The scientific goal of this F31 proposal is to investigate network-level alterations in brain integrity associated with genetic variation in four candidate genes implicated in age-related cognitive decline. Although a large body of research has identified focal alterations in brain integrity in patients with Alzheimer's disease (AD), it i likely that neurodegeneration affects interconnected cortical networks rather than single brain regions in isolation. The proposed project will focus on two resting state networks that include brain regions typically compromised by AD pathology: the default mode network (DMN) and executive control network (ECN). By studying carriers of risk alleles who do not show overt impairment, the proposed research may identify differences in brain network structure and function that serve as preclinical indicators of dementia. The primary aims are to (1) examine genotype differences in functional connectivity of the DMN and ECN; (2) to characterize the association between gene polymorphisms and white matter tracts connecting regions of the DMN and ECN, respectively; and (3) to examine global network differences associated with gene polymorphisms by using a graph theoretical approach to assess the organization of the integrated functional- structural network. This will be accomplished through analysis of DNA and multi-modal imaging data collected from approximately 150 healthy, cognitively normal middle-aged adults, including both carriers and non- carriers of risk alleles. Combining indices of functional and structural connectivity provides an innovative way of describing network integrity in adults at risk for AD. The findings will lead to a better understanding of network- level alterations in brain structure and function that may contribute to age-related changes in cognitive function. Studying middle-aged individuals may establish these network-level characteristics as important early indices of risk of impairment, which may inform prevention or early intervention efforts. Additionally, this proposal draws on the expertise of an exemplary interdisciplinary team to support the candidate's training as a developing research scientist. The training plan will develop competency in neuroimaging methods and quantitative analysis, expertise in connectivity analyses of resting state functional MRI and diffusion tensor imaging, knowledge of the genetics of brain aging, responsible conduct of research, and scholarly dissemination of results. The fundamental outcomes of this proposal are well aligned with the goals of the NIA and may inform the development of novel AD detection and treatment strategies.
Alzheimer's disease will affect an estimated 13.8 million people by the year 2050, resulting in significant economic burden and reduction in quality of life for patients and their families. With the number of older adults in the U.S. steadily growing, it i increasingly important to identify better methods of dementia detection and intervention. Studying gene differences in brain networks during middle age, before the onset of clinical symptoms, may lead to the development of successful early detection and treatment strategies for Alzheimer's disease.
| Korthauer, L E; Zhan, L; Ajilore, O et al. (2018) Disrupted topology of the resting state structural connectome in middle-aged APOE ?4 carriers. Neuroimage 178:295-305 |
