Leveraging multimodal neuroimaging and GWAS for identifying modality-level causal pathways to Alzheimer’s disease

Welcome to our casual research seminar organized in the Department of Statistical Sciences at the University of Toronto. Our aim is to explore the diverse research conducted by our faculty, students, and postdocs. Talks usually last 30 to 45 minutes, followed by discussions. We cover current research, overviews of emerging topics, and more. Some pizza and soda will be offered before the seminar around 12:20pm.

Abstract: The UK Biobank study has produced thousands of brain imaging-derived phenotypes (IDPs) collected from more than 40,000 genotyped individuals so far, facilitating the investigation of genetic and imaging biomarkers for brain disorders. Motivated by efforts in genetics to integrate gene expression levels with genome-wide association studies (GWASs), recent methods in imaging genetics adopted an instrumental variable (IV) approach to identify causal IDPs for brain disorders. However, several methodological challenges arise with existing methods in achieving causality in imaging genetics, including horizontal pleiotropy and high dimensionality of candidate IVs. In this work, we propose testing the causality of each brain modality (i.e., structural, functional, and diffusion MRI) for each gene as a useful alternative, which offers an enhanced understanding of the roles of genetic variants and imaging features on behavior by controlling for the pleiotropic effects of IDPs from other imaging modalities.  We demonstrate the utility of the proposed method by using Alzheimer's GWAS data from the UK Biobank and the International Genomics of Alzheimer's Project (IGAP) study. Our method is implemented using summary statistics, which is available on GitHub. The paper is available on MedRxiv: https://www.medrxiv.org/content/10.1101/2025.02.27.25322897v1.

Seminar organizers: Austin Brown & Archer Gong Zhang & Piotr Zwiernik.