Approved Research

Exploring genomic interrelationships between multi-modal imaging, clinical phenotypes and EHR

Lay summary

This research is based on two critical knowledge gaps: (1) The human brain has shared genetics with several complex human diseases but a high-dimensional multi-omic data-driven approach has not been established to identify genetic interrelationships between neuroimaging phenotypes and diseases across multiple organ systems from EHR (2) Sex- and ancestry-specific differences in late-age cognitive decline can be better understood by examining the relationship between diseases (e.g. cardiovascular and kidney related), lifestyle-related risk factors (e.g. chronic stress) and MRI of brains with early disease progression.

We will use a combination of approaches including phenome-wide association studies to identify genetic associations between image-derived phenotypes and EHR, lifestyle, clinical and behavioral phenotypes as well as introduce statistical approaches that can incorporate interactions between genotype and environmental/risk factors to understand the differences in genetic architectures of neuroimaging phenotypes between individuals with varying levels of disease risk (e.g., sex and ancestry).

This research is likely to help us better understand the genetic mechanisms underlying late-age cognitive decline as well as identify novel biomarkers for disease risk by visualizing connections between the brain, risk-factors for cardiometabolic diseases such as chronic stress, and neurodegeneration phenotypes. In particular, long-term chronic stress has been associated with poorer cognitive outcomes consistently, in addition to increasing the risk of dementia. Chronic psychosocial stress is also a well-known risk factor for cardiometabolic diseases such as hypertension and heart disease, especially among women and these diseases have well-known associations with cognitive impairment. Sex-specific analyses on this cohort could lead to designing better therapeutics for women given that women are much more likely to develop and die from both cardiometabolic diseases as well as late-age neurological diseases such as Alzheimer's.