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

NIH RePORTER · NIH · RF1 · $143,254 · view on reporter.nih.gov ↗

Abstract

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 neurological symptoms that occur in COVID-19 patients. However the impact of this, and its relationship with age, 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 with COVID-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.

Key facts

NIH application ID
10157432
Project number
3RF1AG063153-01A1S1
Recipient
GEORGIA STATE UNIVERSITY
Principal Investigator
VINCE D CALHOUN
Activity code
RF1
Funding institute
NIH
Fiscal year
2020
Award amount
$143,254
Award type
3
Project period
2019-08-01 → 2024-03-31