The Neuropathologic Landscape of Alzheimer's Disease in Hispanic Decedents

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Abstract: Hispanics are the fastest growing population in the US and epidemiological data suggests they are at a higher risk of developing Alzheimer’s disease and have a higher occurrence of cerebrovascular disease (CVD) when compared to non-Hispanic Whites (NHWs). AD is defined neuropathologically by the deposition of neurofibrillary tangles (NFTs) and amyloid plaques. In addition to these hallmarks, many AD patients have mixed neuropathologies, including Lewy bodies (LBs) and pathological indices of CVD. Studies, involving mainly NHWs, have shown associations of these neuropathologies with clinical, genetic, and demographic variables providing insights into disease mechanisms and prevention strategies. However, there is a relative dearth of neuropathology studies on Hispanics. It is imperative to have neuropathology studies with individuals having diverse characteristics as this maximizes variability allowing for better identification of disease risk factors for more precision in development of preventative measures. This study will examine the neuropathologic landscape (the presence, location, and density of NFTs, plaques, CVD and LBs) of Hispanics compared to NHWs and determine if this landscape is altered by clinical, genetic, and demographic variables. To achieve efficiencies in time and further measurement precision we will enhance and adapt innovative machine learning algorithms to narrow in on pathology location and provide more quantitative analyses. Based on previous findings our central hypothesis is that Hispanics will have different neuropathologic landscapes when compared to NHWs and these differences are influenced by underlying risk factors, especially cardiovascular risk factors. Our specific aims are to: 1) profile the presence, location, and semi-quantitative densities of NFTs, plaques, LBs, and pathological indices of CVD in the setting of AD in Hispanics compared to NHWs, 2) profile and determine if pathologic measures from Aim 1 are altered by clinical, genetic, and demographic variables (APOE status, Hispanic origin, age at death, clinical history of cerebrovascular events (i.e. stroke), hyperlipidemia, diabetes, hypertension, sex, and/or education) and 3) strengthen and adapt a deep learning pipeline for quantifying AD pathologies. We will capitalize on existing well-characterized resources within three Alzheimer’s disease centers at University of California- Davis, the University of California- San Diego, and Columbia that contain a diverse autopsy confirmed AD Hispanic and NHW cohort. Also, we will use machine learning resources at the University of California San Francisco. This proposal will be the first largescale initiative to delineate the neuropathology in over 100 Hispanics of Mexican, Puerto Rican, Cuban, and Dominican origins compare to over 200 NHWs and determine the impact of comorbid risk factors. Profiling neuropathologic landscapes and understanding underlying factors has potential to shed light on mechanistic differences in disease development leading to better diagnosis, treatment, and prevention strategies. Results will directly advance understanding of brain health (pathology) in an important and growing part of the elderly population that to date there is miniscule neuropathology information.