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Abstract #3323

Multivariate data-driven approach to dissect imaging-genetic associations in Alzheimer’s disease

Xiaowei Zhuang1, Zhengshi Yang1, and Dietmar Cordes1
1Lou Ruvo Center for Brain Health, Cleveland Clinic, Las Vegas, NV, United States

Synopsis

Keywords: Alzheimer's Disease, Alzheimer's Disease, Imaging geneticsTo better characterize the Alzheimer’s disease pathogenesis and boost the statistical power, we applied a multivariate data-driven approach (independent component analysis (ICA)) to decompose 70000+ single nucleotide variants (SNVs) from 239 AD-associated genes into multiple functionally relevant subsets. We demonstrated that several genetic clusters identified by ICA could be specially associated with AD clinical diagnosis, AD amyloid or tau pathology, and/or MRI-derived neurodegenerative markers. This type of multivariate data-driven approach could be helpful to further delineate diagnoses-associated or neuropathology-associated genetic variants in AD.

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