UCLA

This dissertation examines significant risk loci identified through GWAS for neuropsychiatric illness to prioritize causal variants and genes for future validation in functional assays. This investigation focuses on the impact of risk loci on molecular traits, and whether these functionally relevant variants are associated with GWAS-SNPs for neuropsychiatric phenotypes. Chapter 1 explores the integration of three complementary next-generation sequencing approaches, including genotyping, gene expression, and chromatin accessibility in hundreds of fibroblast cell lines of a multi-ancestry cohort of bipolar disorder patients and controls. Chapter 2 investigates the blood transcriptomes of a larger cohort, including a broader spectrum of bipolar disorder and schizophrenia diagnoses, and how application of computational cell type deconvolution methods can further highlight potentially relevant genes. Chapter 3 delves into metabolomics of cerebrospinal fluid in Alzheimer’s patients and healthy controls, allowing for the investigation of neurobiological mechanisms in vivo. We find that the integration of multiple omics levels significantly enhances our understanding of GWAS risk loci by uncovering the functional consequences and molecular mechanisms of disease-associated loci.