<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Bledsoe X</submitter><funding>Scott Hamilton CARES Foundation</funding><funding>NIA NIH HHS</funding><funding>NHGRI NIH HHS</funding><funding>NIH HHS</funding><funding>NIGMS NIH HHS</funding><pagination>e71217</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12930104</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>22(2)</volume><pubmed_abstract>&lt;h4>Introduction&lt;/h4>Neuroimaging genetics has advanced our understanding of Alzheimer's disease (AD); however, frameworks using functional genomics are needed to elucidate mechanisms connecting loci to neurological outcomes. To address this need, we explored relationships between AD-associated variants and disease via their impact on gene expression and neuroanatomical phenotypes.&lt;h4>Methods&lt;/h4>We mapped established AD genes to neuroimaging traits using the NeuroimaGene Atlas and predicted transcript-driven neurological features of AD by comparing gene-derived neuroimaging features with clinical neuroimaging data. Genetic covariance analyses were performed to characterize shared genetic architecture between AD endophenotypes and neuroimaging features, and to identify neuroimaging feature</pubmed_abstract><journal>Alzheimer's &amp; dementia : the journal of the Alzheimer's Association</journal><pubmed_title>Neuroimaging PheWAS and molecular phenotyping implicate PSMC3 in Alzheimer's disease.</pubmed_title><pmcid>PMC12930104</pmcid><funding_grant_id>R01HG011138</funding_grant_id><funding_grant_id>R01AG073439</funding_grant_id><funding_grant_id>RF1AG061351</funding_grant_id><funding_grant_id>R35HG010718</funding_grant_id><funding_grant_id>R56AG068026</funding_grant_id><funding_grant_id>R01GM140287</funding_grant_id><pubmed_authors>Dumitrescu L</pubmed_authors><pubmed_authors>Bush WS</pubmed_authors><pubmed_authors>Gamazon ER</pubmed_authors><pubmed_authors>Chen HH</pubmed_authors><pubmed_authors>Naj AC</pubmed_authors><pubmed_authors>Below JE</pubmed_authors><pubmed_authors>Archer D</pubmed_authors><pubmed_authors>Wang TC</pubmed_authors><pubmed_authors>Bledsoe X</pubmed_authors><pubmed_authors>Wu Y</pubmed_authors><pubmed_authors>Hohman TJ</pubmed_authors></additional><is_claimable>false</is_claimable><name>Neuroimaging PheWAS and molecular phenotyping implicate PSMC3 in Alzheimer's disease.</name><description>&lt;h4>Introduction&lt;/h4>Neuroimaging genetics has advanced our understanding of Alzheimer's disease (AD); however, frameworks using functional genomics are needed to elucidate mechanisms connecting loci to neurological outcomes. To address this need, we explored relationships between AD-associated variants and disease via their impact on gene expression and neuroanatomical phenotypes.&lt;h4>Methods&lt;/h4>We mapped established AD genes to neuroimaging traits using the NeuroimaGene Atlas and predicted transcript-driven neurological features of AD by comparing gene-derived neuroimaging features with clinical neuroimaging data. Genetic covariance analyses were performed to characterize shared genetic architecture between AD endophenotypes and neuroimaging features, and to identify neuroimaging feature</description><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Feb</publication><modification>2026-07-16T20:26:14.192Z</modification><creation>2026-07-10T03:10:39.704Z</creation></dates><accession>S-EPMC12930104</accession><cross_references><pubmed>41732108</pubmed><doi>10.1002/alz.71217</doi></cross_references></HashMap>