Full exploitation of high dimensionality in brain imaging: The JPND working group statement and findings

Abstract

Advances in technology enable increasing amounts of data collection from individuals for biomedical research. Such technologies, for example, in genetics and medical imaging, have also led to important scientific discoveries about health and disease. The combination of multiple types of high-throughput data for complex analyses, however, has been limited by analytical and logistic resources to handle high-dimensional data sets. In our previous EU Joint Programme–Neurodegenerative Disease Research (JPND) Working Group, called HD-READY, we developed methods that allowed successful combination of omics data with neuroimaging. Still, several issues remained to fully leverage high-dimensional multimodality data. For instance, high-dimensional features, such as voxels and vertices, which are common in neuroimaging, remain difficult to harmonize. In this Full-HD Working Group, we focused on such harmonization of high-dimensional neuroimaging phenotypes in combination with other omics data and how to make the resulting ultra-high-dimensional data easily accessible in neurodegeneration research.

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

“…Of particular interest, we found that genetic loci affecting brain morphology show enrichment for developmentally regulated genes 13 and human-specific regulatory elements 26,27 . Ongoing efforts are beginning to map these genetic effects at a finer-grained spatial resolution using shape analysis, surface-and voxel-based analyses [28][29][30][31] . Moving beyond the mass univariate methods, which analyze each brain measure separately, ENIGMA has begun to use multivariate methods to meet the challenge of quantifying the complex relationships between brain networks-or 'connectomes'-and the genome [32][33][34] .…”