Abstract
SummaryCharacterizing the multifaceted contribution of genetic and epigenetic factors to disease phenotypes is a major challenge in human genetics and medicine. We carried out high-resolution genetic, epigenetic, and transcriptomic profiling in three major human immune cell types (CD14+ monocytes, CD16+ neutrophils, and naive CD4+ T cells) from up to 197 individuals. We assess, quantitatively, the relative contribution of cis-genetic and epigenetic factors to transcription and evaluate their impact as potential sources of confounding in epigenome-wide association studies. Further, we characterize highly coordinated genetic effects on gene expression, methylation, and histone variation through quantitative trait locus (QTL) mapping and allele-specific (AS) analyses. Finally, we demonstrate colocalization of molecular trait QTLs at 345 unique immune disease loci. This expansive, high-resolution atlas of multi-omics changes yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk.
Highlights
Many human complex diseases are characterized by dysregulation of immune and inflammatory activity
Molecular quantitative trait locus (QTL) studies testing for associations between genetic variants and intermediate phenotypes, in particular gene expression levels, provide powerful approaches to annotate the putative consequence of disease associations (Montgomery and Dermitzakis, 2011)
We used a multi-step purification strategy (Figure S1) to isolate, for each donor, cell subsets corresponding to classical monocytes (CD14+CD16À) and neutrophils (CD66b+CD16+)
Summary
Many human complex diseases are characterized by dysregulation of immune and inflammatory activity. Genetic effects on gene expression have been shown to be often context-specific (Kundaje et al, 2015) and are better captured in studies probing multiple primary cell types or experimental conditions (Bentham et al, 2015; Fairfax et al, 2014; Naranbhai et al, 2015). Extending these analyses beyond gene expression to other molecular phenotypes such as variable histone modification or methylation status can greatly enhance the functional and mechanistic interpretation of genetic associations (Allum et al, 2015). Recent studies in cell line models have demonstrated the occurrence of a high degree of local coordination between transcriptional and epigenetic states and suggested that a fraction of
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