{"id":5008,"date":"2022-07-19T20:20:34","date_gmt":"2022-07-20T00:20:34","guid":{"rendered":"https:\/\/ccna-ccnv.ca\/ccna_publication\/data-driven-analyses-of-longitudinal-hippocampal-imaging-trajectories-discrimination-and-biomarker-prediction-of-change-classes-2\/"},"modified":"2024-12-03T14:58:18","modified_gmt":"2024-12-03T19:58:18","slug":"data-driven-analyses-of-longitudinal-hippocampal-imaging-trajectories-discrimination-and-biomarker-prediction-of-change-classes-2","status":"publish","type":"ccna_publication","link":"https:\/\/ccna-ccnv.ca\/fr\/ccna_publication\/data-driven-analyses-of-longitudinal-hippocampal-imaging-trajectories-discrimination-and-biomarker-prediction-of-change-classes-2\/","title":{"rendered":"Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes"},"content":{"rendered":"<h2 class=\"title\">Abstract<\/h2>\n<div id=\"enc-abstract\" class=\"abstract-content selected\">\n<p><strong class=\"sub-title\">Background:\u00a0<\/strong>Hippocampal atrophy is a well-known biomarker of neurodegeneration, such as that observed in Alzheimer&rsquo;s disease (AD). Although distributions of hippocampal volume trajectories for asymptomatic individuals often reveal substantial heterogeneity, it is unclear whether interpretable trajectory classes can be objectively detected and used for prediction analyses.<\/p>\n<p><strong class=\"sub-title\">Objective:\u00a0<\/strong>To detect and predict hippocampal trajectory classes in a computationally competitive context using established AD-related risk factors\/biomarkers.<\/p>\n<p><strong class=\"sub-title\">Methods:\u00a0<\/strong>We used biomarker\/risk factor and longitudinal MRI data in asymptomatic adults from the AD Neuroimaging Initiative (n = 351; Mean = 75 years; 48.7% female). First, we applied latent class growth analyses to left (LHC) and right (RHC) hippocampal trajectory distributions to identify distinct classes. Second, using random forest analyses, we tested 38 multi-modal biomarkers\/risk factors for their relative importance in discriminating the lower (potentially elevated atrophy risk) from the higher (potentially reduced risk) class.<\/p>\n<p><strong class=\"sub-title\">Results:\u00a0<\/strong>For both LHC and RHC trajectory distribution analyses, we observed three distinct trajectory classes. Three biomarkers\/risk factors predicted membership in LHC and RHC lower classes: male sex, higher education, and lower plasma A\u03b21-42. Four additional factors selectively predicted membership in the lower LHC class: lower plasma tau and A\u03b21-40, higher depressive symptomology, and lower body mass index.<\/p>\n<p><strong class=\"sub-title\">Conclusion:\u00a0<\/strong>Data-driven analyses of LHC and RHC trajectories detected three classes underlying the heterogeneous distributions. Machine learning analyses determined three common and four unique biomarkers\/risk factors discriminating the higher and lower LHC\/RHC classes. Our sequential analytic approach produced evidence that the dynamics of preclinical hippocampal trajectories can be predicted by AD-related biomarkers\/risk factors from multiple modalities.<\/p>\n<\/div>\n","protected":false},"author":19,"featured_media":0,"template":"","meta":{"_acf_changed":false},"studies-relation":[],"class_list":["post-5008","ccna_publication","type-ccna_publication","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.8 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes - CCNA - CCNV<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ccna-ccnv.ca\/fr\/ccna_publication\/data-driven-analyses-of-longitudinal-hippocampal-imaging-trajectories-discrimination-and-biomarker-prediction-of-change-classes-2\/\" \/>\n<meta property=\"og:locale\" content=\"fr_CA\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes - 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