Person:

Hutchinson, John

We hypothesize that the phenomenon of allele-specific methylation (ASM) may underlie the phenotypic effects of multiple variants identified by Genome-Wide Association studies (GWAS). We evaluate ASM in a human population and document its genome-wide patterns in an initial screen at up to 380,678 sites within the genome, or up to 5% of the total genomic CpGs. We show that while substantial inter-individual variation exists, 5% of assessed sites show evidence of ASM in at least six samples; the majority of these events (81%) are under genetic influence. Many of these cis-regulated ASM variants are also eQTLs in peripheral blood mononuclear cells and monocytes and/or in high linkage-disequilibrium with variants linked to complex disease. Finally, focusing on autoimmune phenotypes, we extend this initial screen to confirm the association of cis-regulated ASM with multiple complex disease-associated variants in an independent population using next-generation bisulfite sequencing. These four variants are implicated in complex phenotypes such as ulcerative colitis and AIDS progression disease (rs10491434), Celiac disease (rs2762051), Crohn's disease, IgA nephropathy and early-onset inflammatory bowel disease (rs713875) and height (rs6569648). Our results suggest cis-regulated ASM may provide a mechanistic link between the non-coding genetic changes and phenotypic variation observed in these diseases and further suggests a route to integrating DNA methylation status with GWAS results.

Abstract Attempts to develop drugs that address sepsis based on leads developed in animal models have failed. We sought to identify leads based on human data by exploiting a natural experiment: the relative resistance of children to mortality from severe infections and sepsis. Using public datasets, we identified key differences in pathway activity (Pathprint) in blood transcriptome profiles of septic adults and children. To find drugs that could promote beneficial (child) pathways or inhibit harmful (adult) ones, we built an in silico pathway drug network (PDN) using expression correlation between drug, disease, and pathway gene signatures across 58,475 microarrays. Specific pathway clusters from children or adults were assessed for correlation with drug‐based signatures. Validation by literature curation and by direct testing in an endotoxemia model of murine sepsis of the most correlated drug candidates demonstrated that the Pathprint‐PDN methodology is more effective at generating positive drug leads than gene‐level methods (e.g., CMap). Pathway‐centric Pathprint‐PDN is a powerful new way to identify drug candidates for intervention against sepsis and provides direct insight into pathways that may determine survival.

We empirically examined the strengths and weaknesses of two human genome-wide DNA methylation platforms: rapid multiplexed reduced representation bisulfite sequencing and Illumina’s Infinium BeadChip. Rapid multiplexed reduced representation bisulfite sequencing required less input DNA, offered more flexibility in coverage, and interrogated more CpG loci at a higher regional density. The Infinium covered slightly more protein coding, cancer-associated and mitochondrial-related genes, both platforms covered all known imprinting clusters, and rapid multiplexed reduced representation bisulfite sequencing covered more microRNA genes than the HumanMethylation450, but fewer than the MethylationEPIC. Rapid multiplexed reduced representation bisulfite sequencing did not always interrogate exactly the same CpG loci, but genomic tiling improved overlap between different libraries. Reproducibility of rapid multiplexed reduced representation bisulfite sequencing and concordance between the platforms increased with CpG density. Only rapid multiplexed reduced representation bisulfite sequencing could genotype samples and measure allele-specific methylation, and we confirmed that Infinium measurements are influenced by nearby single-nucleotide polymorphisms. The respective strengths and weaknesses of these two genome-wide DNA methylation platforms need to be considered when conducting human epigenetic studies.