Longitudinal Study of MRI, Clinical, and Genetic Biomarkers of Cognitive Impairment and Alzheimer's Disease in Elderly American Indians

点击翻译按钮获取中文摘要

ABSTRACT Precision medicine is the emerging practice of delivering healthcare tailored to patients on the basis of specific factors that contribute to disease risk, prognosis, and treatment response. The prospect of applying precision medicine to neurodegenerative disorders such as Alzheimer's disease (AD) is especially promising. Genetic markers, most notably variation in the apolipoprotein E gene, and measures of vascular brain injury and cerebral atrophy assessed by MRI have emerged as useful biomarkers of preclinical AD and risk of clinical disease. More than 3 million American Indians (AIs), Alaska Natives, Blacks, Latinos, and Asians suffer from AD, and experience earlier onset of cognitive impairment and AD than Whites. The few studies of AD in AIs are limited by small, single-community samples. We will use data from the Strong Heart Study (SHS) and ancillary Cerebrovascular Disease and its Consequences in American Indians (CDCAI) study to evaluate cognitive function, AD risk factors, and MRI-defined biomarkers of AD in older AIs. The SHS collected data from 4,549 AIs aged 45-74 years from tribes in the Southwest, Southern Plains, and Northern Plains in 3 phases from 1988 to 2000. The CDCAI study assessed cognitive function and MRI-defined vascular brain injury in 818 surviving SHS participants in 2010-2013 and is reassessing surviving participants with the same MRI and cognitive tests. We will use statistical mapping software to reprocess MRIs from both the original and follow-up CDCAI examinations and will create 3-dimensional brain maps for older AIs. We will quantify cerebral atrophy in brain regions preferentially affected by AD such as the hippocampus, parahippocampal, medial temporal, and parietal regions, and the posterior cingulate cortex. We will compare structural patterns on MRI at both CDCAI time points with normative data on AD patients from other populations. We will define probable AD cases by assessing change in MRI-defined loss in regions selectively affected by AD, in combination with AD-related cognitive test performance and activities of daily living; and examine associations of probable AD with risk factors and functional outcomes. Our Specific Aims are to: 1) establish AI-specific normative values of MRI atrophy in brain regions selectively affected by AD, and evaluate AD-related regional atrophy in combination with cognitive and behavioral changes to calculate prevalence of probable AD; 2) use genetic, sociodemographic, and clinical data on risk factors for AD observed in other populations to identify correlates of probable AD in elderly AIs; and 3) estimate associations of MRI markers of probable AD with measures of cognitive and physical function, independent of the effects of vascular brain injury. AD is the leading cause of dementia and of death in the US. The CDCAI sample is the only population-based cohort of AIs with MRI data and genetic biomarkers relevant to AD. We will leverage these unique data to address key elements of PM, namely, risk assessment and detection of preclinical pathophysiologic processes of AD among AIs.