Abstract #3314

Identification of Brain Networks Associated with Alzheimer’s Disease Risk

Alexandra Badea¹, Ali Mahzarnia², Jacques S Stout³, Robert J Anderson², Hae Sol Moon⁴, Zay Yar Han², Kate Beck⁵, Jeffrey N Browndyke⁶, David Dunson⁷, Kim G Johnson⁵, and Richard J O'Brien⁸

¹Radiology, Neurology, BIAC, Duke Univ Medical Center, Durham, NC, United States, ²Radiology, Duke Univ Medical Center, Durham, NC, United States, ³BIAC, Duke Univ Medical Center, Durham, NC, United States, ⁴BME, Duke Univ Medical Center, Durham, NC, United States, ⁵Neurology, Duke Univ Medical Center, Durham, NC, United States, ⁶Psychiatry and Behavioral Sciences Department, Duke Univ Medical Center, Durham, NC, United States, ⁷Statistical Sciences, Duke University, Durham, NC, United States, ⁸Neurology, Duke University Medical Center, Durham, NC, United States

Synopsis

Keywords: Alzheimer's Disease, Alzheimer's Disease, AgingThe brain connectome helds promise to detect subtle changes in individuals at risk for Alzheimer's disease. We imaged using high resolution diffusion imaging 72 subjects enriched for the APOE4 genotype to reveal vulnerable networks associated with a composite AD risk factor including age, genotype, and sex. Sparse canonical correlation analysis (CCA) revealed a high weight associated with genotype, and subgraphs involving the cuneus, temporal, cingulate cortex, and cerebellum. Our results have identified structural brain networks and the associated weights for several risk factors for AD in preclinical stages.

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