| Literature DB >> 31742256 |
Xiaohui Yao1, Shan Cong2, Jingwen Yan3, Shannon L Risacher4, Andrew J Saykin4, Jason H Moore1, Li Shen1.
Abstract
Brain imaging genetics aims to reveal genetic effects on brain phenotypes, where most studies examine phenotypes defined on anatomical or functional regions of interest (ROIs) given their biologically meaningful annotation and modest dimensionality compared with voxel-wise approaches. Typical ROI-level measures used in these studies are summary statistics from voxel-wise measures in the region, without making full use of individual voxel signals. In this paper, we propose a flexible and powerful framework for mining regional imaging genetic associations via voxel-wise enrichment analysis, which embraces the collective effect of weak voxel-level signals within an ROI. We demonstrate our method on an imaging genetic analysis using data from the Alzheimers Disease Neuroimaging Initiative, where we assess the collective regional genetic effects of voxel-wise FDGPET measures between 116 ROIs and 19 AD candidate SNPs. Compared with traditional ROI-wise and voxel-wise approaches, our method identified 102 additional significant associations, some of which were further supported by evidences in brain tissue-specific expression analysis. This demonstrates the promise of the proposed method as a flexible and powerful framework for exploring imaging genetic effects on the brain.Entities:
Keywords: enrichment analysis; genetic association analysis; imaging genetics; voxel-wise analysis
Year: 2019 PMID: 31742256 PMCID: PMC6860973 DOI: 10.1109/BHI.2019.8834450
Source DB: PubMed Journal: IEEE EMBS Int Conf Biomed Health Inform