October 10, 2024 Webinar
Bayesian Imaging genetics modeling for brain structural connectivity
Yize Zhao, PhD
Abstract:
With distinct advantages in power over behavioral phenotypes, brain imaging traits have become emerging endophenotypes to dissect molecular contributions to behaviors and neuropsychiatric illnesses. Among different imaging features, brain structural connectivity which summarizes the anatomical connections between different brain regions is one of the most cutting-edge traits; and the genetic influence on the structural connectivity variation remains highly elusive. We discuss two modeling frameworks to investigate the role brain structural connectivity plays to dissect genetic bases and link with disease profiles. Under Bayesian paradigms, in the first project, we developed a biologically plausible brain network response shrinkage model to comprehensively characterize the relationship between high dimensional genetic variants and the structural connectome phenotypes. Within the model, we accommodated the topology of brain network and biological architecture within the genome. In the second project, we further incorporate the disease outcome, and proposed a mediation analysis to explore the effect mechanism among genetic exposure, structural connectivity and time to disease onset. Extensive simulations confirmed the superiority of our methods compared with existing alternatives. By applying the methods to landmark brain connectivity and Alzheimer's disease studies, we obtained biologically plausible insights.
Short Bio:
Dr. Yize Zhao is a tenured Associate Professor in the Department of Biostatistics, Yale School of Public Health, Yale University. Her methodology research focuses on the development of statistical and machine learning methods to analyze large-scale complex data (neuroimaging, -omics, EHRs), Bayesian methods, feature selection, predictive modeling, data integration, missing data and network analysis. Her research has been supported by multiple NIH and foundation grants with her as the principal investigator or co-investigator. She also serves as an Associate Editor for Biometrics and a standing member of the NIH Biodata Management and Analysis (BDMA) study section.