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• W2896401987 abstract "Genetic risk factors associated with late-onset Alzheimer's disease (AD) are carried in each person's genome throughout life, but it is currently not known if these factors affect the development of the brain's functional networks. Measuring effects of genetic risk factors for AD on brain development is important because early changes in the brain may bias an individual toward healthy aging or AD later in life. We studied the effects of genetic risk factors on brain function in youth using an open neuroimaging/genomic dataset. We used genomic and neuroimaging data from the Philadelphia Neurodevelopmental Cohort (PNC) dataset (Neurodevelopmental Genomics: Trajectories of Complex Phenotypes, phs000607.v2.p2) to measure the relationship between genomic risk of late-onset AD and functional differences in the brains of youths age 9-15 (N=112). We assessed genomic risk of AD with a composite polygenic risk score for AD (ADRS). We measured the relationship between ADRS and brain function by processing resting-state functional MRI data from the same dataset using a seed-based approach, and then measuring the influence of the ADRS on resting-state functional connectivity (RSFC). We also measured the covariance of other factors of interest (e.g., age) on RSFC measures. Our preliminary findings suggest that the organization of functional brain networks in children is affected by a variety of factors. First, RSFC measures revealed a typical organization of functional brain networks in the PNC sample. Second, we observed that the RSFC pattern covaried with participant age. Third, we observed some evidence that RSFC patterns covaried with the ADRS of each participant. We studied the relationship between a polygenic risk score for AD and organization of functional brain networks in youth. We observed that typical patterns of brain organization were influenced by several factors, and we found some evidence consistent with effects of ADRS on functional brain organization. Future efforts to refine this developing methodology will test whether genetic factors predispose the brain toward AD, and those results will inform potential early interventions in a potential lifetime AD trajectory." @default.
• W2896401987 created "2018-10-26" @default.
• W2896401987 creator A5003104343 @default.
• W2896401987 date "2018-07-01" @default.
• W2896401987 modified "2023-10-16" @default.
• W2896401987 title "P4‐243: MEASURING THE INFLUENCE OF GENETIC RISK FACTORS ASSOCIATED WITH LATE‐ONSET ALZHEIMER'S DISEASE ON BRAIN FUNCTION IN YOUTH" @default.
• W2896401987 doi "https://doi.org/10.1016/j.jalz.2018.07.064" @default.
• W2896401987 hasPublicationYear "2018" @default.
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