Computation and resource efficient genome-wide association analysis for large-scale imaging studies - PubMed
3 hours ago
- #computational efficiency
- #imaging genetics
- #genome-wide association study
- Introduces RVGA framework for voxel-level genome-wide association studies, reducing computational time and storage by over 200 times.
- RVGA enhances statistical power by denoising images and sharing minimal datasets of summary statistics for secondary analyses.
- Provides a unified estimator for voxel heritability, genetic correlations between voxels, and cross-trait genetic correlations.
- Applied to UK Biobank data (n=53,454), revealing 39 novel loci for hippocampus shape and 275 for white matter microstructure.
- Identifies heterogeneity in heritability within images and subregions sharing genetic bases with 14 brain-related phenotypes.
- Replicates known genetic associations and uncovers new discoveries, such as correlations between hippocampus and educational attainment.
- Authors report potential competing interests but state they are unrelated to the study.