Deconvolution of bulk blood eQTL effects into immune cell subpopulations

Expression quantitative trait loci(eQTL) studies are used to interpret the function of disease-associated genetic risk factors. To date, most eQTL analyses have been conducted in bulk tissues, such as whole blood and tissue biopsies, which are likely to mask the cell typecontext of the eQTL regulatory effects. Although this context can be investigated by generating transcriptional profiles from purified cell subpopulations, the current methods are labor-intensive and expensive. Here we introduce a new method, Decon2, a statistical framework for estimating cell proportions using expression profiles from bulk blood samples (Decon-cell) and consecutive deconvolutionof cell typeeQTLs (Decon-eQTL). The estimated cell proportions from Decon-cell agree with experimental measurements across cohorts (R ≥ 0.77). Using Decon-cell we can predict the proportions of 34 circulating cell typesfor 3,194 samples from a population-based cohort. Next we identified 16,362 whole blood eQTLs and assign them to a cell typewith Decon-eQTL using the predicted cell proportions from Decon-cell. DeconvolutedeQTLs show excellent allelic directional concordance with those of eQTL(≥ 96%) and chromatin mark QTL (≥87%) studies that used either purified cell subpopulations or single-cell RNA-seq. Our new method provides a way to assign cell typeeffects to eQTLs from bulk blood, which is useful in pinpointing the most relevant cell typefor a certain complex disease. Decon2 is available as an R package and Java application (https://github.com/molgenis/systemsgenetics/tree/master/Decon2), and as a web tool (www.molgenis.org/ deconvolution).