Beyond the Bulk: Cell-type Specific Resolution of Epigenomic and Transcriptomic Disease Signatures

Understanding how molecular changes contribute to human health and disease requires analytical approaches capable of resolving the cellular heterogeneity of complex tissues. Traditional bulk RNA and DNA methylation analyses average molecular signals across all cell-types in a sample, obscuring important cell-type specific variation. This dissertation applies and refines cell-type specific methodologies, statistical deconvolution of bulk data and single-nucleus RNA sequencing (snRNA-seq), to identify epigenomic and transcriptomic changes in both developmental and psychiatric contexts. The included studies span four investigations. First, cell-type specific methylome-wide association studies (MWAS) of neonatal blood were used to dissect common and unique DNA methylation patterns associated with early-life health risks. Second, novel analyses revealed that maternal obstetric pain relief, including laughing gas and pudendal block, is associated with distinct neonatal methylation changes in specific immune cell-types. Third, transcriptomic fine-mapping of bipolar disorder GWAS loci identified 20 validated genes across 13 cell-types, linking genetic risk to functional gene expression changes in the human brain. Finally, by integrating bulk and snRNA-seq data, this dissertation demonstrates that transcriptional brain aging is accelerated in psychiatric disorders and varies by cell-type, with excitatory neurons showing the largest increases. Methodological innovations include combining down-sampling and weighted regression for transcriptomic aging clocks, and integrating factor analysis with deconvolution to improve clinical phenotype interpretation. Taken together, this work highlights the importance of cellular resolution in molecular biology and offers tools and insights that improve both mechanistic understanding and translational potential. By identifying cell-type specific molecular signatures, this research provides a more nuanced view of disease risk, developmental programming, and biological aging, laying the groundwork for more precise diagnostic and therapeutic strategies.