{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Loreto F"],"funding":["NIA NIH HHS","Alzheimer&apos;s Drug Discovery Foundation","U.S. Department of Defense","Alzheimer&apos;s Society","National Institutes of Health","Alzheimer&apos;s Association","AbbVie","National Institute of Biomedical Imaging and Bioengineering","National Institute on Aging"],"pagination":["e12559"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10937817"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["16(1)"],"pubmed_abstract":["<h4>Introduction</h4>Overlooking the heterogeneity in Alzheimer's disease (AD) may lead to diagnostic delays and failures. Neuroanatomical normative modeling captures individual brain variation and may inform our understanding of individual differences in AD-related atrophy.<h4>Methods</h4>We applied neuroanatomical normative modeling to magnetic resonance imaging from a real-world clinical cohort with confirmed AD (<i>n</i> = 86). Regional cortical thickness was compared to a healthy reference cohort (<i>n</i> = 33,072) and the number of outlying regions was summed (total outlier count) and mapped at individual- and group-levels.<h4>Results</h4>The superior temporal sulcus contained the highest proportion of outliers (60%). Elsewhere, overlap between patient atrophy patterns was low. Mean total outlier count was higher in patients who were non-amnestic, at more advanced disease stages, and without depressive symptoms. Amyloid burden was negatively associated with outlier count.<h4>Discussion</h4>Brain atrophy in AD is highly heterogeneous and neuroanatomical normative modeling can be used to explore anatomo-clinical correlations in individual patients."],"journal":["Alzheimer's & dementia (Amsterdam, Netherlands)"],"pubmed_title":["Alzheimer's disease heterogeneity revealed by neuroanatomical normative modeling."],"pmcid":["PMC10937817"],"funding_grant_id":["W81XWH‐12‐2‐0012","P75464","U01 AG024904"],"pubmed_authors":["Duvnjak A","Hakeem H","Marquand AF","Fitzgerald A","Loreto F","Win Z","Patel N","Cole JH","Kia SM","Lilja J","Malhotra P","Verdi S","Perry R"],"additional_accession":[]},"is_claimable":false,"name":"Alzheimer's disease heterogeneity revealed by neuroanatomical normative modeling.","description":"<h4>Introduction</h4>Overlooking the heterogeneity in Alzheimer's disease (AD) may lead to diagnostic delays and failures. Neuroanatomical normative modeling captures individual brain variation and may inform our understanding of individual differences in AD-related atrophy.<h4>Methods</h4>We applied neuroanatomical normative modeling to magnetic resonance imaging from a real-world clinical cohort with confirmed AD (<i>n</i> = 86). Regional cortical thickness was compared to a healthy reference cohort (<i>n</i> = 33,072) and the number of outlying regions was summed (total outlier count) and mapped at individual- and group-levels.<h4>Results</h4>The superior temporal sulcus contained the highest proportion of outliers (60%). Elsewhere, overlap between patient atrophy patterns was low. Mean total outlier count was higher in patients who were non-amnestic, at more advanced disease stages, and without depressive symptoms. Amyloid burden was negatively associated with outlier count.<h4>Discussion</h4>Brain atrophy in AD is highly heterogeneous and neuroanatomical normative modeling can be used to explore anatomo-clinical correlations in individual patients.","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jan-Mar","modification":"2026-07-07T03:11:36.409Z","creation":"2026-07-07T03:08:18.762Z"},"accession":"S-EPMC10937817","cross_references":{"pubmed":["38487076"],"doi":["10.1002/dad2.12559"]}}