Differentially expressed genes reflect disease-induced rather than disease-causing changes in the transcriptome.

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Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_253FEBED3C3F
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Differentially expressed genes reflect disease-induced rather than disease-causing changes in the transcriptome.
Journal
Nature communications
Author(s)
Porcu E., Sadler M.C., Lepik K., Auwerx C., Wood A.R., Weihs A., Sleiman MSB, Ribeiro D.M., Bandinelli S., Tanaka T., Nauck M., Völker U., Delaneau O., Metspalu A., Teumer A., Frayling T., Santoni F.A., Reymond A., Kutalik Z.
ISSN
2041-1723 (Electronic)
ISSN-L
2041-1723
Publication state
Published
Issued date
24/09/2021
Peer-reviewed
Oui
Volume
12
Number
1
Pages
5647
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: epublish
Abstract
Comparing transcript levels between healthy and diseased individuals allows the identification of differentially expressed genes, which may be causes, consequences or mere correlates of the disease under scrutiny. We propose a method to decompose the observational correlation between gene expression and phenotypes driven by confounders, forward- and reverse causal effects. The bi-directional causal effects between gene expression and complex traits are obtained by Mendelian Randomization integrating summary-level data from GWAS and whole-blood eQTLs. Applying this approach to complex traits reveals that forward effects have negligible contribution. For example, BMI- and triglycerides-gene expression correlation coefficients robustly correlate with trait-to-expression causal effects (r <sub>BMI </sub> = 0.11, P <sub>BMI </sub> = 2.0 × 10 <sup>-51</sup> and r <sub>TG </sub> = 0.13, P <sub>TG </sub> = 1.1 × 10 <sup>-68</sup> ), but not detectably with expression-to-trait effects. Our results demonstrate that studies comparing the transcriptome of diseased and healthy subjects are more prone to reveal disease-induced gene expression changes rather than disease causing ones.
Pubmed
Web of science
Open Access
Yes
Create date
18/01/2021 21:58
Last modification date
12/01/2022 7:08
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