Alzheimer's disease (AD) is the most common form of dementia, accounting for 50-75% of all cases. Clinical AD affects episodic memory first, but eventually results in global dementia, leaving patients severely cognitively impaired and unable to care for themselves. Marked brain atrophy, especially in the hippocampus, and disruption of normal structural and functional neural networks are all associated with AD. It is likely that thes changes are extremely difficult to reverse. Therefore, AD prevention strategies are needed to preserve brain health and prevent the neuronal loss that leads to morphological changes in the brain and cognitive decline. A key component of any disease-specific prevention strategy is the reliable identification of individuals who are at risk for developing the disease so that they may be enrolled in controlled clinical trials. Twin studies reveal that the heritability of AD is 60-80, and APOE genotype accounts for about 50% of the variation in heritability. Thus, there is a significant portion of heritability that is explained by other genes. AD risk genes identified in genome wide association studies and through bench experiments are potential candidates and provide possible targets for studying the molecular basis of AD pathogenesis. In addition, these genes may have clinical relevance in helping to identify individuals who are likely to develop AD. This proposal suggests using non-invasive imaging and cognitive measures to assess this potential clinical use. The goal is to ascertain whether non-APOE AD risk genes have additional clinical prediction value by creating indices of polygenic risk based on APOE status, family history of AD and additional AD risk genes. The predictive power of these scores will be assessed against multiple metrics of decline in a cohort of cognitively healthy older adults. Decline over a two-year period will be estimated based on early AD-related changes in brain structure that are supported in the literature, including cortical thinning within the hippocampus and across AD-vulnerable regions of the cortical ribbon (e.g., the precuneus, angular gyrus and others). Cognitive decline will be measured by creating memory domain Z-scores (derived from multiple memory performance measures, including recall of word lists, stories and visual word pairs) for each time point. Polygenic risk score may be a more sensitive predictor of decline in these metrics than APOE status alone. In order to identify individuals at highest risk for AD, thi proposal suggests a multidisciplinary approach that integrates multiple genetic risk factors with imaging and behavioral data. Taken together, these studies will provide a better understanding of the neural substrates and cognitive (memory) consequences of genetic risk for AD.
Alzheimer's disease (AD) primarily effects older adults and causes progressive cognitive decline with an eventual loss of independence, requiring substantial financial resources to provide care. In humans, neuroimaging methods, genetics and cognitive assessments are tools that can be used to learn about AD onset, progression and the functional consequences. It is essential that neuroimaging and genetic risk factors become further integrated, as this research proposes, so that individuals at greatest risk for developing AD may be identified and participate in future AD intervention trials.
