DNA methylation is an important epigenetic mark with a regulated pattern in healthy tissues. Disruption of this pattern, called methylation dysregulation, has been reported in many diseases including cancer, autoimmune diseases, metabolic and psychological disorders, and diseases related to aging. Importantly, methylation dysregulation has been observed in pre-disease states and the degree of dysregulation correlates with disease severity and also response to treatment. These observations compel the study of methylation dysregulation because it may reveal common origins of human disease, and because genomic elements (e.g. genes, mutations, and regulatory features) associated with methylation dysregulation may be potential targets for diagnostic and early intervention therapies. However, the genomic elements that control and maintain methylation dysregulation have not been well-characterized. Understanding the mechanisms and pathways that are responsible for the establishment of epigenetic dysregulation is critical for understanding the establishment of the disease phenotype in general. We hypothesize that specific genomic elements could contribute to methylation dysregulation in reproducible ways across diseases. This research seeks to identify genomic elements that may initiate a disease state that is common across multiple diseases. This will be accomplished by the development of computational algorithms to leverage and integrate patient samples from many diseases, as well as the development of a new high-throughput genomic screen. Specifically, we propose the following specific aims: (1) Identification of genes associated with methylation dysregulation using a pan-disease machine-learning approach; (2) Exploration of the contribution of the noncoding genome to methylation dysregulation through analysis of genome variants and chromatin accessibility data; (3) Development and validation of a novel CRISPR screen to link gene perturbations to methylation landscapes in a high-throughput manner. In summary, completion of these aims will produce an in-depth characterization of the genomic elements associated with methylation dysregulation, leading to understanding of the processes and mechanisms of epigenetic dysregulation. More broadly, the proposed analysis framework and computational approach will explore the utility of integrative pan-disease studies to identify common characteristics of disease which could lead to diagnostic and therapeutic solutions. This proposal takes advantage of the applicant's expertise in genetics, genomics, and high-throughput assays. It also includes training and research experience in experimental design and execution which will advance the candidate's goal of becoming an independent research scientist capable of investigating genome function, specifically the genomic origins of human disease.