UCLA

Neuropsychiatric disorders are brain disorders involving complex genetics, molecular, cellular, and circuitry mechanisms. Recent advances in multimodal omics data and systems biology tools have enabled modeling and dissection of the underlying pathogenic mechanisms in silico. However, such approaches have not been widely adopted in the neuropsychiatric field. My dissertation focuses on the applications of various system biology approaches, especially network-based multi-omics integration methods, to unveil the pathogenic mechanisms of neuropsychiatric disorders. I firstly reviewed and surveyed the current state of network modeling usage in studying neuropsychiatric disorders. I then applied various system biology tools, including Mergeomics and WGCNA, to identify the molecular, network, cellular, and connectome basis of sex-specific transcriptional changes caused by chronic adolescent exposure to cannabis. I also expanded the network applications from tissue level to single-cell resolution, and constructed cell-level networks informed by common genetic variants of autism spectrum disorder to predict potential key regulators of the affected networks for drug repurposing. In summary, my studies revealed novel pathogenic mechanisms across multiple levels of biological complexity, provided databases of networks and key regulators for query, and offered potential therapeutic targets for multiple neuropsychiatric disorders.