Grand Challenges: Genetic and Lifestyle Risk Factors of Accelerated Brain Aging in Severe Mental Illness
A Multimodal and Multi-Omics Approach
Severe mental illnesses (SMI), including schizophrenia spectrum disorder, bipolar disorder, and major depressive disorder, present a major global and economic health burden. SMI patients have a greater risk of Alzheimer’s dementia before age 70 due to accelerated brain aging, however, the risk factors for accelerated brain aging in SMI remain unknown. In this project, we will jointly analyze both structural and functional imaging data to study brain aging trajectories among individuals with SMI, capturing the different temporal, spatial, and biological characteristics in assessing brain age. We will further integrate with multi-omics (e.g. genotype, gene expression and metabolite profiles) and lifestyle (e.g. smoking, alcohol drinking, diet, obesity and physical activity) data and develop novel machine learning, statistical genetic and causal inference methods to identify the genetic and lifestyle risk and protective factors that modulate accelerated brain aging in SMI. Our overarching goal is to understand the regulatory mechanism of accelerated brain aging in SMI and the complex causal relationship between genetics, environment, brain aging and SMI, and ultimately prevent the premature aging in SMI. Our work addresses an important grand challenge of global mental health and provides possible solutions to clinical implications for SMI patients, which can potentially reduce the excess morbidity and mortality of SMI and improve health of millions of people.
PI: Tianzhou Ma (SPHL),
Assistant Professor, Epidemiology and Biostatistics