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

The UK Biobank study has produced thousands of brain imaging-driven 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.