Flexible multivariate models for linking multi-scale connectome and genome data in Alzheimer's disease and related disorders

Abstract COVID-19 is having a major impact around the world, however we are still learning about the mechanisms and manifestations of this illness. There is considerable evidence of neurologicalsymptoms that occur in COVID-19 patients. However the impact of this, and its relationship withage, on brain structure have not been studies at all thus far. We propose to use multivariate approaches to extract covarying brain patterns from individuals to study changes associated withCOVID-19 as well as potential interactions with age in older individuals. We will leverage the approaches being developed as part of the parent award, but customize them to incorporate spatial priors to address ischemic lesions. We will evaluate COVID-19 and age effects on these networks and compare them with networks extracted from normative data. We will share the methods via user friendly tools. Results are expected to provide insights into the neurological manifestations of COVID-19 including age specific effects.