Whole genome sequence analyses of brain imaging measures in the Framingham Study
- PMID: 29282330
- PMCID: PMC5772158
- DOI: 10.1212/WNL.0000000000004820
Whole genome sequence analyses of brain imaging measures in the Framingham Study
Abstract
Objective: We sought to identify rare variants influencing brain imaging phenotypes in the Framingham Heart Study by performing whole genome sequence association analyses within the Trans-Omics for Precision Medicine Program.
Methods: We performed association analyses of cerebral and hippocampal volumes and white matter hyperintensity (WMH) in up to 2,180 individuals by testing the association of rank-normalized residuals from mixed-effect linear regression models adjusted for sex, age, and total intracranial volume with individual variants while accounting for familial relatedness. We conducted gene-based tests for rare variants using (1) a sliding-window approach, (2) a selection of functional exonic variants, or (3) all variants.
Results: We detected new loci in 1p21 for cerebral volume (minor allele frequency [MAF] 0.005, p = 10-8) and in 16q23 for hippocampal volume (MAF 0.05, p = 2.7 × 10-8). Previously identified associations in 12q24 for hippocampal volume (rs7294919, p = 4.4 × 10-4) and in 17q25 for WMH (rs7214628, p = 2.0 × 10-3) were confirmed. Gene-based tests detected associations (p ≤ 2.3 × 10-6) in new loci for cerebral (5q13, 8p12, 9q31, 13q12-q13, 15q24, 17q12, 19q13) and hippocampal volumes (2p12) and WMH (3q13, 4p15) including Alzheimer disease- (UNC5D) and Parkinson disease-associated genes (GBA). Pathway analyses evidenced enrichment of associated genes in immunity, inflammation, and Alzheimer disease and Parkinson disease pathways.
Conclusions: Whole genome sequence-wide search reveals intriguing new loci associated with brain measures. Replication of novel loci is needed to confirm these findings.
Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.
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Comment in
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Comment: Unraveling DNA sequence to identify cerebral indicators of dementia risk.Neurology. 2018 Jan 16;90(3):109. doi: 10.1212/WNL.0000000000004838. Epub 2017 Dec 27. Neurology. 2018. PMID: 29282334 No abstract available.
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