Deconvolution of bulk blood eQTL effects into immune cell subpopulations

BIOS Consortium, Raul Aguirre-Gamboa, Niek de Klein, Jennifer di Tommaso, Annique Claringbould, Monique G. P. van der Wijst, Dylan de Vries, Harm Brugge, Roy Oelen, Urmo Vosa, Maria M. Zorro, Xiaojing Chu, Olivier B. Bakker, Zuzanna Borek, Isis Ricano-Ponce, Patrick Deelen, Cheng-Jian Xu, Morris Swertz, Iris Jonkers, Sebo WithoffIrma Joosten, Serena Sanna, Vinod Kumar, Hans J. P. M. Koenen, Leo A. B. Joosten, Mihai G. Netea, Cisca Wijmenga, Lude Franke, Yang Li*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

30 Citations (Scopus)
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BACKGROUND: 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 type-context of the eQTL regulatory effects. Although this context can be investigated by generating transcriptional profiles from purified cell subpopulations, current methods to do this are labor-intensive and expensive. We introduce a new method, Decon2, as a framework for estimating cell proportions using expression profiles from bulk blood samples (Decon-cell) followed by deconvolution of cell type eQTLs (Decon-eQTL).

RESULTS: The estimated cell proportions from Decon-cell agree with experimental measurements across cohorts (R ≥ 0.77). Using Decon-cell, we could predict the proportions of 34 circulating cell types for 3194 samples from a population-based cohort. Next, we identified 16,362 whole-blood eQTLs and deconvoluted cell type interaction (CTi) eQTLs using the predicted cell proportions from Decon-cell. CTi eQTLs show excellent allelic directional concordance with eQTL (≥ 96-100%) and chromatin mark QTL (≥87-92%) studies that used either purified cell subpopulations or single-cell RNA-seq, outperforming the conventional interaction effect.

CONCLUSIONS: Decon2 provides a method to detect cell type interaction effects from bulk blood eQTLs that is useful for pinpointing the most relevant cell type for a given complex disease. Decon2 is available as an R package and Java application ( and as a web tool (

Original languageEnglish
Article number243
Number of pages23
JournalBmc Bioinformatics
Issue number1
Publication statusPublished - 12-Jun-2020


  • eQTL
  • Deconvolution
  • Cell types
  • Immune cells


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