Dataset Information

Regional imaging genetic enrichment analysis.

ABSTRACT:

Motivation

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 interpretation and modest dimensionality compared with voxelwise approaches. Typical ROI-level measures used in these studies are summary statistics from voxelwise measures in the region, without making full use of individual voxel signals.

Results

In this article, we propose a flexible and powerful framework for mining regional imaging genetic associations via voxelwise enrichment analysis, which embraces the collective effect of weak voxel-level signals and integrates brain anatomical annotation information. Our proposed method achieves three goals at the same time: (i) increase the statistical power by substantially reducing the burden of multiple comparison correction; (ii) employ brain annotation information to enable biologically meaningful interpretation and (iii) make full use of fine-grained voxelwise signals. We demonstrate our method on an imaging genetic analysis using data from the Alzheimer's Disease Neuroimaging Initiative, where we assess the collective regional genetic effects of voxelwise FDG-positron emission tomography measures between 116 ROIs and 565 373 single-nucleotide polymorphisms. Compared with traditional ROI-wise and voxelwise approaches, our method identified 2946 novel imaging genetic associations in addition to 33 ones overlapping with the two benchmark methods. In particular, two newly reported variants were further supported by transcriptome evidences from region-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.

Availability and implementation

The R code and sample data are freely available at https://github.com/lshen/RIGEA.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Yao X

PROVIDER: S-EPMC7178438 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:A number of genetic loci are associated with risk for Parkinson's disease (PD) based on genome-wide association studies; however, the relationship between genetic variants and nigrostriatal degeneration, which is the structural correlate of parkinsonism, has not been reported. OBJECTIVES:We quantified nigrostriatal dopaminergic integrity with image analysis of putaminal tyrosine hydroxylase immunoreactivity in 492 brains with Lewy body disease and used this pathologic endophenotype to explore possible association with PD genetic variants. METHODS:The study cases had Lewy-related pathology and variable degrees of nigrostriatal degeneration. They were assigned to one of the following clinical subgroups according to their predominant clinical syndrome: parkinsonism-predominant, parkinsonism+dementia, and dementia-predominant. In addition to putaminal tyrosine hydroxylase immunoreactivity, semiquantitative scoring was used to assess substantia nigra neuronal loss. A total of 29 PD genetic risk variants were genotyped on each case. RESULTS:When compared with controls, tyrosine hydroxylase immunoreactivity was reduced in Lewy body cases in the dorsolateral (79%) and ventromedial (57%) putamen. The dorsolateral region was better preserved in dementia-predominant cases than in cases with parkinsonism. Dorsolateral putaminal tyrosine hydroxylase immunoreactivity correlated with neuronal loss in the ventrolateral substantia nigra. Genetic analyses showed no significant association of PD risk variants with putaminal tyrosine hydroxylase immunoreactivity. CONCLUSIONS:The results confirm regional differences in putaminal dopaminergic degeneration and vulnerability of nigrostriatal pathway in Lewy body disorders with parkinsonism. The lack of association with PD genetic risk variants suggests that they may not be associated with quantitative endophenotypes of nigrostriatal degeneration, but more likely related to the risk of disease per se. © 2017 International Parkinson and Movement Disorder Society.