Understanding ethno-racial differences in AT(N)-defined heterogeneity profiles

PROJECT ABSTRACT Alzheimer disease (AD) is a highly heterogeneous disorder which varies in presentation within and across diverse communities and backgrounds. Neuroanatomically, heterogeneity is observed in the topographical patterns of amyloid (A), tau (T), and neurodegeneration (N) markers used to stage AD. For example, patterns of tau accumulation and brain atrophy are highly correlated and have been subtyped by advanced multivariate and machine learning methods into those involving typical AD regions (e.g., medial-temporal, lateral temporoparietal), hippocampal-sparing, limbic-predominant regions or minimal atrophy, while amyloid accumulation can be subtyped into frontal, parietal, and occipital regions. Notably, spatial subtypes are associated with distinct cognitive, genetic (e.g., APOE e4 genotype), and fluid biomarker profiles, thus suggesting that clinical heterogeneity may in part stem from neuroanatomical heterogeneity. Although neuroanatomical heterogeneity in AD has important implications for cognitive and functional outcomes as well as patient-specific treatments, there is a large gap in the literature regarding AD biomarker topographical patterns in ethno-racial groups. Similarly, it is largely unknown to what extent socio-demographic factors affect spatial heterogeneity. The present study fills a critical gap in the literature by including under-represented groups and relevant socio-demographic factors in the investigation of heterogeneity in AT(N) imaging markers. Using data from the racially and ethnically diverse Health and Aging Brain Study – Health Disparities (HABS-HD), this study will A) determine AD heterogeneity profiles (i.e., spatial subtypes and magnitude) for A, T, and N neuroimaging markers (i.e., magnetic resonance imaging [MRI], amyloid and tau positron emission tomography [PET]) using a machine learning approach; B) assess within and between group differences in heterogeneity profiles across Mexican-Americans, Blacks, and non-Hispanic Whites (NHW); and C) assess overall effects of socio-demographic factors (e.g., area deprivation index, income, education etc.) on A, T, and N heterogeneity profiles within and between ethno-racial groups. Biomarker cut-points and group-level composites used to classify individuals in research and clinical settings are often informed through the identification of AD-specific or AD-vulnerable brain regions. However, the identified AD-sensitive regions and associated cut-points are typically derived from one group (i.e., NHWs) and applied to all. Characterizing heterogeneity in AT(N) imaging markers using a diverse and representative sample is therefore crucial to informing whether AD-sensitive regions are similar across individuals and thus whether current cut-points are appropriate.