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Deconvolution of bulk blood eQTL effects into immune cell subpopulations

BIOS Consortium, Aguirre-Gamboa, R., de Klein, N., di Tommaso, J., Claringbould, A., van der Wijst, M. G. P., de Vries, D., Brugge, H., Oelen, R., Vosa, U., Zorro, M. M., Chu, X., Bakker, O. B., Borek, Z., Ricano-Ponce, I., Deelen, P., Xu, C-J., Swertz, M., Jonkers, I., Withoff, S., Joosten, I., Sanna, S., Kumar, V., Koenen, H. J. P. M., Joosten, L. A. B., Netea, M. G., Wijmenga, C., Franke, L. & Li, Y., 12-Jun-2020, In : Bmc Bioinformatics. 21, 1, 23 p., 243.

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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 (https://github.com/molgenis/systemsgenetics/tree/master/Decon2) and as a web tool (www.molgenis.org/deconvolution).

Original languageEnglish
Article number243
Number of pages23
JournalBmc Bioinformatics
Volume21
Issue number1
Publication statusPublished - 12-Jun-2020

    Keywords

  • eQTL, Deconvolution, Cell types, Immune cells, ASSOCIATION, SURVIVAL, DRIVERS, FORMAT

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