pagination>457-465</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8906231</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>17(3)</volume><pubmed_abstract>&lt;h4>Introduction&lt;/h4>Elevated β-amyloid is used to enroll individuals into preclinical Alzheimer's disease trials, but the screening process is inefficient and expensive. Novel enrichment methods are needed to improve efficiency of enrollment.&lt;h4>Methods&lt;/h4>Alzheimer's disease incidence rates and a polygenic hazard score were used to create a gene- and age-defined ADAge. An ADAge cutpoint was chosen to optimally predict β-amyloid positivity among clinically normal Alzheimer's Disease Neuroimaging Initiative participants and applied to an independent Alzheimer's Disease Research Center validation cohort. The impact of ADAge enrichment on screening costs was evaluated in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease trial data.&lt;h4>Results&lt;/h4>In the validation cohort, the ADAge-enriched sample had a higher proportion of individuals with elevated β-amyloid (difference [95% CI] 0.19[0.07 to 0.33]) than the unenriched sample. ADAge enrichment lowered screening costs by $4.41 million (31.00%) in the real-world clinical trial scenario.&lt;h4>Discussion&lt;/h4>ADAge enrichment provides for a more efficient and cost-effective means to enroll clinically normal individuals with elevated β-amyloid in clinical trials.</pubmed_abstract><journal>Alzheimer's &amp; dementia : the journal of the Alzheimer's Association</journal><pubmed_title>Gene- and age-informed screening for preclinical Alzheimer's disease trials.</pubmed_title><pmcid>PMC8906231</pmcid><funding_grant_id>P30 AG028383</funding_grant_id><funding_grant_id>P30 AG013846</funding_grant_id><funding_grant_id>P30 AG008017</funding_grant_id><funding_grant_id>P30 AG053760</funding_grant_id><funding_grant_id>P30 AG010133</funding_grant_id><funding_grant_id>P50 AG005146</funding_grant_id><funding_grant_id>1P30‐AG062429‐01</funding_grant_id><funding_grant_id>P50 AG005142</funding_grant_id><funding_grant_id>P50 AG005681</funding_grant_id><funding_grant_id>U19 AG010483</funding_grant_id><funding_grant_id>P30 AG062715</funding_grant_id><funding_grant_id>P50 AG047366</funding_grant_id><funding_grant_id>P50 AG047266</funding_grant_id><funding_grant_id>P30 AG019610</funding_grant_id><funding_grant_id>P50 AG023501</funding_grant_id><funding_grant_id>R01 AG063689</funding_grant_id><funding_grant_id>P30 AG008051</funding_grant_id><funding_grant_id>P30 AG010129</funding_grant_id><funding_grant_id>P30 AG013854</funding_grant_id><funding_grant_id>P50 AG005138</funding_grant_id><funding_grant_id>P50 AG008702</funding_grant_id><funding_grant_id>P30 AG062428</funding_grant_id><funding_grant_id>1P30-AG062429-01</funding_grant_id><funding_grant_id>P30 AG010124</funding_grant_id><funding_grant_id>P30 AG012300</funding_grant_id><funding_grant_id>P50 AG047270</funding_grant_id><funding_grant_id>U01 AG016976</funding_grant_id><funding_grant_id>P50 AG025688</funding_grant_id><funding_grant_id>P30 AG062421</funding_grant_id><funding_grant_id>P50 AG005136</funding_grant_id><funding_grant_id>P30 AG062422</funding_grant_id><funding_grant_id>P30 AG035982</funding_grant_id><funding_grant_id>P30 AG010161</funding_grant_id><funding_grant_id>P50 AG005133</funding_grant_id><funding_grant_id>P30 AG062429</funding_grant_id><funding_grant_id>P30 AG049638</funding_grant_id><funding_grant_id>U24 AG072122</funding_grant_id><funding_grant_id>U01 AG024904</funding_grant_id><funding_grant_id>P50 AG016573</funding_grant_id><pubmed_authors>Digma LA</pubmed_authors><pubmed_authors>Alzheimer's Disease Neuroimaging Initiative and the A4 Study Team</pubmed_authors><pubmed_authors>Jennings RG</pubmed_authors><pubmed_authors>Brewer JB</pubmed_authors><pubmed_authors>Spencer BE</pubmed_authors></additional><is_claimable>false</is_claimable><name>Gene- and age-informed screening for preclinical Alzheimer's disease trials.</name><description>&lt;h4>Introduction&lt;/h4>Elevated β-amyloid is used to enroll individuals into preclinical Alzheimer's disease trials, but the screening process is inefficient and expensive. Novel enrichment methods are needed to improve efficiency of enrollment.&lt;h4>Methods&lt;/h4>Alzheimer's disease incidence rates and a polygenic hazard score were used to create a gene- and age-defined ADAge. An ADAge cutpoint was chosen to optimally predict β-amyloid positivity among clinically normal Alzheimer's Disease Neuroimaging Initiative participants and applied to an independent Alzheimer's Disease Research Center validation cohort. The impact of ADAge enrichment on screening costs was evaluated in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease trial data.&lt;h4>Results&lt;/h4>In the validation cohort, the ADAge-enriched sample had a higher proportion of individuals with elevated β-amyloid (difference [95% CI] 0.19[0.07 to 0.33]) than the unenriched sample. ADAge enrichment lowered screening costs by $4.41 million (31.00%) in the real-world clinical trial scenario.&lt;h4>Discussion&lt;/h4>ADAge enrichment provides for a more efficient and cost-effective means to enroll clinically normal individuals with elevated β-amyloid in clinical trials.</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021 Mar</publication><modification>2025-04-26T03:56:00.296Z</modification><creation>2025-04-06T10:59:30.293Z</creation></dates><accession>S-EPMC8906231</accession><cross_references><pubmed>33226723</pubmed><doi>10.1002/alz.12207</doi></cross_references></HashMap>