Grant: Operating Grant: Future Leaders in Canadian Brain Research Program

As the number of older adults is rising, late-life conditions such as dementia and late-life depression become more taxing on the healthcare system. Neurodegeneration, white matter lesions and changes in functional organization of brain networks are harbingers of worse brain health outcomes, with specific circuits affected in different neurological and psychiatric disorders. Worse executive function, memory and processing speed are also considered risk markers for dementia and cut across several psychiatric conditions[1]. Late-life determinants of brain and cognitive health are complex and intertwined. However, the increasing availability of large-scale well phenotyped mid- and late-life cohorts with proteomic data is promising for disentangling the contributions of different biological pathways and environmental factors to brain and cognitive health. In this project, we aim to identify proteomic markers for brain and cognitive health. We will then build on our recent investigations of gene-by-environment interactions[2] to identify the extent to which these biomarkers are specific to modifiable conditions like cardiovascular disease, depression and alcohol use in a proteome-by-environment analyses. More specifically, we aim to: Aim 1: identify robust proteomic associations (~3,000 proteins) with brain and cognitive health in the UK Biobank and replicate and validate these associations in the smaller ADNI cohort. H1: Higher levels of inflammatory markers will predict degradation of the HPA axis, with lower hippocampal and temporal volumes and worse memory. Higher levels of cardiovascular and neurological markers will predict degradation of fronto-striatal circuits and worse executive function. Aim 2: test for protein-by-environment and protein-by-sex interactions on brain and cognitive health. H2: We will identify some neurology and inflammatory proteins that predict cognitive function in people with cardiovascular health issues specifically. Exploratory Aim: better understand the genomic regulators and correlates of the proteome-brain health associations using protein QTL data[3] and anatomical gene expression maps[4–6], respectively.